Inference_Colab.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "  # DT-SegNet\n",
        "\n",
        "  This notebook should be run in Google Colab. Tested at ver. 2024/03/06."
      ],
      "metadata": {
        "id": "MmMGZsrbTLyn"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Preparations"
      ],
      "metadata": {
        "id": "ccsmg9Mry0n1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Environment preparation\n",
        "\n",
        "%cd /content\n",
        "!git clone https://github.com/xiazeyu/DT_SegNet.git\n",
        "%cd /content/DT_SegNet\n",
        "# !git checkout bugfix-01\n",
        "!git checkout main\n",
        "# %pip uninstall -y protobuf\n",
        "# %pip install paddlepaddle-gpu==2.5.0 -f https://www.paddlepaddle.org.cn/whl/linux/cudnnin/stable.html # https://github.com/PaddlePaddle/Paddle/pull/56366\n",
        "%pip install paddlepaddle-gpu==2.4.2.post117 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html\n",
        "%pip install -r 1_Detection_Model/requirements.txt\n",
        "%pip install -r 3_Segmentation_Model/requirements.txt\n",
        "%pip install --upgrade ipykernel"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "mO7IlajDTSbG",
        "outputId": "13c600fe-0532-4d75-d0dc-d48deae00538",
        "cellView": "form"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n",
            "Cloning into 'DT_SegNet'...\n",
            "remote: Enumerating objects: 869, done.\u001b[K\n",
            "remote: Counting objects: 100% (231/231), done.\u001b[K\n",
            "remote: Compressing objects: 100% (195/195), done.\u001b[K\n",
            "remote: Total 869 (delta 63), reused 164 (delta 36), pack-reused 638\u001b[K\n",
            "Receiving objects: 100% (869/869), 17.22 MiB | 32.13 MiB/s, done.\n",
            "Resolving deltas: 100% (165/165), done.\n",
            "/content/DT_SegNet\n",
            "Branch 'bugfix-01' set up to track remote branch 'bugfix-01' from 'origin'.\n",
            "Switched to a new branch 'bugfix-01'\n",
            "Looking in links: https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html\n",
            "Collecting paddlepaddle-gpu==2.4.2.post117\n",
            "  Downloading https://paddle-wheel.bj.bcebos.com/2.4.2/linux/linux-gpu-cuda11.7-cudnn8.4.1-mkl-gcc8.2-avx/paddlepaddle_gpu-2.4.2.post117-cp310-cp310-linux_x86_64.whl (557.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m557.3/557.3 MB\u001b[0m \u001b[31m2.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: requests>=2.20.0 in /usr/local/lib/python3.10/dist-packages (from paddlepaddle-gpu==2.4.2.post117) (2.31.0)\n",
            "Requirement already satisfied: numpy>=1.13 in /usr/local/lib/python3.10/dist-packages (from paddlepaddle-gpu==2.4.2.post117) (1.25.2)\n",
            "Collecting protobuf<=3.20.0,>=3.1.0 (from paddlepaddle-gpu==2.4.2.post117)\n",
            "  Downloading protobuf-3.20.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m5.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from paddlepaddle-gpu==2.4.2.post117) (9.4.0)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from paddlepaddle-gpu==2.4.2.post117) (1.16.0)\n",
            "Requirement already satisfied: decorator in /usr/local/lib/python3.10/dist-packages (from paddlepaddle-gpu==2.4.2.post117) (4.4.2)\n",
            "Collecting astor (from paddlepaddle-gpu==2.4.2.post117)\n",
            "  Downloading astor-0.8.1-py2.py3-none-any.whl (27 kB)\n",
            "Collecting paddle-bfloat==0.1.7 (from paddlepaddle-gpu==2.4.2.post117)\n",
            "  Downloading paddle_bfloat-0.1.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (383 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m383.2/383.2 kB\u001b[0m \u001b[31m29.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: opt-einsum==3.3.0 in /usr/local/lib/python3.10/dist-packages (from paddlepaddle-gpu==2.4.2.post117) (3.3.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20.0->paddlepaddle-gpu==2.4.2.post117) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20.0->paddlepaddle-gpu==2.4.2.post117) (3.6)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20.0->paddlepaddle-gpu==2.4.2.post117) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20.0->paddlepaddle-gpu==2.4.2.post117) (2024.2.2)\n",
            "Installing collected packages: paddle-bfloat, protobuf, astor, paddlepaddle-gpu\n",
            "  Attempting uninstall: protobuf\n",
            "    Found existing installation: protobuf 3.20.3\n",
            "    Uninstalling protobuf-3.20.3:\n",
            "      Successfully uninstalled protobuf-3.20.3\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-ai-generativelanguage 0.4.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-api-core 2.11.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0.dev0,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-cloud-aiplatform 1.43.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-cloud-bigquery 3.12.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-cloud-bigquery-connection 1.12.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-cloud-bigquery-storage 2.24.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-cloud-datastore 2.15.2 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-cloud-firestore 2.11.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-cloud-functions 1.13.3 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-cloud-iam 2.14.2 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-cloud-language 2.13.2 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-cloud-resource-manager 1.12.2 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "google-cloud-translate 3.11.3 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "googleapis-common-protos 1.62.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0.dev0,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "grpc-google-iam-v1 0.13.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
            "tensorflow 2.15.0 requires protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3, but you have protobuf 3.20.0 which is incompatible.\n",
            "tensorflow-metadata 1.14.0 requires protobuf<4.21,>=3.20.3, but you have protobuf 3.20.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed astor-0.8.1 paddle-bfloat-0.1.7 paddlepaddle-gpu-2.4.2.post117 protobuf-3.20.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "google"
                ]
              },
              "id": "afb451dbc9e541dd96c3498b36793dff"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: matplotlib>=3.2.2 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 5)) (3.7.1)\n",
            "Requirement already satisfied: numpy>=1.18.5 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 6)) (1.25.2)\n",
            "Requirement already satisfied: opencv-python>=4.1.1 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 7)) (4.8.0.76)\n",
            "Requirement already satisfied: Pillow>=7.1.2 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 8)) (9.4.0)\n",
            "Requirement already satisfied: PyYAML>=5.3.1 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 9)) (6.0.1)\n",
            "Requirement already satisfied: requests>=2.23.0 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 10)) (2.31.0)\n",
            "Requirement already satisfied: scipy>=1.4.1 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 11)) (1.11.4)\n",
            "Requirement already satisfied: torch>=1.7.0 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 12)) (2.1.0+cu121)\n",
            "Requirement already satisfied: torchvision>=0.8.1 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 13)) (0.16.0+cu121)\n",
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            "Requirement already satisfied: pandas>=1.1.4 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 23)) (1.5.3)\n",
            "Requirement already satisfied: seaborn>=0.11.0 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 24)) (0.13.1)\n",
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            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 39)) (5.9.5)\n",
            "Collecting thop>=0.1.1 (from -r 1_Detection_Model/requirements.txt (line 40))\n",
            "  Downloading thop-0.1.1.post2209072238-py3-none-any.whl (15 kB)\n",
            "Requirement already satisfied: pycocotools>=2.0 in /usr/local/lib/python3.10/dist-packages (from -r 1_Detection_Model/requirements.txt (line 42)) (2.0.7)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.2.2->-r 1_Detection_Model/requirements.txt (line 5)) (1.2.0)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.2.2->-r 1_Detection_Model/requirements.txt (line 5)) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.2.2->-r 1_Detection_Model/requirements.txt (line 5)) (4.49.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.2.2->-r 1_Detection_Model/requirements.txt (line 5)) (1.4.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.2.2->-r 1_Detection_Model/requirements.txt (line 5)) (23.2)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.2.2->-r 1_Detection_Model/requirements.txt (line 5)) (3.1.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.2.2->-r 1_Detection_Model/requirements.txt (line 5)) (2.8.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->-r 1_Detection_Model/requirements.txt (line 10)) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->-r 1_Detection_Model/requirements.txt (line 10)) (3.6)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->-r 1_Detection_Model/requirements.txt (line 10)) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.23.0->-r 1_Detection_Model/requirements.txt (line 10)) (2024.2.2)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.7.0->-r 1_Detection_Model/requirements.txt (line 12)) (3.13.1)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch>=1.7.0->-r 1_Detection_Model/requirements.txt (line 12)) (4.10.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.7.0->-r 1_Detection_Model/requirements.txt (line 12)) (1.12)\n",
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            "Requirement already satisfied: triton==2.1.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.7.0->-r 1_Detection_Model/requirements.txt (line 12)) (2.1.0)\n",
            "Requirement already satisfied: absl-py>=0.4 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.4.1->-r 1_Detection_Model/requirements.txt (line 18)) (1.4.0)\n",
            "Requirement already satisfied: grpcio>=1.48.2 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.4.1->-r 1_Detection_Model/requirements.txt (line 18)) (1.62.0)\n",
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            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.4.1->-r 1_Detection_Model/requirements.txt (line 18)) (3.5.2)\n",
            "Requirement already satisfied: protobuf!=4.24.0,>=3.19.6 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.4.1->-r 1_Detection_Model/requirements.txt (line 18)) (3.20.0)\n",
            "Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.4.1->-r 1_Detection_Model/requirements.txt (line 18)) (67.7.2)\n",
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            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.4->-r 1_Detection_Model/requirements.txt (line 23)) (2023.4)\n",
            "Collecting jedi>=0.16 (from ipython->-r 1_Detection_Model/requirements.txt (line 38))\n",
            "  Downloading jedi-0.19.1-py2.py3-none-any.whl (1.6 MB)\n",
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            "\u001b[?25hRequirement already satisfied: decorator in /usr/local/lib/python3.10/dist-packages (from ipython->-r 1_Detection_Model/requirements.txt (line 38)) (4.4.2)\n",
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            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<2,>=0.5->tensorboard>=2.4.1->-r 1_Detection_Model/requirements.txt (line 18)) (3.2.2)\n",
            "Installing collected packages: jedi, thop\n",
            "Successfully installed jedi-0.19.1 thop-0.1.1.post2209072238\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from -r 3_Segmentation_Model/requirements.txt (line 1)) (6.0.1)\n",
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            "Installing collected packages: rarfile, pycryptodome, bce-python-sdk, Flask-Babel, visualdl\n",
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            "Installing collected packages: pyzmq, comm, ipykernel\n",
            "  Attempting uninstall: pyzmq\n",
            "    Found existing installation: pyzmq 23.2.1\n",
            "    Uninstalling pyzmq-23.2.1:\n",
            "      Successfully uninstalled pyzmq-23.2.1\n",
            "  Attempting uninstall: ipykernel\n",
            "    Found existing installation: ipykernel 5.5.6\n",
            "    Uninstalling ipykernel-5.5.6:\n",
            "      Successfully uninstalled ipykernel-5.5.6\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-colab 1.0.0 requires ipykernel==5.5.6, but you have ipykernel 6.29.3 which is incompatible.\n",
            "notebook 6.5.5 requires pyzmq<25,>=17, but you have pyzmq 25.1.2 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed comm-0.2.1 ipykernel-6.29.3 pyzmq-25.1.2\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "zmq"
                ]
              },
              "id": "c5cdad5fa5c84403a0999bedbb705abb"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Sanity check\n",
        "!nvidia-smi\n",
        "%cd /content/DT_SegNet/1_Detection_Model\n",
        "import os\n",
        "import shutil\n",
        "from utils.general import check_requirements, emojis, is_colab\n",
        "from utils.torch_utils import select_device  # imports\n",
        "import psutil\n",
        "check_requirements(('psutil', 'IPython'))\n",
        "check_requirements('/content/DT_SegNet/1_Detection_Model/requirements.txt')\n",
        "check_requirements('/content/DT_SegNet/3_Segmentation_Model/requirements.txt')\n",
        "if not is_colab():\n",
        "    print('WARN: not running in Google Colab.')\n",
        "shutil.rmtree('/content/sample_data', ignore_errors=True)  # remove colab /sample_data directory\n",
        "gb = 1 << 30  # bytes to GiB (1024 ** 3)\n",
        "ram = psutil.virtual_memory().total\n",
        "total, used, free = shutil.disk_usage(\"/\")\n",
        "s = f'({os.cpu_count()} CPUs, {ram / gb:.1f} GB RAM, {(total - free) / gb:.1f}/{total / gb:.1f} GB disk)'\n",
        "select_device(newline=False)\n",
        "print(emojis(f'Passed ✅ {s}'))\n",
        "import paddle\n",
        "paddle.utils.run_check()\n",
        "print(paddle.__version__)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-NIUcvRMTn2N",
        "outputId": "483c35d5-5684-4569-8154-ab3368441ae6",
        "cellView": "form"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Wed Mar  6 14:12:38 2024       \n",
            "+---------------------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 535.104.05             Driver Version: 535.104.05   CUDA Version: 12.2     |\n",
            "|-----------------------------------------+----------------------+----------------------+\n",
            "| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                                         |                      |               MIG M. |\n",
            "|=========================================+======================+======================|\n",
            "|   0  Tesla T4                       Off | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   35C    P8               9W /  70W |      0MiB / 15360MiB |      0%      Default |\n",
            "|                                         |                      |                  N/A |\n",
            "+-----------------------------------------+----------------------+----------------------+\n",
            "                                                                                         \n",
            "+---------------------------------------------------------------------------------------+\n",
            "| Processes:                                                                            |\n",
            "|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |\n",
            "|        ID   ID                                                             Usage      |\n",
            "|=======================================================================================|\n",
            "|  No running processes found                                                           |\n",
            "+---------------------------------------------------------------------------------------+\n",
            "/content/DT_SegNet/1_Detection_Model\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "YOLOv5 🚀 2024-3-6 Python-3.10.12 torch-2.1.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Passed ✅ (2 CPUs, 12.7 GB RAM, 29.2/78.2 GB disk)\n",
            "Running verify PaddlePaddle program ... \n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "W0306 14:12:51.750880  1324 gpu_resources.cc:61] Please NOTE: device: 0, GPU Compute Capability: 7.5, Driver API Version: 12.2, Runtime API Version: 11.7\n",
            "W0306 14:12:51.771757  1324 gpu_resources.cc:91] device: 0, cuDNN Version: 8.9.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "PaddlePaddle works well on 1 GPU.\n",
            "PaddlePaddle works well on 1 GPUs.\n",
            "PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.\n",
            "2.4.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Import packages\n",
        "\n",
        "from pathlib import Path\n",
        "from PIL import Image\n",
        "from tqdm.notebook import tqdm\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from matplotlib import pyplot as plt\n",
        "from google.colab import files\n",
        "import ipywidgets as widgets\n",
        "from IPython import display"
      ],
      "metadata": {
        "id": "Ud9uqddkcXIH",
        "cellView": "form"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Select & download models\n",
        "\n",
        "detection_model = \"https://github.com/xiazeyu/DT_SegNet/releases/latest/download/detection.pt\" #@param [\"https://github.com/xiazeyu/DT_SegNet/releases/latest/download/detection.pt\"] {allow-input: true}\n",
        "segmentation_model = \"https://github.com/xiazeyu/DT_SegNet/releases/latest/download/segmentation.pdparams\" #@param [\"https://github.com/xiazeyu/DT_SegNet/releases/latest/download/segmentation.pdparams\"] {allow-input: true}\n",
        "\n",
        "Path('/content/DT_SegNet/Models').mkdir(exist_ok=True, parents=True)\n",
        "\n",
        "detection_model_path = \"/content/DT_SegNet/Models/detection.pt\"\n",
        "segmentation_model_path = \"/content/DT_SegNet/Models/segmentation.pdparams\"\n",
        "\n",
        "\n",
        "!wget -O {detection_model_path} {detection_model}\n",
        "!wget -O {segmentation_model_path} {segmentation_model}\n",
        "\n",
        "print('Current model:')\n",
        "!ls /content/DT_SegNet/Models --human-readable --kibibytes -Sl"
      ],
      "metadata": {
        "id": "GrwoxiHuWk8t",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "cellView": "form",
        "outputId": "604cf3d2-c3f3-4f1d-e218-6fbb4f9b3a16"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2024-03-06 14:13:26--  https://github.com/xiazeyu/DT_SegNet/releases/latest/download/detection.pt\n",
            "Resolving github.com (github.com)... 140.82.113.4\n",
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            "Location: https://github.com/xiazeyu/DT_SegNet/releases/download/v1.1.0/detection.pt [following]\n",
            "--2024-03-06 14:13:26--  https://github.com/xiazeyu/DT_SegNet/releases/download/v1.1.0/detection.pt\n",
            "Reusing existing connection to github.com:443.\n",
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            "Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/583010192/ecbcd211-f9be-4421-a8d0-d9e3b2016796?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAVCODYLSA53PQK4ZA%2F20240306%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20240306T141326Z&X-Amz-Expires=300&X-Amz-Signature=5761f2fb1afcf6d36a045f3c1f27568ee83170518f3103d2c3f568facde2c3dd&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=583010192&response-content-disposition=attachment%3B%20filename%3Ddetection.pt&response-content-type=application%2Foctet-stream [following]\n",
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            "Saving to: ‘/content/DT_SegNet/Models/detection.pt’\n",
            "\n",
            "/content/DT_SegNet/ 100%[===================>] 146.58M   159MB/s    in 0.9s    \n",
            "\n",
            "2024-03-06 14:13:27 (159 MB/s) - ‘/content/DT_SegNet/Models/detection.pt’ saved [153696317/153696317]\n",
            "\n",
            "--2024-03-06 14:13:28--  https://github.com/xiazeyu/DT_SegNet/releases/latest/download/segmentation.pdparams\n",
            "Resolving github.com (github.com)... 140.82.112.4\n",
            "Connecting to github.com (github.com)|140.82.112.4|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://github.com/xiazeyu/DT_SegNet/releases/download/v1.1.0/segmentation.pdparams [following]\n",
            "--2024-03-06 14:13:28--  https://github.com/xiazeyu/DT_SegNet/releases/download/v1.1.0/segmentation.pdparams\n",
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            "Saving to: ‘/content/DT_SegNet/Models/segmentation.pdparams’\n",
            "\n",
            "/content/DT_SegNet/ 100%[===================>]  52.20M   198MB/s    in 0.3s    \n",
            "\n",
            "2024-03-06 14:13:29 (198 MB/s) - ‘/content/DT_SegNet/Models/segmentation.pdparams’ saved [54730932/54730932]\n",
            "\n",
            "Current model:\n",
            "total 199M\n",
            "-rw-r--r-- 1 root root 147M May 19  2023 detection.pt\n",
            "-rw-r--r-- 1 root root  53M May 19  2023 segmentation.pdparams\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title a) Upload local images for prediction\n",
        "\n",
        "Path('/content/DT_SegNet/Uploaded').mkdir(exist_ok=True, parents=True)\n",
        "%cd /content/DT_SegNet/Uploaded\n",
        "support_exts = ['.jpg', '.png', '.tif', '.bmp']\n",
        "accepted_file_names = [x.stem for x in Path('/content/DT_SegNet/Uploaded').glob('**/*')]\n",
        "\n",
        "print(f'Current supported image types: {\", \".join(support_exts)}')\n",
        "uploaded = files.upload()\n",
        "\n",
        "\n",
        "for fn in uploaded.keys():\n",
        "    if Path(fn).suffix not in support_exts:\n",
        "        print(f'{fn} is discarded due to unsupported file extension {Path(fn).suffix}.')\n",
        "        Path(fn).unlink(missing_ok=True)\n",
        "    else:\n",
        "        if Path(fn).stem in accepted_file_names:\n",
        "            print(f'You\\'ve uploaded two files with the same stem: {Path(fn).stem}. Please rename {fn} and try uploading again to avoid conflicts.')\n",
        "            Path(fn).unlink(missing_ok=True)\n",
        "        else:\n",
        "            accepted_file_names.append(Path(fn).stem)\n",
        "            print(f'User uploaded file \"{fn}\" with length {len(uploaded[fn])} bytes')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 183
        },
        "id": "pbfdZm1kYjmT",
        "outputId": "d2f9b737-6a01-4bab-d2b8-40e09cbfc5f9",
        "cellView": "form"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/DT_SegNet/Uploaded\n",
            "Current supported image types: .jpg, .png, .tif, .bmp\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-ee1463e0-8285-49b5-b9d8-f50d0fd5e88e\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-ee1463e0-8285-49b5-b9d8-f50d0fd5e88e\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving 1.png to 1.png\n",
            "Saving 2.jpg to 2.jpg\n",
            "User uploaded file \"1.png\" with length 331450 bytes\n",
            "User uploaded file \"2.jpg\" with length 3865104 bytes\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title b) Or connect to Google Drive to upload images for prediction\n",
        "\n",
        "Path('/content/DT_SegNet/Uploaded').mkdir(exist_ok=True, parents=True)\n",
        "%cd /content/DT_SegNet/Uploaded\n",
        "support_exts = ['.jpg', '.png', '.tif', '.bmp']\n",
        "accepted_file_names = [x.stem for x in Path('/content/DT_SegNet/Uploaded').glob('**/*')]\n",
        "\n",
        "print(f'Current supported image types: {\", \".join(support_exts)}')\n",
        "\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "\n",
        "drive_input_root = \"/content/drive/MyDrive/DT_SegNet_Input\" #@param {allow-input: true}\n",
        "\n",
        "\n",
        "for fn in [file for file in Path(drive_input_root).glob('**/*') if file.suffix in support_exts]:\n",
        "    if Path(fn).stem in accepted_file_names:\n",
        "        print(f'You\\'ve uploaded two files with the same stem: {Path(fn).stem}. Please rename {fn} and try uploading again to avoid conflicts.')\n",
        "    else:\n",
        "        accepted_file_names.append(Path(fn).stem)\n",
        "        shutil.copy(fn, Path('/content/DT_SegNet/Uploaded') / fn.name)\n",
        "        print(f'User uploaded file \"{fn}\".')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "cellView": "form",
        "id": "6m0J_HhURcWt",
        "outputId": "7a03da3f-cc72-468c-973f-55ada5dadba0"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/DT_SegNet/Uploaded\n",
            "Current supported image types: .jpg, .png, .tif, .bmp\n",
            "Mounted at /content/drive\n",
            "User uploaded file \"/content/drive/MyDrive/DT_SegNet_Input/3.tif\".\n",
            "User uploaded file \"/content/drive/MyDrive/DT_SegNet_Input/4.bmp\".\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Inference"
      ],
      "metadata": {
        "id": "wa95KgDhy6Md"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Specify hyper-parameters\n",
        "#@markdown Adjust these values if the results are not satisfactory. If still not ideal, consider finetune the model\n",
        "#@markdown ## Object Confidence Threshold\n",
        "#@markdown A lower threshold may result in more false detections, while a higher threshold may result in missed detections.\n",
        "conf_thres = 0.475 # @param {type:\"slider\", min:0, max:1, step:0.001}\n",
        "\n",
        "#@markdown ## IoU Threshold for NMS (Non-Maximum Suppression)\n",
        "#@markdown A higher IOU threshold means that one of the two boxes will only be considered for deletion if they overlap highly. A lower threshold may result in more boxes being removed, which may cause some objects to be missed.\n",
        "iou_thres = 0.45 # @param {type:\"slider\", min:0, max:1, step:0.001}\n",
        "\n"
      ],
      "metadata": {
        "cellView": "form",
        "id": "YJgOXUuAycX9"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Detection\n",
        "%cd /content/DT_SegNet/1_Detection_Model\n",
        "!python detect.py --project \"/content/DT_SegNet/Detection_Output\" --weights {detection_model_path} --img 1280 --source /content/DT_SegNet/Uploaded --line-thickness 2 --save-txt --save-conf --save-crop --conf-thres {conf_thres} --iou-thres {iou_thres}\n",
        "%cd .."
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R9MG-aFObQ7G",
        "outputId": "a2f34455-629f-4533-bfc9-7f93c7700000",
        "cellView": "form"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/DT_SegNet/1_Detection_Model\n",
            "\u001b[34m\u001b[1mdetect: \u001b[0mweights=['/content/DT_SegNet/Models/detection.pt'], source=/content/DT_SegNet/Uploaded, data=data/coco128.yaml, imgsz=[1280, 1280], conf_thres=0.475, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=True, save_conf=True, save_crop=True, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=/content/DT_SegNet/Detection_Output, name=exp, exist_ok=False, line_thickness=2, hide_labels=False, hide_conf=False, half=False, dnn=False\n",
            "YOLOv5 🚀 2024-3-6 Python-3.10.12 torch-2.1.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
            "\n",
            "Fusing layers... \n",
            "Model summary: 476 layers, 76118664 parameters, 0 gradients, 109.9 GFLOPs\n",
            "WARNING: NMS time limit 0.330s exceeded\n",
            "image 1/4 /content/DT_SegNet/Uploaded/1.png: 1088x1280 50 precipitates, Done. (0.092s)\n",
            "image 2/4 /content/DT_SegNet/Uploaded/2.jpg: 960x1280 330 precipitates, Done. (0.080s)\n",
            "image 3/4 /content/DT_SegNet/Uploaded/3.tif: 960x1280 331 precipitates, Done. (0.099s)\n",
            "image 4/4 /content/DT_SegNet/Uploaded/4.bmp: 960x1280 331 precipitates, Done. (0.131s)\n",
            "Speed: 1.3ms pre-process, 100.4ms inference, 176.9ms NMS per image at shape (1, 3, 1280, 1280)\n",
            "Results saved to \u001b[1m/content/DT_SegNet/Detection_Output/exp\u001b[0m\n",
            "4 labels saved to /content/DT_SegNet/Detection_Output/exp/labels\n",
            "/content/DT_SegNet\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Select your detection exp\n",
        "\n",
        "output = widgets.Output()\n",
        "\n",
        "det_exps = [x.stem for x in Path('/content/DT_SegNet/Detection_Output').iterdir() if x.is_dir()]\n",
        "w = widgets.Dropdown(\n",
        "    options=det_exps + ['---'],\n",
        "    value='---',\n",
        "    description='choose exp:',\n",
        "    disabled=False,\n",
        ")\n",
        "\n",
        "def on_change(change):\n",
        "    global detection_inference_exp_path\n",
        "    if change['type'] == 'change' and change['name'] == 'value':\n",
        "        if change['new'] == '---':\n",
        "            display.clear_output()\n",
        "            display.display(w, output)\n",
        "            return\n",
        "        display.clear_output()\n",
        "        display.display(w, output)\n",
        "        detection_inference_exp = change['new']\n",
        "        detection_inference_exp_path = f\"/content/DT_SegNet/Detection_Output/{detection_inference_exp}\"\n",
        "        print(f'Selected {detection_inference_exp_path}')\n",
        "        button = widgets.Button(\n",
        "            description='Download',\n",
        "            disabled=False,\n",
        "            button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
        "            tooltip='Download the prediction result of selected exp.',\n",
        "            icon='download' # (FontAwesome names without the `fa-` prefix)\n",
        "        )\n",
        "\n",
        "        def on_button_clicked(b):\n",
        "            %cd {detection_inference_exp_path}\n",
        "            !rm -f /content/DT_SegNet/detection_output.zip\n",
        "            !zip -qr '/content/DT_SegNet/detection_output.zip' .\n",
        "            files.download('/content/DT_SegNet/detection_output.zip')\n",
        "\n",
        "        button.on_click(on_button_clicked)\n",
        "        display.display(button, output)\n",
        "\n",
        "w.observe(on_change)\n",
        "display.display(w, output)\n"
      ],
      "metadata": {
        "id": "DnQhLJyOb8lK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 117,
          "referenced_widgets": [
            "7f3adc7c663f4867a92f9c64ea33c037",
            "f8484f4fe6cd48cfbcd6f254c22a16d0",
            "24f6487a623a4dea86616d8293760582",
            "1a98617340fc4b53a1d07fda534ed688",
            "91e3986c553b4afda68d9cd0c4febb04",
            "a17c531f83ad4bd983d405ee30f7d7ec",
            "31084feb284e4de3ac241d713adaa790",
            "8c9621297ec44228b04b71154bbddd01"
          ]
        },
        "cellView": "form",
        "outputId": "df8f967e-43d7-4804-ed2b-2f5fe6984c45"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Dropdown(description='choose exp:', options=('exp', '---'), value='exp')"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7f3adc7c663f4867a92f9c64ea33c037"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1a98617340fc4b53a1d07fda534ed688"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Selected /content/DT_SegNet/Detection_Output/exp\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Button(button_style='success', description='Download', icon='download', style=ButtonStyle(), tooltip='Download…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a17c531f83ad4bd983d405ee30f7d7ec"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1a98617340fc4b53a1d07fda534ed688"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/DT_SegNet/Detection_Output/exp\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "\n",
              "    async function download(id, filename, size) {\n",
              "      if (!google.colab.kernel.accessAllowed) {\n",
              "        return;\n",
              "      }\n",
              "      const div = document.createElement('div');\n",
              "      const label = document.createElement('label');\n",
              "      label.textContent = `Downloading \"${filename}\": `;\n",
              "      div.appendChild(label);\n",
              "      const progress = document.createElement('progress');\n",
              "      progress.max = size;\n",
              "      div.appendChild(progress);\n",
              "      document.body.appendChild(div);\n",
              "\n",
              "      const buffers = [];\n",
              "      let downloaded = 0;\n",
              "\n",
              "      const channel = await google.colab.kernel.comms.open(id);\n",
              "      // Send a message to notify the kernel that we're ready.\n",
              "      channel.send({})\n",
              "\n",
              "      for await (const message of channel.messages) {\n",
              "        // Send a message to notify the kernel that we're ready.\n",
              "        channel.send({})\n",
              "        if (message.buffers) {\n",
              "          for (const buffer of message.buffers) {\n",
              "            buffers.push(buffer);\n",
              "            downloaded += buffer.byteLength;\n",
              "            progress.value = downloaded;\n",
              "          }\n",
              "        }\n",
              "      }\n",
              "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
              "      const a = document.createElement('a');\n",
              "      a.href = window.URL.createObjectURL(blob);\n",
              "      a.download = filename;\n",
              "      div.appendChild(a);\n",
              "      a.click();\n",
              "      div.remove();\n",
              "    }\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "download(\"download_cc01b5dd-919d-4d05-8063-e21a8d2797fa\", \"detection_output.zip\", 27316483)"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Segmentation\n",
        "\n",
        "data_dir = Path('/content/DT_SegNet/Uploaded')\n",
        "label_dir = Path(detection_inference_exp_path) / 'labels'\n",
        "\n",
        "seg_output_dir = Path('/content/DT_SegNet/Segmentation_Input/')\n",
        "\n",
        "# read YOLO format txt label, and perform dilation\n",
        "def read_labels(label_path, img, dilation = 1.5):\n",
        "    data = pd.read_csv(str(label_path), sep=\" \", header=None,\n",
        "                    names=[\"class\", \"x_center\", \"y_center\", \"width\", \"height\", \"proability\"])\n",
        "    img_x, img_y = img.size\n",
        "    data['x0'] = ((data['x_center'] - dilation * data['width'] / 2) * img_x).astype(\"int\")\n",
        "    data['x1'] = ((data['x_center'] + dilation * data['width'] / 2) * img_x).astype(\"int\")\n",
        "    data['y0'] = ((data['y_center'] - dilation * data['height'] / 2) * img_y).astype(\"int\")\n",
        "    data['y1'] = ((data['y_center'] + dilation * data['height'] / 2) * img_y).astype(\"int\")\n",
        "    return data\n",
        "\n",
        "shutil.rmtree(seg_output_dir, ignore_errors=True)\n",
        "shutil.rmtree('/content/DT_SegNet/Segmentation_Output/', ignore_errors=True)\n",
        "seg_output_dir.mkdir(parents=True, exist_ok=True)\n",
        "for img_path in [file for file in data_dir.glob('**/*') if file.suffix in support_exts]:\n",
        "    print(f'Processing {str(img_path)}')\n",
        "\n",
        "    # process cropped image\n",
        "    img = Image.open(img_path)\n",
        "    img = img.convert(\"L\")\n",
        "    # print(img.format, img.size, img.mode)\n",
        "    labels = read_labels((label_dir / img_path.name).with_suffix('.txt'), img)\n",
        "    with tqdm(total=len(labels)) as pbar:\n",
        "        for index, r in labels.iterrows():\n",
        "            box = (r.x0, r.y0, r.x1, r.y1)\n",
        "            region = img.crop(box)\n",
        "            # region.show()\n",
        "            croped_savepath = seg_output_dir / f'{img_path.stem}_{index}.png'\n",
        "            # print(croped_savepath, box)\n",
        "            region.save(croped_savepath)\n",
        "            pbar.update(1)\n",
        "\n",
        "%cd /content/DT_SegNet/3_Segmentation_Model\n",
        "!python predict.py --config configs/dtsegnet/segformer_b1.yml --model_path {segmentation_model_path} --image_path /content/DT_SegNet/Segmentation_Input/ --save_dir /content/DT_SegNet/Segmentation_Output/\n",
        "%cd /content/DT_SegNet"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "0163aba0038b48649f144b25951d0a4c",
            "80ff9b6de1f843aeb38e9ae26a587297",
            "2763685fdccb496dac5e598861c9891a",
            "0ec65554c8ad4543b47f1ca99291b23c",
            "dd4f5fc4f5ac4c8eaaf36bdfd8f5b4d5",
            "c419bf5d6e94449ca57519a41f9ad837",
            "5708a0f94c9646f4b5a9f3d12c2c4a5a",
            "48a25e154b06462ba4c3144745109038",
            "7389f87bf72d4d6988c872c3038aa17f",
            "8104ddecf3804734ac930a85a08a824f",
            "2f7d3b32af6e42858c491144bdfbd407",
            "925aaca7345f469b8d85b7632af75283",
            "8a09dba6a1f244289194dbc8c4ac9515",
            "fc1ff1898fa44ceead5675ad74aa98f9",
            "7f601c63c7bb4b69936b1f37aaf4a3d5",
            "e69fa23c271a46649bf555c078106c40",
            "0c4d1c1342a64f9684dd47fe76d3fd0a",
            "52c904afc762446b9a5728b4c023fefd",
            "67fed026a1fd427abaf0220de01446c1",
            "e6ab335118a648ef875757fb6763331c",
            "33e37f94ae09486e925999690925856d",
            "4dfa0c396d474662ab18370da70c8210",
            "dd88fbcd81354066adf94ee948952af1",
            "3edb310dfb684f41b147ad074503f09a",
            "0b4cea92df5848238216e07fecff4567",
            "aa6945daaa7a4e73a1e0b4ffdc6e7b95",
            "721dbf3dbd2547c6af08746bc31e8ab3",
            "f6eef9d5907a47cdba241c1ef742dc79",
            "2ed88e0f0cce455da8937da2f747df15",
            "757d6a683a5c4e0ca63277bbd8e4142f",
            "c2f3dd701108492fac11d2b88310b8b6",
            "11c7ca4eba4040a8aa00cbaca04b8f8d",
            "5f8271c583f444b9b572c821968fe731",
            "39e108fcf5e4441aa4b3fd06c8fb89f5",
            "849d3296a312496cad34cb12ee83cb82",
            "2ee46d077be546f5886b00c76ac9a0c6",
            "157af447ca374afca3cf876c73f30316",
            "92e82024d865430085a0d7efe29c7ef7",
            "82e0217bdc954a1b81dd9add7be86223",
            "7f713bc000d842f1aaa6b93292d37a6b",
            "c27a40e00363401bb789aafc8c0ad7c9",
            "e35eb119c1684da3896d8fc5369e2c8c",
            "37a3d84a91f34c288595577d3c59bc68",
            "67c1dc186d7e4cd591bff700c42c294b"
          ]
        },
        "id": "TYAdtE8icJS5",
        "outputId": "71f09304-b69b-4149-aa81-6701160f9492",
        "cellView": "form"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Processing /content/DT_SegNet/Uploaded/2.jpg\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/ipywidgets/widgets/widget.py:503: DeprecationWarning: The `ipykernel.comm.Comm` class has been deprecated. Please use the `comm` module instead.For creating comms, use the function `from comm import create_comm`.\n",
            "  self.comm = Comm(**args)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/330 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "0163aba0038b48649f144b25951d0a4c"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.\n",
            "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)\n",
            "  return np.find_common_type(types, [])\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Processing /content/DT_SegNet/Uploaded/4.bmp\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/ipywidgets/widgets/widget.py:503: DeprecationWarning: The `ipykernel.comm.Comm` class has been deprecated. Please use the `comm` module instead.For creating comms, use the function `from comm import create_comm`.\n",
            "  self.comm = Comm(**args)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/331 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "925aaca7345f469b8d85b7632af75283"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.\n",
            "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)\n",
            "  return np.find_common_type(types, [])\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Processing /content/DT_SegNet/Uploaded/1.png\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/ipywidgets/widgets/widget.py:503: DeprecationWarning: The `ipykernel.comm.Comm` class has been deprecated. Please use the `comm` module instead.For creating comms, use the function `from comm import create_comm`.\n",
            "  self.comm = Comm(**args)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/50 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "dd88fbcd81354066adf94ee948952af1"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Processing /content/DT_SegNet/Uploaded/3.tif\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.\n",
            "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)\n",
            "  return np.find_common_type(types, [])\n",
            "/usr/local/lib/python3.10/dist-packages/ipywidgets/widgets/widget.py:503: DeprecationWarning: The `ipykernel.comm.Comm` class has been deprecated. Please use the `comm` module instead.For creating comms, use the function `from comm import create_comm`.\n",
            "  self.comm = Comm(**args)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/331 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "39e108fcf5e4441aa4b3fd06c8fb89f5"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.\n",
            "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)\n",
            "  return np.find_common_type(types, [])\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/DT_SegNet/3_Segmentation_Model\n",
            "/usr/local/lib/python3.10/dist-packages/pkg_resources/__init__.py:121: DeprecationWarning: pkg_resources is deprecated as an API\n",
            "  warnings.warn(\"pkg_resources is deprecated as an API\", DeprecationWarning)\n",
            "/usr/local/lib/python3.10/dist-packages/pkg_resources/__init__.py:2870: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google')`.\n",
            "Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages\n",
            "  declare_namespace(pkg)\n",
            "/usr/local/lib/python3.10/dist-packages/pkg_resources/__init__.py:2870: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google.cloud')`.\n",
            "Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages\n",
            "  declare_namespace(pkg)\n",
            "/usr/local/lib/python3.10/dist-packages/pkg_resources/__init__.py:2349: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google')`.\n",
            "Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages\n",
            "  declare_namespace(parent)\n",
            "/usr/local/lib/python3.10/dist-packages/pkg_resources/__init__.py:2870: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('mpl_toolkits')`.\n",
            "Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages\n",
            "  declare_namespace(pkg)\n",
            "/usr/local/lib/python3.10/dist-packages/pkg_resources/__init__.py:2870: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('sphinxcontrib')`.\n",
            "Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages\n",
            "  declare_namespace(pkg)\n",
            "/content/DT_SegNet/3_Segmentation_Model/paddleseg/models/losses/rmi_loss.py:73: DeprecationWarning: invalid escape sequence '\\i'\n",
            "  \"\"\"\n",
            "2024-03-06 14:16:54 [INFO]\t\n",
            "---------------Config Information---------------\n",
            "batch_size: 1\n",
            "iters: 80000\n",
            "loss:\n",
            "  coef:\n",
            "  - 1\n",
            "  types:\n",
            "  - type: CrossEntropyLoss\n",
            "lr_scheduler:\n",
            "  end_lr: 0\n",
            "  learning_rate: 6.0e-05\n",
            "  power: 1\n",
            "  type: PolynomialDecay\n",
            "model:\n",
            "  backbone:\n",
            "    in_channels: 3\n",
            "    pretrained: https://bj.bcebos.com/paddleseg/dygraph/backbone/mix_vision_transformer_b1.tar.gz\n",
            "    type: MixVisionTransformer_B1\n",
            "  embedding_dim: 256\n",
            "  num_classes: 2\n",
            "  type: SegFormer\n",
            "optimizer:\n",
            "  beta1: 0.9\n",
            "  beta2: 0.999\n",
            "  type: AdamW\n",
            "  weight_decay: 0.01\n",
            "test_config:\n",
            "  crop_size:\n",
            "  - 1024\n",
            "  - 1024\n",
            "  is_slide: true\n",
            "  stride:\n",
            "  - 768\n",
            "  - 768\n",
            "test_dataset:\n",
            "  dataset_root: /root/autodl-tmp/DT_SegNet/Dataset/Segmentation_Dataset\n",
            "  mode: val\n",
            "  num_classes: 2\n",
            "  transforms:\n",
            "  - target_size:\n",
            "    - 512\n",
            "    - 512\n",
            "    type: Resize\n",
            "  - type: Normalize\n",
            "  type: Dataset\n",
            "  val_path: /root/autodl-tmp/DT_SegNet/Dataset/Segmentation_Dataset/test.txt\n",
            "train_dataset:\n",
            "  dataset_root: /root/autodl-tmp/DT_SegNet/Dataset/Segmentation_Dataset\n",
            "  img_channels: 3\n",
            "  mode: train\n",
            "  num_classes: 2\n",
            "  train_path: /root/autodl-tmp/DT_SegNet/Dataset/Segmentation_Dataset/train.txt\n",
            "  transforms:\n",
            "  - target_size:\n",
            "    - 512\n",
            "    - 512\n",
            "    type: Resize\n",
            "  - type: RandomHorizontalFlip\n",
            "  - type: RandomVerticalFlip\n",
            "  - type: Normalize\n",
            "  type: Dataset\n",
            "val_dataset:\n",
            "  dataset_root: /root/autodl-tmp/DT_SegNet/Dataset/Segmentation_Dataset\n",
            "  img_channels: 3\n",
            "  mode: val\n",
            "  num_classes: 2\n",
            "  transforms:\n",
            "  - target_size:\n",
            "    - 512\n",
            "    - 512\n",
            "    type: Resize\n",
            "  - type: Normalize\n",
            "  type: Dataset\n",
            "  val_path: /root/autodl-tmp/DT_SegNet/Dataset/Segmentation_Dataset/val.txt\n",
            "------------------------------------------------\n",
            "W0306 14:16:54.359659  2711 gpu_resources.cc:61] Please NOTE: device: 0, GPU Compute Capability: 7.5, Driver API Version: 12.2, Runtime API Version: 11.7\n",
            "W0306 14:16:54.359697  2711 gpu_resources.cc:91] device: 0, cuDNN Version: 8.9.\n",
            "2024-03-06 14:16:55 [INFO]\tLoading pretrained model from https://bj.bcebos.com/paddleseg/dygraph/backbone/mix_vision_transformer_b1.tar.gz\n",
            "Connecting to https://bj.bcebos.com/paddleseg/dygraph/backbone/mix_vision_transformer_b1.tar.gz\n",
            "Downloading mix_vision_transformer_b1.tar.gz\n",
            "[==================================================] 100.00%\n",
            "Uncompress mix_vision_transformer_b1.tar.gz\n",
            "[==================================================] 100.00%\n",
            "2024-03-06 14:17:14 [INFO]\tThere are 176/176 variables loaded into MixVisionTransformer.\n",
            "2024-03-06 14:17:14 [INFO]\tNumber of predict images = 1042\n",
            "2024-03-06 14:17:14 [INFO]\tLoading pretrained model from /content/DT_SegNet/Models/segmentation.pdparams\n",
            "2024-03-06 14:17:14 [INFO]\tThere are 191/191 variables loaded into SegFormer.\n",
            "2024-03-06 14:17:14 [INFO]\tStart to predict...\n",
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            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 277/1042 [======>.......................] - ETA: 26slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 279/1042 [=======>......................] - ETA: 26slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 285/1042 [=======>......................] - ETA: 25slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 287/1042 [=======>......................] - ETA: 25slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 289/1042 [=======>......................] - ETA: 25slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 291/1042 [=======>......................] - ETA: 25slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 293/1042 [=======>......................] - ETA: 25slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 297/1042 [=======>......................] - ETA: 25slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 303/1042 [=======>......................] - ETA: 24slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 307/1042 [=======>......................] - ETA: 24slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 309/1042 [=======>......................] - ETA: 24slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 311/1042 [=======>......................] - ETA: 24slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 313/1042 [========>.....................] - ETA: 24slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 315/1042 [========>.....................] - ETA: 24slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 317/1042 [========>.....................] - ETA: 24slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 323/1042 [========>.....................] - ETA: 23slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 329/1042 [========>.....................] - ETA: 23slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 333/1042 [========>.....................] - ETA: 23slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 335/1042 [========>.....................] - ETA: 23slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 341/1042 [========>.....................] - ETA: 23slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 345/1042 [========>.....................] - ETA: 22slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 347/1042 [========>.....................] - ETA: 22slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 353/1042 [=========>....................] - ETA: 22slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 359/1042 [=========>....................] - ETA: 22slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 363/1042 [=========>....................] - ETA: 22slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 365/1042 [=========>....................] - ETA: 22slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 367/1042 [=========>....................] - ETA: 22slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 371/1042 [=========>....................] - ETA: 21slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 373/1042 [=========>....................] - ETA: 21slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 375/1042 [=========>....................] - ETA: 21slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 381/1042 [=========>....................] - ETA: 21slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 383/1042 [==========>...................] - ETA: 21slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 387/1042 [==========>...................] - ETA: 21slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 389/1042 [==========>...................] - ETA: 21slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 391/1042 [==========>...................] - ETA: 21slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 397/1042 [==========>...................] - ETA: 20slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 399/1042 [==========>...................] - ETA: 20slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 411/1042 [==========>...................] - ETA: 20slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 413/1042 [==========>...................] - ETA: 20slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 415/1042 [==========>...................] - ETA: 20slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 419/1042 [===========>..................] - ETA: 19slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 421/1042 [===========>..................] - ETA: 19slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 425/1042 [===========>..................] - ETA: 19slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 427/1042 [===========>..................] - ETA: 19slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 431/1042 [===========>..................] - ETA: 19slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 433/1042 [===========>..................] - ETA: 19slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 435/1042 [===========>..................] - ETA: 19slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 437/1042 [===========>..................] - ETA: 19slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 439/1042 [===========>..................] - ETA: 19slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 451/1042 [===========>..................] - ETA: 18slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 453/1042 [============>.................] - ETA: 18slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 463/1042 [============>.................] - ETA: 18slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 467/1042 [============>.................] - ETA: 18slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 469/1042 [============>.................] - ETA: 18slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 471/1042 [============>.................] - ETA: 17slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 477/1042 [============>.................] - ETA: 17slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 483/1042 [============>.................] - ETA: 17slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 487/1042 [=============>................] - ETA: 17slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 493/1042 [=============>................] - ETA: 17slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 495/1042 [=============>................] - ETA: 17slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 497/1042 [=============>................] - ETA: 17slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 499/1042 [=============>................] - ETA: 17slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 501/1042 [=============>................] - ETA: 17slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 503/1042 [=============>................] - ETA: 16slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 511/1042 [=============>................] - ETA: 16slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 513/1042 [=============>................] - ETA: 16slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 519/1042 [=============>................] - ETA: 16slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 523/1042 [==============>...............] - ETA: 16slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 529/1042 [==============>...............] - ETA: 16slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 531/1042 [==============>...............] - ETA: 16slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 537/1042 [==============>...............] - ETA: 15slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 547/1042 [==============>...............] - ETA: 15slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 549/1042 [==============>...............] - ETA: 15slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 557/1042 [===============>..............] - ETA: 15slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 561/1042 [===============>..............] - ETA: 15slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 565/1042 [===============>..............] - ETA: 15slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 567/1042 [===============>..............] - ETA: 15slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 569/1042 [===============>..............] - ETA: 14slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 573/1042 [===============>..............] - ETA: 14slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 577/1042 [===============>..............] - ETA: 14slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 583/1042 [===============>..............] - ETA: 14slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 585/1042 [===============>..............] - ETA: 14slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 587/1042 [===============>..............] - ETA: 14slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 589/1042 [===============>..............] - ETA: 14slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 593/1042 [================>.............] - ETA: 14slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 597/1042 [================>.............] - ETA: 14slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 599/1042 [================>.............] - ETA: 14slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 601/1042 [================>.............] - ETA: 13slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 603/1042 [================>.............] - ETA: 13slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 605/1042 [================>.............] - ETA: 13slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 607/1042 [================>.............] - ETA: 13slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 611/1042 [================>.............] - ETA: 13slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 613/1042 [================>.............] - ETA: 13slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 621/1042 [================>.............] - ETA: 13slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 623/1042 [================>.............] - ETA: 13slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 627/1042 [=================>............] - ETA: 13slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 629/1042 [=================>............] - ETA: 13slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 631/1042 [=================>............] - ETA: 12slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 635/1042 [=================>............] - ETA: 12slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 643/1042 [=================>............] - ETA: 12slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 647/1042 [=================>............] - ETA: 12slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 649/1042 [=================>............] - ETA: 12slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 655/1042 [=================>............] - ETA: 12slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 657/1042 [=================>............] - ETA: 12slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 659/1042 [=================>............] - ETA: 12slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 661/1042 [==================>...........] - ETA: 11slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 665/1042 [==================>...........] - ETA: 11slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 667/1042 [==================>...........] - ETA: 11slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 673/1042 [==================>...........] - ETA: 11slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 677/1042 [==================>...........] - ETA: 11slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 681/1042 [==================>...........] - ETA: 11slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 685/1042 [==================>...........] - ETA: 11slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 687/1042 [==================>...........] - ETA: 11slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 689/1042 [==================>...........] - ETA: 11slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 693/1042 [==================>...........] - ETA: 10slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 695/1042 [===================>..........] - ETA: 10slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 697/1042 [===================>..........] - ETA: 10slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 701/1042 [===================>..........] - ETA: 10slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 703/1042 [===================>..........] - ETA: 10slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 709/1042 [===================>..........] - ETA: 10slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 717/1042 [===================>..........] - ETA: 10slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 721/1042 [===================>..........] - ETA: 9s libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 725/1042 [===================>..........] - ETA: 9slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 727/1042 [===================>..........] - ETA: 9slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 739/1042 [====================>.........] - ETA: 9slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 741/1042 [====================>.........] - ETA: 9slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 743/1042 [====================>.........] - ETA: 9slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 749/1042 [====================>.........] - ETA: 9slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 753/1042 [====================>.........] - ETA: 8slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 755/1042 [====================>.........] - ETA: 8slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 759/1042 [====================>.........] - ETA: 8slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 761/1042 [====================>.........] - ETA: 8slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 763/1042 [====================>.........] - ETA: 8slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 765/1042 [=====================>........] - ETA: 8slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 767/1042 [=====================>........] - ETA: 8slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 773/1042 [=====================>........] - ETA: 8slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 777/1042 [=====================>........] - ETA: 8slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 779/1042 [=====================>........] - ETA: 8slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 781/1042 [=====================>........] - ETA: 8slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 783/1042 [=====================>........] - ETA: 7slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 787/1042 [=====================>........] - ETA: 7slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 789/1042 [=====================>........] - ETA: 7slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 799/1042 [======================>.......] - ETA: 7slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 801/1042 [======================>.......] - ETA: 7slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 803/1042 [======================>.......] - ETA: 7slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 805/1042 [======================>.......] - ETA: 7slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 807/1042 [======================>.......] - ETA: 7slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 809/1042 [======================>.......] - ETA: 7slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 815/1042 [======================>.......] - ETA: 6slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 817/1042 [======================>.......] - ETA: 6slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 819/1042 [======================>.......] - ETA: 6slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 821/1042 [======================>.......] - ETA: 6slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 823/1042 [======================>.......] - ETA: 6slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 825/1042 [======================>.......] - ETA: 6slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 837/1042 [=======================>......] - ETA: 6slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 845/1042 [=======================>......] - ETA: 6slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 847/1042 [=======================>......] - ETA: 5slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 851/1042 [=======================>......] - ETA: 5slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 861/1042 [=======================>......] - ETA: 5slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 863/1042 [=======================>......] - ETA: 5slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 871/1042 [========================>.....] - ETA: 5slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 873/1042 [========================>.....] - ETA: 5slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 877/1042 [========================>.....] - ETA: 5slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 881/1042 [========================>.....] - ETA: 4slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 887/1042 [========================>.....] - ETA: 4slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 901/1042 [========================>.....] - ETA: 4slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 903/1042 [========================>.....] - ETA: 4slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 905/1042 [=========================>....] - ETA: 4slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 909/1042 [=========================>....] - ETA: 4slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            " 911/1042 [=========================>....] - ETA: 3slibpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
            "libpng warning: iCCP: profile 'ICC Profile': 'RGB ': RGB color space not permitted on grayscale PNG\n",
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            "1042/1042 [==============================] - 32s 31ms/step\n",
            "2024-03-06 14:17:46 [WARNING]\tThis `predict.py` will be removed in version 2.8, please use `tools/predict.py`.\n",
            "/content/DT_SegNet\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Generate output\n",
        "data_dir = Path('/content/DT_SegNet/Uploaded')\n",
        "seg_output_dir = Path('/content/DT_SegNet/Segmentation_Output/pseudo_color_prediction')\n",
        "label_dir = Path(detection_inference_exp_path) / 'labels'\n",
        "output_root = Path('/content/DT_SegNet/myOutput')\n",
        "output_root.mkdir(exist_ok=True, parents=True)\n",
        "\n",
        "for img_path in [file for file in data_dir.glob('**/*') if file.suffix in support_exts]:\n",
        "    print(f'Processing {str(img_path)}')\n",
        "    img = Image.open(img_path)\n",
        "    img = img.convert(\"L\")\n",
        "    labels = read_labels((label_dir / img_path.name).with_suffix('.txt'), img)\n",
        "    output = np.zeros_like(img)\n",
        "    with tqdm(total=len(labels)) as pbar:\n",
        "        for index, r in labels.iterrows():\n",
        "            croped_path = seg_output_dir / f'{img_path.stem}_{index}.png'\n",
        "            region = Image.open(croped_path)\n",
        "            np_region = np.array(region)\n",
        "            x0, x1, y0, y1 = int(r.x0), int(r.x1), int(r.y0), int(r.y1)\n",
        "            for x in range(x1-x0):\n",
        "                for y in range(y1-y0):\n",
        "                    y_out = y+y0\n",
        "                    x_out = x+x0\n",
        "                    y_out = max(0, y_out)\n",
        "                    x_out = max(0, x_out)\n",
        "                    y_out = min(output.shape[0]-1, y_out)\n",
        "                    x_out = min(output.shape[1]-1, x_out)\n",
        "                    output[y_out, x_out] += np_region[y, x] # add regions\n",
        "                    # output[y_out, x_out] = np_region[y, x] # replace regions\n",
        "            pbar.update(1)\n",
        "\n",
        "    output[output>=1]=1\n",
        "    data = np.array(output)\n",
        "    new_data = data.astype('uint8')\n",
        "    print(data.shape, new_data.shape, np.unique(new_data))\n",
        "    plt.imshow(new_data, interpolation='nearest', cmap='Greys')\n",
        "    # white background\n",
        "    plt.show()\n",
        "    np.save(output_root / f'{img_path.stem}.npy', new_data)\n",
        "    Image.fromarray(\n",
        "        new_data*255).save(output_root / f'{img_path.stem}.png')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
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        "id": "W4MBeDgodP3R",
        "outputId": "5ac055c5-9102-497e-cd4e-2d9881b206bf",
        "cellView": "form"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Processing /content/DT_SegNet/Uploaded/2.jpg\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/ipywidgets/widgets/widget.py:503: DeprecationWarning: The `ipykernel.comm.Comm` class has been deprecated. Please use the `comm` module instead.For creating comms, use the function `from comm import create_comm`.\n",
            "  self.comm = Comm(**args)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/330 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "257b361d18e64d95bb151b7bd13133be"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.\n",
            "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)\n",
            "  return np.find_common_type(types, [])\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(2188, 3072) (2188, 3072) [0 1]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Processing /content/DT_SegNet/Uploaded/4.bmp\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/ipywidgets/widgets/widget.py:503: DeprecationWarning: The `ipykernel.comm.Comm` class has been deprecated. Please use the `comm` module instead.For creating comms, use the function `from comm import create_comm`.\n",
            "  self.comm = Comm(**args)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/331 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "30b72c9aff62484fa78984ccc6ee47fd"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.\n",
            "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)\n",
            "  return np.find_common_type(types, [])\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(2188, 3072) (2188, 3072) [0 1]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Processing /content/DT_SegNet/Uploaded/1.png\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/ipywidgets/widgets/widget.py:503: DeprecationWarning: The `ipykernel.comm.Comm` class has been deprecated. Please use the `comm` module instead.For creating comms, use the function `from comm import create_comm`.\n",
            "  self.comm = Comm(**args)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/50 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "186ac2d946144456b355e782f6cbbf24"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.\n",
            "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)\n",
            "  return np.find_common_type(types, [])\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(514, 636) (514, 636) [0 1]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Processing /content/DT_SegNet/Uploaded/3.tif\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/ipywidgets/widgets/widget.py:503: DeprecationWarning: The `ipykernel.comm.Comm` class has been deprecated. Please use the `comm` module instead.For creating comms, use the function `from comm import create_comm`.\n",
            "  self.comm = Comm(**args)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/331 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "aa7d78730a8a4e51ad61579c5c7418a0"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.\n",
            "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)\n",
            "  return np.find_common_type(types, [])\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(2188, 3072) (2188, 3072) [0 1]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Download result to local filesystem\n",
        "\n",
        "%cd /content/DT_SegNet/myOutput\n",
        "!zip -qr '/content/DT_SegNet/Output.zip' .\n",
        "files.download('/content/DT_SegNet/Output.zip')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "Ws3yJ9ngZll1",
        "outputId": "16b84ba8-51a7-4b4d-f872-007347a1c8ae",
        "cellView": "form"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/DT_SegNet/myOutput\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "\n",
              "    async function download(id, filename, size) {\n",
              "      if (!google.colab.kernel.accessAllowed) {\n",
              "        return;\n",
              "      }\n",
              "      const div = document.createElement('div');\n",
              "      const label = document.createElement('label');\n",
              "      label.textContent = `Downloading \"${filename}\": `;\n",
              "      div.appendChild(label);\n",
              "      const progress = document.createElement('progress');\n",
              "      progress.max = size;\n",
              "      div.appendChild(progress);\n",
              "      document.body.appendChild(div);\n",
              "\n",
              "      const buffers = [];\n",
              "      let downloaded = 0;\n",
              "\n",
              "      const channel = await google.colab.kernel.comms.open(id);\n",
              "      // Send a message to notify the kernel that we're ready.\n",
              "      channel.send({})\n",
              "\n",
              "      for await (const message of channel.messages) {\n",
              "        // Send a message to notify the kernel that we're ready.\n",
              "        channel.send({})\n",
              "        if (message.buffers) {\n",
              "          for (const buffer of message.buffers) {\n",
              "            buffers.push(buffer);\n",
              "            downloaded += buffer.byteLength;\n",
              "            progress.value = downloaded;\n",
              "          }\n",
              "        }\n",
              "      }\n",
              "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
              "      const a = document.createElement('a');\n",
              "      a.href = window.URL.createObjectURL(blob);\n",
              "      a.download = filename;\n",
              "      div.appendChild(a);\n",
              "      a.click();\n",
              "      div.remove();\n",
              "    }\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "download(\"download_4776d596-eec8-46f3-b0d4-afa52a22432d\", \"Output.zip\", 542384)"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Analysis"
      ],
      "metadata": {
        "id": "pWA4_6-e4XF2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Total object count from detection stage\n",
        "\n",
        "output = widgets.Output()\n",
        "\n",
        "det_exps = [x.stem for x in Path('/content/DT_SegNet/Detection_Output').iterdir() if x.is_dir()]\n",
        "w = widgets.Dropdown(\n",
        "    options=det_exps + ['---'],\n",
        "    value='---',\n",
        "    description='choose exp:',\n",
        "    disabled=False,\n",
        ")\n",
        "\n",
        "def on_change(change):\n",
        "    global detection_inference_exp_path\n",
        "    if change['type'] == 'change' and change['name'] == 'value':\n",
        "        if change['new'] == '---':\n",
        "            display.clear_output()\n",
        "            display.display(w, output)\n",
        "            return\n",
        "        display.clear_output()\n",
        "        display.display(w, output)\n",
        "        detection_inference_exp = change['new']\n",
        "        detection_inference_exp_path = f\"/content/DT_SegNet/Detection_Output/{detection_inference_exp}\"\n",
        "        print(f'Selected {detection_inference_exp_path}')\n",
        "        button = widgets.Button(\n",
        "            description='Calculate',\n",
        "            disabled=False,\n",
        "            button_style='info', # 'success', 'info', 'warning', 'danger' or ''\n",
        "            tooltip='Calculate the total object count in selected exp.',\n",
        "            icon='calculator' # (FontAwesome names without the `fa-` prefix)\n",
        "        )\n",
        "\n",
        "        def on_button_clicked(b):\n",
        "            for txt_path in list((Path(detection_inference_exp_path) / 'labels').glob('*.txt')):\n",
        "                data = pd.read_csv(str(txt_path), sep=\" \", header=None,\n",
        "                      names=[\"class\", \"x_center\", \"y_center\", \"width\", \"height\", \"proability\"])\n",
        "                print(f'{txt_path.stem}: {len(data)} objects')\n",
        "\n",
        "        button.on_click(on_button_clicked)\n",
        "        display.display(button, output)\n",
        "\n",
        "w.observe(on_change)\n",
        "display.display(w, output)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 170,
          "referenced_widgets": [
            "90e5b9e846864964a0b563f4f26b9fab",
            "6f1a7497cb4a4765af07f97d6d466d93",
            "7ab25c9d5c4949db8d7a4b444cf6727a",
            "fe6f9d86e7ab4807beb86dda560e89d7",
            "096407b180bf439f85eeb7f7cb9828e7",
            "55525e5b455847f6b44ef6d897b8498f",
            "0764c04d4d324b2ca54c4bbe25931297",
            "01b3c6093dab449dad5a43ed391a469e"
          ]
        },
        "cellView": "form",
        "id": "3Yq3O3_P71WM",
        "outputId": "2689ef68-8ad7-4eae-c2e7-b73a374ee6f0"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Dropdown(description='choose exp:', options=('exp', '---'), value='exp')"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "90e5b9e846864964a0b563f4f26b9fab"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "fe6f9d86e7ab4807beb86dda560e89d7"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Selected /content/DT_SegNet/Detection_Output/exp\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Button(button_style='info', description='Calculate', icon='calculator', style=ButtonStyle(), tooltip='Calculat…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "55525e5b455847f6b44ef6d897b8498f"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "fe6f9d86e7ab4807beb86dda560e89d7"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2: 330 objects\n",
            "3: 331 objects\n",
            "1: 50 objects\n",
            "4: 331 objects\n"
          ]
        }
      ]
    }
  ]
}