person_count_in_frame.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4",
      "authorship_tag": "ABX9TyPDyNHJtP4+fDMqMcHHXZSD",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/mayuras7685/Hack4in-Unkils/blob/main/person_count_in_frame.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fAIuLdubxCfE",
        "outputId": "a986d5d6-2fcd-4e5c-d15e-1876a67d53b5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting supervision\n",
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            "Installing collected packages: supervision\n",
            "Successfully installed supervision-0.15.0\n",
            "Collecting ultralytics\n",
            "  Downloading ultralytics-8.0.194-py3-none-any.whl (617 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m617.4/617.4 kB\u001b[0m \u001b[31m12.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "Collecting thop>=0.1.1 (from ultralytics)\n",
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            "Installing collected packages: thop, ultralytics\n",
            "Successfully installed thop-0.1.1.post2209072238 ultralytics-8.0.194\n"
          ]
        }
      ],
      "source": [
        "!pip install supervision\n",
        "!pip install ultralytics"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1M3UuH3QNDWGiH0NmGgHtIgXXGDo_nigm' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\\1\\n/p')&id=1M3UuH3QNDWGiH0NmGgHtIgXXGDo_nigm\" -O mall.mp4 && rm -rf /tmp/cookies.txt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "okec7rEaxeVw",
        "outputId": "579cddbe-6588-423c-96cc-0c0d31c71810"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2023-10-06 11:36:39--  https://docs.google.com/uc?export=download&confirm=&id=1M3UuH3QNDWGiH0NmGgHtIgXXGDo_nigm\n",
            "Resolving docs.google.com (docs.google.com)... 142.251.2.100, 142.251.2.139, 142.251.2.138, ...\n",
            "Connecting to docs.google.com (docs.google.com)|142.251.2.100|:443... connected.\n",
            "HTTP request sent, awaiting response... 303 See Other\n",
            "Location: https://doc-0c-ag-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/imvolfhui09bi0u9ut7bvjjupvc954tp/1696592175000/04309230031174164349/*/1M3UuH3QNDWGiH0NmGgHtIgXXGDo_nigm?e=download&uuid=f73c60ac-ee27-4239-99c3-3015aef54841 [following]\n",
            "Warning: wildcards not supported in HTTP.\n",
            "--2023-10-06 11:36:41--  https://doc-0c-ag-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/imvolfhui09bi0u9ut7bvjjupvc954tp/1696592175000/04309230031174164349/*/1M3UuH3QNDWGiH0NmGgHtIgXXGDo_nigm?e=download&uuid=f73c60ac-ee27-4239-99c3-3015aef54841\n",
            "Resolving doc-0c-ag-docs.googleusercontent.com (doc-0c-ag-docs.googleusercontent.com)... 142.251.2.132, 2607:f8b0:4023:c0d::84\n",
            "Connecting to doc-0c-ag-docs.googleusercontent.com (doc-0c-ag-docs.googleusercontent.com)|142.251.2.132|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 103282086 (98M) [video/mp4]\n",
            "Saving to: ‘mall.mp4’\n",
            "\n",
            "mall.mp4            100%[===================>]  98.50M   125MB/s    in 0.8s    \n",
            "\n",
            "2023-10-06 11:36:42 (125 MB/s) - ‘mall.mp4’ saved [103282086/103282086]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import supervision as sv\n",
        "import cv2\n",
        "generator = sv.get_video_frames_generator(\"./mall.mp4\")\n",
        "iterator = iter(generator)\n",
        "frame = next(iterator)\n",
        "\n",
        "cv2.imwrite(\"frame.jpg\", frame)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GD5-h0Cbxsb2",
        "outputId": "4f3b8f5c-da06-4232-8b9f-7a7c7953d119"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import cv2\n",
        "\n",
        "MALL_VIDEO_PATH = \"/content/mall.mp4\"\n",
        "\n",
        "polygon = np.array([\n",
        "[1848, 1350],[1848, 1350],[1488, 1902],[3196, 1906],[2456, 1334],[2456, 1334],[2456, 1334],[1848, 1350]\n",
        "])\n"
      ],
      "metadata": {
        "id": "a7F7DZHDzCGt"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "video_info = sv.VideoInfo.from_video_path(MALL_VIDEO_PATH)\n",
        "zone = sv.PolygonZone(polygon=polygon, frame_resolution_wh=video_info.resolution_wh)\n",
        "\n",
        "box_annotator = sv.BoxAnnotator(thickness=4, text_thickness=4, text_scale=2)\n",
        "zone_annotator = sv.PolygonZoneAnnotator(zone=zone, color=sv.Color.white(), thickness=6, text_thickness=6, text_scale=4)"
      ],
      "metadata": {
        "id": "gTfPiG0YzwI7"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from ultralytics import YOLO\n",
        "\n",
        "model = YOLO(\"yolov8s.pt\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-a1N74nA0pAA",
        "outputId": "695f4100-54e0-44e3-fc5b-74a0dcadb416"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s.pt to 'yolov8s.pt'...\n",
            "100%|██████████| 21.5M/21.5M [00:00<00:00, 211MB/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def process_frame(frame: np.ndarray, _) -> np.ndarray:\n",
        "   results = model(frame, imgsz=1280)[0]\n",
        "   detections = sv.Detections.from_yolov8(results)\n",
        "   detections = detections[detections.class_id == 0]\n",
        "   zone.trigger(detections=detections)\n",
        "\n",
        "   box_annotator = sv.BoxAnnotator(thickness=4, text_thickness=4, text_scale=2)\n",
        "\n",
        "   labels = [f\"{model.names[class_id]} {confidence:0.2f}\" for _, _, confidence, class_id, _ in detections]\n",
        "   frame = box_annotator.annotate(scene=frame, detections=detections, labels=labels)\n",
        "   frame = zone_annotator.annotate(scene=frame)\n",
        "\n",
        "\n",
        "   return frame"
      ],
      "metadata": {
        "id": "nuXTLFRr0oVi"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sv.process_video(source_path=MALL_VIDEO_PATH, target_path=f\"mall-result.mp4\", callback=process_frame)"
      ],
      "metadata": {
        "id": "0EO7dLMp012u"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "7NFDi4Lb06_a"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}