Merge pull request PaddlePaddle#9 from jiweibo/add_yolo_demo

[yolov3] Add yolov3 demo
zhoutianzi666 · May 20, 2020 · 108fab2 · 108fab2
2 parents b105710 + 942d450
commit 108fab2
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diff --git a/c++/yolov3/CMakeLists.txt b/c++/yolov3/CMakeLists.txt
@@ -0,0 +1,96 @@
+cmake_minimum_required(VERSION 3.0)
+project(cpp_inference_demo CXX C)
+option(WITH_MKL        "Compile demo with MKL/OpenBlas support, default use MKL."       ON)
+option(WITH_GPU        "Compile demo with GPU/CPU, default use CPU."                    OFF)
+option(WITH_STATIC_LIB "Compile demo with static/shared library, default use static."   ON)
+option(USE_TENSORRT "Compile demo with TensorRT."   OFF)
+
+
+macro(safe_set_static_flag)
+    foreach(flag_var
+        CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_DEBUG CMAKE_CXX_FLAGS_RELEASE
+        CMAKE_CXX_FLAGS_MINSIZEREL CMAKE_CXX_FLAGS_RELWITHDEBINFO)
+      if(${flag_var} MATCHES "/MD")
+        string(REGEX REPLACE "/MD" "/MT" ${flag_var} "${${flag_var}}")
+      endif(${flag_var} MATCHES "/MD")
+    endforeach(flag_var)
+endmacro()
+
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
+set(CMAKE_STATIC_LIBRARY_PREFIX "")
+message("flags" ${CMAKE_CXX_FLAGS})
+
+if(NOT DEFINED PADDLE_LIB)
+  message(FATAL_ERROR "please set PADDLE_LIB with -DPADDLE_LIB=/path/paddle/lib")
+endif()
+if(NOT DEFINED DEMO_NAME)
+  message(FATAL_ERROR "please set DEMO_NAME with -DDEMO_NAME=demo_name")
+endif()
+
+
+include_directories("${PADDLE_LIB}")
+include_directories("${PADDLE_LIB}/third_party/install/protobuf/include")
+include_directories("${PADDLE_LIB}/third_party/install/glog/include")
+include_directories("${PADDLE_LIB}/third_party/install/gflags/include")
+include_directories("${PADDLE_LIB}/third_party/install/xxhash/include")
+include_directories("${PADDLE_LIB}/third_party/install/zlib/include")
+include_directories("${PADDLE_LIB}/third_party/boost")
+include_directories("${PADDLE_LIB}/third_party/eigen3")
+
+if (USE_TENSORRT AND WITH_GPU)
+      include_directories("${TENSORRT_ROOT}/include")
+      link_directories("${TENSORRT_ROOT}/lib")
+endif()
+
+link_directories("${PADDLE_LIB}/third_party/install/zlib/lib")
+
+link_directories("${PADDLE_LIB}/third_party/install/protobuf/lib")
+link_directories("${PADDLE_LIB}/third_party/install/glog/lib")
+link_directories("${PADDLE_LIB}/third_party/install/gflags/lib")
+link_directories("${PADDLE_LIB}/third_party/install/xxhash/lib")
+link_directories("${PADDLE_LIB}/paddle/lib")
+
+add_executable(${DEMO_NAME} ${DEMO_NAME}.cc)
+
+if(WITH_MKL)
+  include_directories("${PADDLE_LIB}/third_party/install/mklml/include")
+  set(MATH_LIB ${PADDLE_LIB}/third_party/install/mklml/lib/libmklml_intel${CMAKE_SHARED_LIBRARY_SUFFIX}
+               ${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5${CMAKE_SHARED_LIBRARY_SUFFIX})
+  set(MKLDNN_PATH "${PADDLE_LIB}/third_party/install/mkldnn")
+  if(EXISTS ${MKLDNN_PATH})
+    include_directories("${MKLDNN_PATH}/include")
+    set(MKLDNN_LIB ${MKLDNN_PATH}/lib/libmkldnn.so.0)
+  endif()
+else()
+  set(MATH_LIB ${PADDLE_LIB}/third_party/install/openblas/lib/libopenblas${CMAKE_STATIC_LIBRARY_SUFFIX})
+endif()
+
+# Note: libpaddle_inference_api.so/a must put before libpaddle_fluid.so/a
+if(WITH_STATIC_LIB)
+  set(DEPS
+      ${PADDLE_LIB}/paddle/lib/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
+else()
+  set(DEPS
+      ${PADDLE_LIB}/paddle/lib/libpaddle_fluid${CMAKE_SHARED_LIBRARY_SUFFIX})
+endif()
+
+set(EXTERNAL_LIB "-lrt -ldl -lpthread")
+set(DEPS ${DEPS}
+    ${MATH_LIB} ${MKLDNN_LIB}
+    glog gflags protobuf z xxhash
+    ${EXTERNAL_LIB})
+
+if(WITH_GPU)
+  if (USE_TENSORRT)
+    set(DEPS ${DEPS}
+        ${TENSORRT_ROOT}/lib/libnvinfer${CMAKE_SHARED_LIBRARY_SUFFIX})
+    set(DEPS ${DEPS}
+        ${TENSORRT_ROOT}/lib/libnvinfer_plugin${CMAKE_SHARED_LIBRARY_SUFFIX})
+  endif()
+  set(DEPS ${DEPS} ${CUDA_LIB}/libcudart${CMAKE_SHARED_LIBRARY_SUFFIX})
+  set(DEPS ${DEPS} ${CUDA_LIB}/libcudart${CMAKE_SHARED_LIBRARY_SUFFIX} )
+  set(DEPS ${DEPS} ${CUDA_LIB}/libcublas${CMAKE_SHARED_LIBRARY_SUFFIX} )
+  set(DEPS ${DEPS} ${CUDNN_LIB}/libcudnn${CMAKE_SHARED_LIBRARY_SUFFIX} )
+endif()
+
+target_link_libraries(${DEMO_NAME} ${DEPS})
diff --git a/c++/yolov3/README.md b/c++/yolov3/README.md
@@ -0,0 +1,50 @@
+## 运行C++ YOLOv3图像检测样例
+
+### 一：获取YOLOv3模型
+
+点击[链接](https://paddle-inference-dist.cdn.bcebos.com/PaddleLite/yolov3_infer.tar.gz)下载模型， 该模型在imagenet数据集训练得到的，如果你想获取更多的**模型训练信息**，请访问[这里](https://github.com/PaddlePaddle/PaddleDetection)。
+
+### 二：**样例编译**
+
+文件`yolov3_test.cc` 为预测的样例程序（程序中的输入为固定值，如果您有opencv或其他方式进行数据读取的需求，需要对程序进行一定的修改）。    
+文件`CMakeLists.txt` 为编译构建文件。   
+脚本`run_impl.sh` 包含了第三方库、预编译库的信息配置。
+
+编译yolov3样例，我们首先需要对脚本`run_impl.sh` 文件中的配置进行修改。
+
+1）**修改`run_impl.sh`**
+
+打开`run_impl.sh`，我们对以下的几处信息进行修改：
+
+```shell
+# 根据预编译库中的version.txt信息判断是否将以下三个标记打开
+WITH_MKL=ON
+WITH_GPU=ON
+USE_TENSORRT=OFF
+
+# 配置预测库的根目录
+LIB_DIR=${YOUR_LIB_DIR}/fluid_inference_install_dir
+
+# 如果上述的WITH_GPU 或 USE_TENSORRT设为ON，请设置对应的CUDA， CUDNN， TENSORRT的路径。
+CUDNN_LIB=/usr/local/cudnn/lib64
+CUDA_LIB=/usr/local/cuda/lib64
+# TENSORRT_ROOT=/usr/local/TensorRT-6.0.1.5
+```
+
+运行 `sh run_impl.sh`， 会在目录下产生build目录。
+
+
+2） **运行样例**
+
+```shell
+# 进入build目录
+cd build
+# 运行样例
+./yolov3_test -model_file ${YOLO_MODEL_PATH}/__model__ --params_file ${YOLO_MODEL_PATH}/__params__
+```
+
+运行结束后，程序会将模型输出个数打印到屏幕，说明运行成功。
+
+### 更多链接
+- [Paddle Inference使用Quick Start！]()
+- [Paddle Inference Python Api使用]()
diff --git a/c++/yolov3/run_impl.sh b/c++/yolov3/run_impl.sh
@@ -0,0 +1,29 @@
+work_path=$(dirname $(readlink -f $0))
+
+mkdir -p build
+cd build
+rm -rf *
+
+# same with the yolov3_test.cc
+DEMO_NAME=yolov3_test
+
+WITH_MKL=ON
+WITH_GPU=ON
+USE_TENSORRT=OFF
+
+LIB_DIR=${work_path}/fluid_inference_install_dir
+CUDNN_LIB=/usr/local/cudnn/lib64
+CUDA_LIB=/usr/local/cuda/lib64
+# TENSORRT_ROOT=/usr/local/TensorRT-6.0.1.5
+
+cmake .. -DPADDLE_LIB=${LIB_DIR} \
+  -DWITH_MKL=${WITH_MKL} \
+  -DDEMO_NAME=${DEMO_NAME} \
+  -DWITH_GPU=${WITH_GPU} \
+  -DWITH_STATIC_LIB=OFF \
+  -DUSE_TENSORRT=${USE_TENSORRT} \
+  -DCUDNN_LIB=${CUDNN_LIB} \
+  -DCUDA_LIB=${CUDA_LIB} \
+  -DTENSORRT_ROOT=${TENSORRT_ROOT}
+
+make -j
diff --git a/c++/yolov3/yolov3_test.cc b/c++/yolov3/yolov3_test.cc
@@ -0,0 +1,99 @@
+#include "paddle/include/paddle_inference_api.h"
+
+#include <numeric>
+#include <iostream>
+#include <memory>
+#include <chrono>
+
+#include <gflags/gflags.h>
+#include <glog/logging.h>
+
+using paddle::AnalysisConfig;
+
+DEFINE_string(model_file, "", "Directory of the inference model.");
+DEFINE_string(params_file, "", "Directory of the inference model.");
+DEFINE_string(model_dir, "", "Directory of the inference model.");
+DEFINE_int32(batch_size, 1, "Directory of the inference model.");
+DEFINE_bool(use_gpu, false, "enable gpu");
+DEFINE_bool(use_mkldnn, false, "enable mkldnn");
+DEFINE_bool(mem_optim, false, "enable memory optimize");
+
+using Time = decltype(std::chrono::high_resolution_clock::now());
+Time time() { return std::chrono::high_resolution_clock::now(); };
+double time_diff(Time t1, Time t2) {
+  typedef std::chrono::microseconds ms;
+  auto diff = t2 - t1;
+  ms counter = std::chrono::duration_cast<ms>(diff);
+  return counter.count() / 1000.0;
+}
+
+std::unique_ptr<paddle::PaddlePredictor> CreatePredictor() {
+  AnalysisConfig config;
+  if (FLAGS_model_dir != "") {
+    config.SetModel(FLAGS_model_dir);
+  } else {
+    config.SetModel(FLAGS_model_file,
+                    FLAGS_params_file);
+  }
+  if (FLAGS_use_gpu) {
+    config.EnableUseGpu(100, 0);
+  }
+  if (FLAGS_use_mkldnn) {
+    config.EnableMKLDNN();
+  }
+  // Open the memory optim.
+  if (FLAGS_mem_optim) {
+    config.EnableMemoryOptim();
+  }
+  // We use ZeroCopy, so we set config->SwitchUseFeedFetchOps(false)
+  config.SwitchUseFeedFetchOps(false);
+  return CreatePaddlePredictor(config);
+}
+
+void run(paddle::PaddlePredictor *predictor,
+         const std::vector<float>& input,
+         const std::vector<int>& input_shape, 
+         const std::vector<int>& input_im,
+         const std::vector<int>& input_im_shape,
+         std::vector<float> *out_data) {
+  auto input_names = predictor->GetInputNames();
+  auto input_img = predictor->GetInputTensor(input_names[0]);
+  input_img->Reshape(input_shape);
+  input_img->copy_from_cpu(input.data());
+
+  auto input_size = predictor->GetInputTensor(input_names[1]);
+  input_size->Reshape(input_im_shape);
+  input_size->copy_from_cpu(input_im.data());
+
+  CHECK(predictor->ZeroCopyRun());
+
+  auto output_names = predictor->GetOutputNames();
+  // there is only one output of yolov3
+  auto output_t = predictor->GetOutputTensor(output_names[0]);
+  std::vector<int> output_shape = output_t->shape();
+  int out_num = std::accumulate(output_shape.begin(), output_shape.end(), 1, std::multiplies<int>());
+
+  out_data->resize(out_num);
+  output_t->copy_to_cpu(out_data->data());
+}
+
+int main(int argc, char* argv[]) {
+  google::ParseCommandLineFlags(&argc, &argv, true);
+  auto predictor = CreatePredictor();
+
+  const int height = 608;
+  const int width = 608;
+  const int channels = 3;
+  std::vector<int> input_shape = {FLAGS_batch_size, channels, height, width};
+  std::vector<float> input_data(FLAGS_batch_size * channels * height * width, 0);
+  for (size_t i = 0; i < input_data.size(); ++i) {
+    input_data[i] = i % 255 * 0.13f;
+  }
+  std::vector<int> input_im_shape = {FLAGS_batch_size, 2};
+  std::vector<int> input_im_data(FLAGS_batch_size * 2, 608);
+
+  std::vector<float> out_data;
+  run(predictor.get(), input_data, input_shape, input_im_data, input_im_shape, &out_data);
+  LOG(INFO) << "output num is " << out_data.size();
+  return 0;
+}
diff --git a/python/resnet50/README.md b/python/resnet50/README.md
@@ -29,7 +29,7 @@
 ### 三：运行预测
 
 文件`img_preprocess.py`包含了图像的预处理。    
-文件`infer_resnet.py` 包含了创建predictor，读取事例图片，预测，获取输出的等功能。   
+文件`infer_resnet.py` 包含了创建predictor，读取示例图片，预测，获取输出的等功能。
 
 运行：
 ```

diff --git a/python/yolov3/README.md b/python/yolov3/README.md
@@ -0,0 +1,70 @@
+## 运行YOLOv3图像检测样例
+
+
+### 一：准备环境
+
+请您在环境中安装1.7或以上版本的Paddle，具体的安装方式请参照[飞桨官方页面](https://www.paddlepaddle.org.cn/)的指示方式。
+
+
+### 二：下载模型以及测试数据
+
+
+1）**获取预测模型**
+
+点击[链接](https://paddle-inference-dist.cdn.bcebos.com/PaddleLite/yolov3_infer.tar.gz)下载模型， 该模型在imagenet数据集训练得到的，如果你想获取更多的**模型训练信息**，请访问[这里](https://github.com/PaddlePaddle/PaddleDetection)。
+
+
+2）**获取预测样例图片**
+
+下载[样例图片](https://paddle-inference-dist.bj.bcebos.com/inference_demo/images/kite.jpg)。
+
+图片如下：
+<p align="left">
+    <br>
+<img src='https://paddle-inference-dist.bj.bcebos.com/inference_demo/images/kite.jpg' width = "200" height = "200">
+    <br>
+<p>
+
+
+### 三：运行预测
+
+文件`utils.py`包含了图像的预处理等帮助函数。
+文件`infer_yolov3.py` 包含了创建predictor，读取示例图片，预测，获取输出的等功能。
+
+运行：
+```
+python infer_yolov3.py --model_file=./yolov3_infer/__model__ --params_file=./yolov3_infer/__params__ --use_gpu=1
+```
+
+输出结果如下所示：
+
+```
+('category id is ', 0.0, ', bbox is ', array([ 98.47467, 471.34283, 120.73273, 578.5184 ], dtype=float32))
+('category id is ', 0.0, ', bbox is ', array([ 51.752716, 415.51324 ,  73.18762 , 515.24005 ], dtype=float32))
+('category id is ', 0.0, ', bbox is ', array([ 37.176304, 343.378   ,  46.64221 , 380.92963 ], dtype=float32))
+('category id is ', 0.0, ', bbox is ', array([155.78638, 328.0806 , 159.5393 , 339.37192], dtype=float32))
+('category id is ', 0.0, ', bbox is ', array([233.86328, 339.96912, 239.35403, 355.3322 ], dtype=float32))
+('category id is ', 0.0, ', bbox is ', array([ 16.212902, 344.42365 ,  25.193722, 377.97137 ], dtype=float32))
+('category id is ', 0.0, ', bbox is ', array([ 10.583471, 356.67862 ,  14.9261  , 372.8137  ], dtype=float32))
+('category id is ', 0.0, ', bbox is ', array([ 79.76479, 364.19492,  86.07656, 385.64255], dtype=float32))
+('category id is ', 0.0, ', bbox is ', array([312.8938 , 311.9908 , 314.58527, 316.60056], dtype=float32))
+('category id is ', 33.0, ', bbox is ', array([266.97925 ,  51.70044 , 299.45105 ,  99.996414], dtype=float32))
+('category id is ', 33.0, ', bbox is ', array([210.45593, 229.92128, 217.77551, 240.97136], dtype=float32))
+('category id is ', 33.0, ', bbox is ', array([125.36278, 159.80171, 135.49306, 189.8976 ], dtype=float32))
+('category id is ', 33.0, ', bbox is ', array([486.9354 , 266.164  , 494.4437 , 283.84637], dtype=float32))
+('category id is ', 33.0, ', bbox is ', array([259.01584, 232.23044, 270.69266, 248.58704], dtype=float32))
+('category id is ', 33.0, ', bbox is ', array([135.60567, 254.57668, 144.96178, 276.9275 ], dtype=float32))
+('category id is ', 33.0, ', bbox is ', array([341.91315, 255.44394, 345.0335 , 262.3398 ], dtype=float32))
+```
+
+<p align="left">
+    <br>
+<img src='https://paddle-inference-dist.bj.bcebos.com/inference_demo/images/kite_res.jpg' width = "200" height = "200">
+    <br>
+<p>
+
+
+### 相关链接
+- [Paddle Inference使用Quick Start！]()
+- [Paddle Inference Python Api使用]()
+
diff --git a/python/yolov3/infer_yolov3.py b/python/yolov3/infer_yolov3.py
@@ -1,9 +1,13 @@
 import numpy as np
 import argparse
+import cv2
+from PIL import Image
 
 from paddle.fluid.core import AnalysisConfig
 from paddle.fluid.core import create_paddle_predictor
 
+from utils import preprocess, draw_bbox
+
 def create_predictor(args):
    if args.model_dir is not "":
      config = AnalysisConfig(args.model_dir)
@@ -54,10 +58,13 @@ def parse_args():
 
 if __name__ == '__main__':
   args = parse_args()
+  img_name = 'kite.jpg'
+  save_img_name = 'res.jpg'
+  im_size = 608
   pred = create_predictor(args) 
-  data = np.ones((1, 3, 608, 608)).astype(np.float32)
-  im_shape = np.array([608, 608]).reshape((1,2)).astype(np.int32)
-  result = run(pred, [data, im_shape]) 
-
-  print (result[0])
-
+  img = cv2.imread(img_name)
+  data = preprocess(img, im_size)
+  im_shape = np.array([im_size, im_size]).reshape((1,2)).astype(np.int32)
+  result = run(pred, [data, im_shape])
+  img = Image.open(img_name).convert('RGB').resize((im_size, im_size))
+  draw_bbox(img, result[0], save_name=save_img_name)