Fix MOT module bug (#1665)

modules/video/multiple_object_tracking/fairmot_dla34/README.md

@@ -31,7 +31,7 @@
 
 - ### 1、环境依赖  
 
-  - paddledet >= 2.1.0
+  - paddledet >= 2.2.0
 
   - opencv-python
 
@@ -42,6 +42,7 @@
     ```
   - 如您安装时遇到问题，可参考：[零基础windows安装](../../../../docs/docs_ch/get_start/windows_quickstart.md)
  | [零基础Linux安装](../../../../docs/docs_ch/get_start/linux_quickstart.md) | [零基础MacOS安装](../../../../docs/docs_ch/get_start/mac_quickstart.md)
+  - 在windows下安装，由于paddledet package会依赖cython-bbox以及pycocotools, 这两个包需要windows用户提前装好，可参考[cython-bbox安装](https://blog.csdn.net/qq_24739717/article/details/105588729)和[pycocotools安装](https://github.com/PaddlePaddle/PaddleX/blob/release/1.3/docs/install.md#pycocotools安装问题)
 ## 三、模型API预测
 
 - ### 1、命令行预测

modules/video/multiple_object_tracking/fairmot_dla34/module.py

@@ -31,7 +31,8 @@ from .tracker import StreamTracker
 logger = setup_logger('Predict')
 
 
-@moduleinfo(name="fairmot_dla34",
+@moduleinfo(
+    name="fairmot_dla34",
     type="CV/multiple_object_tracking",
     author="paddlepaddle",
     author_email="",
@@ -70,7 +71,8 @@ class FairmotTracker_1088x608:
         tracker.load_weights_jde(self.pretrained_model)
         signal.signal(signal.SIGINT, self.signalhandler)
         # inference
-        tracker.videostream_predict(video_stream=video_stream,
+        tracker.videostream_predict(
+            video_stream=video_stream,
             output_dir=output_dir,
             data_type='mot',
             model_type='FairMOT',
@@ -106,7 +108,8 @@ class FairmotTracker_1088x608:
         return self
 
     def __enter__(self):
-        self.tracker_generator = self.tracker.imagestream_predict(self.output_dir,
+        self.tracker_generator = self.tracker.imagestream_predict(
+            self.output_dir,
             data_type='mot',
             model_type='FairMOT',
             visualization=self.visualization,
@@ -129,10 +132,12 @@ class FairmotTracker_1088x608:
                 logger.info('No output images to save for video')
                 return
             img = cv2.imread(os.path.join(save_dir, '00000.jpg'))
-            video_writer = cv2.VideoWriter(output_video_path,
+            video_writer = cv2.VideoWriter(
+                output_video_path,
+                apiPreference=0,
                 fourcc=cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'),
                 fps=30,
-                                           frameSize=[img.shape[1], img.shape[0]])
+                frameSize=(img.shape[1], img.shape[0]))
             for i in range(len(imgnames)):
                 imgpath = os.path.join(save_dir, '{:05d}.jpg'.format(i))
                 img = cv2.imread(imgpath)
@@ -169,7 +174,8 @@ class FairmotTracker_1088x608:
         """
         Run as a command.
         """
-        self.parser = argparse.ArgumentParser(description="Run the {} module.".format(self.name),
+        self.parser = argparse.ArgumentParser(
+            description="Run the {} module.".format(self.name),
             prog='hub run {}'.format(self.name),
             usage='%(prog)s',
             add_help=True)
@@ -204,10 +210,12 @@ class FairmotTracker_1088x608:
                 logger.info('No output images to save for video')
                 return
             img = cv2.imread(os.path.join(save_dir, '00000.jpg'))
-            video_writer = cv2.VideoWriter(output_video_path,
+            video_writer = cv2.VideoWriter(
+                output_video_path,
+                apiPreference=0,
                 fourcc=cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'),
                 fps=30,
-                                           frameSize=[img.shape[1], img.shape[0]])
+                frameSize=(img.shape[1], img.shape[0]))
             for i in range(len(imgnames)):
                 imgpath = os.path.join(save_dir, '{:05d}.jpg'.format(i))
                 img = cv2.imread(imgpath)
@@ -223,22 +231,16 @@ class FairmotTracker_1088x608:
         """
         self.arg_config_group.add_argument('--use_gpu', action='store_true', help="use GPU or not")
 
-        self.arg_config_group.add_argument('--output_dir',
-                                           type=str,
-                                           default='mot_result',
-                                           help='Directory name for output tracking results.')
-        self.arg_config_group.add_argument('--visualization',
-                                           action='store_true',
-                                           help="whether to save output as images.")
-        self.arg_config_group.add_argument("--draw_threshold",
-                                           type=float,
-                                           default=0.5,
-                                           help="Threshold to reserve the result for visualization.")
+        self.arg_config_group.add_argument(
+            '--output_dir', type=str, default='mot_result', help='Directory name for output tracking results.')
+        self.arg_config_group.add_argument(
+            '--visualization', action='store_true', help="whether to save output as images.")
+        self.arg_config_group.add_argument(
+            "--draw_threshold", type=float, default=0.5, help="Threshold to reserve the result for visualization.")
 
     def add_module_input_arg(self):
         """
         Add the command input options.
         """
-        self.arg_input_group.add_argument('--video_stream',
-                                          type=str,
-                                          help="path to video stream, can be a video file or stream device number.")
+        self.arg_input_group.add_argument(
+            '--video_stream', type=str, help="path to video stream, can be a video file or stream device number.")

modules/video/multiple_object_tracking/fairmot_dla34/requirements.txt

-paddledet >= 2.1.0
+cython
+paddledet >= 2.2.0
 opencv-python
+imageio

modules/video/multiple_object_tracking/fairmot_dla34/tracker.py

@@ -159,7 +159,6 @@ class StreamTracker(object):
         yield
         results = []
         while True:
-            with paddle.no_grad():
             try:
                 results, nf = next(generator)
                 yield results
@@ -175,7 +174,7 @@ class StreamTracker(object):
                             visualization=True,
                             draw_threshold=0.5):
         assert video_stream is not None, \
-            "--video_file or --image_dir should be set."
+            "--video_stream should be set."
 
         if not os.path.exists(output_dir): os.makedirs(output_dir)
         result_root = os.path.join(output_dir, 'mot_results')
@@ -215,9 +214,10 @@ class StreamTracker(object):
             img = cv2.imread(os.path.join(save_dir, '00000.jpg'))
             video_writer = cv2.VideoWriter(
                 output_video_path,
+                apiPreference=0,
                 fourcc=cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'),
                 fps=30,
-                frameSize=[img.shape[1], img.shape[0]])
+                frameSize=(img.shape[1], img.shape[0]))
             for i in range(len(imgnames)):
                 imgpath = os.path.join(save_dir, '{:05d}.jpg'.format(i))
                 img = cv2.imread(imgpath)

modules/video/multiple_object_tracking/jde_darknet53/README.md

@@ -31,7 +31,7 @@
 
 - ### 1、环境依赖  
 
-  - paddledet >= 2.1.0
+  - paddledet >= 2.2.0
 
   - opencv-python
 
@@ -42,6 +42,7 @@
     ```
   - 如您安装时遇到问题，可参考：[零基础windows安装](../../../../docs/docs_ch/get_start/windows_quickstart.md)
  | [零基础Linux安装](../../../../docs/docs_ch/get_start/linux_quickstart.md) | [零基础MacOS安装](../../../../docs/docs_ch/get_start/mac_quickstart.md)
+  - 在windows下安装，由于paddledet package会依赖cython-bbox以及pycocotools, 这两个包需要windows用户提前装好，可参考[cython-bbox安装](https://blog.csdn.net/qq_24739717/article/details/105588729)和[pycocotools安装](https://github.com/PaddlePaddle/PaddleX/blob/release/1.3/docs/install.md#pycocotools安装问题)
 
 
 ## 三、模型API预测

modules/video/multiple_object_tracking/jde_darknet53/module.py

@@ -31,7 +31,8 @@ from .tracker import StreamTracker
 logger = setup_logger('Predict')
 
 
-@moduleinfo(name="jde_darknet53",
+@moduleinfo(
+    name="jde_darknet53",
     type="CV/multiple_object_tracking",
     author="paddlepaddle",
     author_email="",
@@ -70,7 +71,8 @@ class JDETracker_1088x608:
         tracker.load_weights_jde(self.pretrained_model)
         signal.signal(signal.SIGINT, self.signalhandler)
         # inference
-        tracker.videostream_predict(video_stream=video_stream,
+        tracker.videostream_predict(
+            video_stream=video_stream,
             output_dir=output_dir,
             data_type='mot',
             model_type='JDE',
@@ -106,7 +108,8 @@ class JDETracker_1088x608:
         return self
 
     def __enter__(self):
-        self.tracker_generator = self.tracker.imagestream_predict(self.output_dir,
+        self.tracker_generator = self.tracker.imagestream_predict(
+            self.output_dir,
             data_type='mot',
             model_type='JDE',
             visualization=self.visualization,
@@ -129,10 +132,12 @@ class JDETracker_1088x608:
                 logger.info('No output images to save for video')
                 return
             img = cv2.imread(os.path.join(save_dir, '00000.jpg'))
-            video_writer = cv2.VideoWriter(output_video_path,
+            video_writer = cv2.VideoWriter(
+                output_video_path,
+                apiPreference=0,
                 fourcc=cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'),
                 fps=30,
-                                           frameSize=[img.shape[1], img.shape[0]])
+                frameSize=(img.shape[1], img.shape[0]))
             for i in range(len(imgnames)):
                 imgpath = os.path.join(save_dir, '{:05d}.jpg'.format(i))
                 img = cv2.imread(imgpath)
@@ -169,7 +174,8 @@ class JDETracker_1088x608:
         """
         Run as a command.
         """
-        self.parser = argparse.ArgumentParser(description="Run the {} module.".format(self.name),
+        self.parser = argparse.ArgumentParser(
+            description="Run the {} module.".format(self.name),
             prog='hub run {}'.format(self.name),
             usage='%(prog)s',
             add_help=True)
@@ -204,10 +210,12 @@ class JDETracker_1088x608:
                 logger.info('No output images to save for video')
                 return
             img = cv2.imread(os.path.join(save_dir, '00000.jpg'))
-            video_writer = cv2.VideoWriter(output_video_path,
+            video_writer = cv2.VideoWriter(
+                output_video_path,
+                apiPreference=0,
                 fourcc=cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'),
                 fps=30,
-                                           frameSize=[img.shape[1], img.shape[0]])
+                frameSize=(img.shape[1], img.shape[0]))
             for i in range(len(imgnames)):
                 imgpath = os.path.join(save_dir, '{:05d}.jpg'.format(i))
                 img = cv2.imread(imgpath)
@@ -223,22 +231,16 @@ class JDETracker_1088x608:
         """
         self.arg_config_group.add_argument('--use_gpu', action='store_true', help="use GPU or not")
 
-        self.arg_config_group.add_argument('--output_dir',
-                                           type=str,
-                                           default='mot_result',
-                                           help='Directory name for output tracking results.')
-        self.arg_config_group.add_argument('--visualization',
-                                           action='store_true',
-                                           help="whether to save output as images.")
-        self.arg_config_group.add_argument("--draw_threshold",
-                                           type=float,
-                                           default=0.5,
-                                           help="Threshold to reserve the result for visualization.")
+        self.arg_config_group.add_argument(
+            '--output_dir', type=str, default='mot_result', help='Directory name for output tracking results.')
+        self.arg_config_group.add_argument(
+            '--visualization', action='store_true', help="whether to save output as images.")
+        self.arg_config_group.add_argument(
+            "--draw_threshold", type=float, default=0.5, help="Threshold to reserve the result for visualization.")
 
     def add_module_input_arg(self):
         """
         Add the command input options.
         """
-        self.arg_input_group.add_argument('--video_stream',
-                                          type=str,
-                                          help="path to video stream, can be a video file or stream device number.")
+        self.arg_input_group.add_argument(
+            '--video_stream', type=str, help="path to video stream, can be a video file or stream device number.")

modules/video/multiple_object_tracking/jde_darknet53/requirements.txt

-paddledet >= 2.1.0
+cython
+paddledet >= 2.2.0
 opencv-python
+imageio

modules/video/multiple_object_tracking/jde_darknet53/tracker.py

@@ -160,7 +160,6 @@ class StreamTracker(object):
         yield
         results = []
         while True:
-            with paddle.no_grad():
             try:
                 results, nf = next(generator)
                 yield results
@@ -176,7 +175,7 @@ class StreamTracker(object):
                             visualization=True,
                             draw_threshold=0.5):
         assert video_stream is not None, \
-            "--video_file or --image_dir should be set."
+            "--video_stream should be set."
 
         if not os.path.exists(output_dir): os.makedirs(output_dir)
         result_root = os.path.join(output_dir, 'mot_results')
@@ -214,7 +213,12 @@ class StreamTracker(object):
                 logger.info('No output images to save for video')
                 return
             img = cv2.imread(os.path.join(save_dir, '00000.jpg'))
-            video_writer = cv2.VideoWriter(output_video_path, fourcc=cv2.VideoWriter_fourcc('M','J','P','G'), fps=30, frameSize=[img.shape[1],img.shape[0]])
+            video_writer = cv2.VideoWriter(
+                output_video_path,
+                apiPreference=0,
+                fourcc=cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'),
+                fps=30,
+                frameSize=(img.shape[1], img.shape[0]))
             for i in range(len(imgnames)):
                 imgpath = os.path.join(save_dir, '{:05d}.jpg'.format(i))
                 img = cv2.imread(imgpath)