fix PP-HumanV2 PP-TinyPose PP-Vehicle video adaptive code (#5689)

* fix PP-HumanV2 PP-Vehicle Single choice bug

* add PP-TinyPose model file

* modified PP-TinyPose auto download model

* del modelcenter/PP-TinyPose/APP/output_inference/

* add PP-TinyPose PP-HumanV2 PP-Vehicle video format checks

* fix PP-HumanV2 PP-TinyPose PP-Vehicle video adaptive code

modelcenter/PP-HumanV2/APP/pipeline/pipeline.py

@@ -389,8 +389,7 @@ class PipePredictor(object):
 
     def set_file_name(self, path):
         if path is not None:
-            if "." in path:
-                self.file_name = path.split(".")[-2]
+            self.file_name = path
         else:
             # use camera id
             self.file_name = None
@@ -446,9 +445,9 @@ class PipePredictor(object):
         frame_count = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
         print("video fps: %d, frame_count: %d" % (fps, frame_count))
 
-        video_out_name = 'output' if self.file_name is None else self.file_name
-        out_path = video_out_name + "_output.mp4"
-        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+        video_name,suffix = os.path.splitext(self.file_name)
+        out_path = video_name + "_output"+suffix
+        fourcc = int(capture.get(cv2.CAP_PROP_FOURCC))
         writer = cv2.VideoWriter(out_path, fourcc, fps, (width, height))
 
         frame_id = 0

modelcenter/PP-TinyPose/APP/det_keypoint_unite_infer.py

@@ -107,18 +107,18 @@ def topdown_unite_predict_video(FLAGS,
         capture = cv2.VideoCapture(camera_id)
     else:
         capture = cv2.VideoCapture(FLAGS.video_file)
-        video_name,suffix = FLAGS.video_file.split('.')
-        video_name = video_name+"_output."+suffix
+        video_name,suffix = os.path.splitext(FLAGS.video_file) 
+        video_name = video_name+"_output"+suffix
+    
     # Get Video info : resolution, fps, frame count
     width = int(capture.get(cv2.CAP_PROP_FRAME_WIDTH))
     height = int(capture.get(cv2.CAP_PROP_FRAME_HEIGHT))
     fps = int(capture.get(cv2.CAP_PROP_FPS))
     frame_count = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
     print("fps: %d, frame_count: %d" % (fps, frame_count))
-
-   
-    fourcc = cv2.VideoWriter_fourcc(* 'mp4v')
-    writer = cv2.VideoWriter(video_name, fourcc, fps, (width, height))
+    
+    codec = int(capture.get(cv2.CAP_PROP_FOURCC))
+    writer = cv2.VideoWriter(video_name, codec, fps, (width, height))
     index = 0
     store_res = []
     keypoint_smoothing = KeypointSmoothing(

modelcenter/PP-Vehicle/APP/pipeline/pipeline.py

@@ -329,8 +329,7 @@ class PipePredictor(object):
 
     def set_file_name(self, path):
         if path is not None:
-            if "." in path:
-                self.file_name = path.split(".")[-2]
+            self.file_name = path
         else:
             # use camera id
             self.file_name = None
@@ -397,9 +396,9 @@ class PipePredictor(object):
         frame_count = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
         print("video fps: %d, frame_count: %d" % (fps, frame_count))
 
-        video_out_name = 'output' if self.file_name is None else self.file_name
-        out_path = video_out_name + "_output.mp4"
-        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+        video_name,suffix = os.path.splitext(self.file_name)
+        out_path = video_name + "_output"+suffix
+        fourcc = int(capture.get(cv2.CAP_PROP_FOURCC))
         writer = cv2.VideoWriter(out_path, fourcc, fps, (width, height))
 
         frame_id = 0