Update utils/object_detection_brainai.py

utils/object_detection_brainai.py

@@ -39,42 +39,6 @@ class ObjectDetectionModel():
 
         return img_plot, f'Objects Detected: {", ".join(detected_classes) if detected_classes else "No objects detected"}'
 
-    def play_video_orig(self, input_video):
-        uploaded_video = io.BytesIO(input_video.read())
-        temporary_location = "upload.mp4" 
-        with open(temporary_location, "wb") as out: 
-            out.write(uploaded_video.read())
-        out.close() 
-        
-        camera = cv2.VideoCapture(temporary_location)
-        fps = camera.get(cv2.CAP_PROP_FPS)
-        temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4')
-        processed_frames=[]
-        total_frames = int(camera.get(cv2.CAP_PROP_FRAME_COUNT))
-        progress_bar = st.progress(0)
-        frame_count = 0
-    
-        st_frame = st.empty()
-        while(camera.isOpened()):
-            ret, frame = camera.read()
-    
-            if ret:
-                img_plot, _ = self.process_image(frame)
-                st_frame.image(img_plot, channels = "BGR")
-                processed_frames.append(cv2.cvtColor(img_plot,cv2.COLOR_BGR2RGB))
-                frame_count +=1
-                progress_bar.progress(frame_count/total_frames, text = None)
-    
-            else:
-                camera.release()
-                st_frame.empty()
-                progress_bar.empty()
-                break
-        clip = mpy.ImageSequenceClip(processed_frames,fps=fps)
-        clip.write_videofile(temp_file.name)
-    
-        return temp_file.name
-
     def play_video(self, video_path):
 
         uploaded_video = io.BytesIO(video_path.read())
@@ -84,13 +48,8 @@ class ObjectDetectionModel():
         temp_out.close()
         
         camera = cv2.VideoCapture(temporary_location)
-        frame_width = int(camera.get(cv2.CAP_PROP_FRAME_WIDTH))
-        frame_height = int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT))
         fps = camera.get(cv2.CAP_PROP_FPS)
-
-        fourcc = cv2.VideoWriter_fourcc(*'X264')
-        output_video_path = 'output_video.mp4'
-        out = cv2.VideoWriter(output_video_path,fourcc,fps, (frame_width,frame_height))
+        temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4')
         processed_frames = []
 
         total_frames = int(camera.get(cv2.CAP_PROP_FRAME_COUNT))
@@ -112,15 +71,13 @@ class ObjectDetectionModel():
             progress_bar.progress(frame_count/total_frames, text = None)
             
         camera.release()
-        for frame in processed_frames:
-             out.write(frame)
-        out.release()
+        clip = mpy.ImageSequenceClip(processed_frames, fps=fps)
+        clip.write_videofile(temp_file.name)
 
         st_frame.empty()
         progress_bar.empty()
 
-        return output_video_path
-
+        return temp_file.name
     
     def call_class(self):
         random_class = random.choice(list(self.game_classes))