Update utils/emotion_detection_brainai.py

utils/emotion_detection_brainai.py

@@ -40,6 +40,7 @@ class EmotionModel:
         return input_img
 
     def detect_faces(self, img, conf = 0.5):
+        input_img = self.preprocess( img, input_layer)
         result_face = self.face_compiled_model([input_img])[self.face_output_layer]
         boxes = self.post_process_face(result_face, uploaded_img_cv, conf)
 
@@ -99,40 +100,39 @@ class EmotionModel:
         
         return uploaded_img_cv
 
-emotion_model = EmotionModel()
-def play_video(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() 
+    def play_video(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
     
-    camera = cv2.VideoCapture(temporary_location)
-    fps = camera.get(cv2.CAP_PROP_FPS)
-    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4')
-    video_row=[]
-    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:
-            emotion_img = emotion_model.process(frame)
-            st_frame.image(emotion_img, channels = "BGR")
-            video_row.append(cv2.cvtColor(emotion_img,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(video_row,fps=fps)
-    clip.write_videofile(temp_file.name)
-
-    return temp_file.name
+        st_frame = st.empty()
+        while(camera.isOpened()):
+            ret, frame = camera.read()
+    
+            if ret:
+                emotion_img = self.process(frame)
+                st_frame.image(emotion_img, channels = "BGR")
+                processed_frames.append(cv2.cvtColor(emotion_img,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