Update app.py

app.py

@@ -5,20 +5,33 @@ import face_recognition
 from fastai.vision.all import load_learner
 import time
 import chardet
+import base64
+
+import pathlib
+temp = pathlib.PosixPath
+pathlib.PosixPath = pathlib.WindowsPath
+
 
 model = load_learner("gaze-recognizer-v1.pkl")
 
-def video_processing(video):
-    print('Type')
-    print(type(video))
-    print(video)
-    #print('video encoding done into = ' + chardet.detect(video)['encoding'])
+def video_processing(video_file, encoded_video):
+
+    if encoded_video != "":
+    
+        decoded_file_data = base64.b64decode(encoded_video)
+
+        with open("temp_video.mp4", "wb") as f:
+            f.write(decoded_file_data)
+        
+        video_file = "temp_video.mp4"
+
     start_time = time.time()
-    # Loop through the frames of the video
-    video_capture = cv2.VideoCapture(video)
+    
+    video_capture = cv2.VideoCapture(video_file)
     on_camera = 0
     off_camera = 0
     total = 0
+
     while True:
         # Read a single frame from the video
         for i in range(24*3):
@@ -67,14 +80,15 @@ def video_processing(video):
     cv2.destroyAllWindows()
     end_time = time.time()
     print(f'Time taken: {end_time-start_time}')
+    if os.path.exists("temp_video.mp4"): 
+        os.remove("temp_video.mp4")
     print(gaze_percentage)
     return str(gaze_percentage)
 
 
-demo = gr.Interface(fn = video_processing,
-                    inputs= 'video',#gr.Video(),
-                    outputs = 'text'
-                    )
+demo = gr.Interface(fn=video_processing,
+                     inputs=["video", "text"],
+                     outputs="text")
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()