a

.ipynb_checkpoints/app-checkpoint.py

@@ -5,29 +5,35 @@ from encoded_video import EncodedVideo, write_video
 import torch
 import numpy as np
 
-def video_identity(video,text):
+def video_identity(video,user_name,class_name):
 
 
     capture = cv2.VideoCapture(video)
-     
+    user_d=str(user_name)
+    class_d=str(user_name)+'/'+str(class_name)
+    if not os.path.exists(user_d):
+        os.makedirs(user_d) 
+    if not os.path.exists(class_d):
+        os.makedirs(class_d)
     frameNr = 0
     while (True):
     
         success, frame = capture.read()
 
         if success:
-            cv2.imwrite(f'frame_{frameNr}.jpg', frame)
+            cv2.imwrite(f'{class_d}/frame_{frameNr}.jpg', frame)
 
         else:
             break
 
         frameNr = frameNr+10
         
-    img=cv2.imread('frame_0.jpg')
+    img=cv2.imread(class_d+'/frame_0.jpg')
     
     return img, text
 demo = gr.Interface(video_identity, 
                     inputs=[gr.Video(source='upload'),
+                            gr.Text(),
                             gr.Text()],
                     outputs=[gr.Image(),
                              gr.Text()],

app.py

@@ -5,29 +5,35 @@ from encoded_video import EncodedVideo, write_video
 import torch
 import numpy as np
 
-def video_identity(video,text):
+def video_identity(video,user_name,class_name):
 
 
     capture = cv2.VideoCapture(video)
-     
+    user_d=str(user_name)
+    class_d=str(user_name)+'/'+str(class_name)
+    if not os.path.exists(user_d):
+        os.makedirs(user_d) 
+    if not os.path.exists(class_d):
+        os.makedirs(class_d)
     frameNr = 0
     while (True):
     
         success, frame = capture.read()
 
         if success:
-            cv2.imwrite(f'frame_{frameNr}.jpg', frame)
+            cv2.imwrite(f'{class_d}/frame_{frameNr}.jpg', frame)
 
         else:
             break
 
         frameNr = frameNr+10
         
-    img=cv2.imread('frame_0.jpg')
+    img=cv2.imread(class_d+'/frame_0.jpg')
     
     return img, text
 demo = gr.Interface(video_identity, 
                     inputs=[gr.Video(source='upload'),
+                            gr.Text(),
                             gr.Text()],
                     outputs=[gr.Image(),
                              gr.Text()],