a

.ipynb_checkpoints/app-checkpoint.py

@@ -5,36 +5,38 @@ from encoded_video import EncodedVideo, write_video
 import torch
 import numpy as np
 
-def video_identity(video,user_name,class_name):
+def video_identity(video,user_name,class_name,trainortest,ready):
+    if ready=='yes':
+        return user_name
+    else:
+        capture = cv2.VideoCapture(video)
+   
+        user_d=str(trainortest)+str(user_name)
+        class_d=str(trainortest)+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):
 
-    here='nothing'
-    capture = cv2.VideoCapture(video)
-    user_d=str(user_name)
-    class_d=str(user_name)+'/'+str(class_name)
-    if os.path.exists(class_d):
-        here='something'
-    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()
+            success, frame = capture.read()
 
-        if success:
-            cv2.imwrite(f'{class_d}/frame_{frameNr}.jpg', frame)
+            if success:
+                cv2.imwrite(f'{class_d}/frame_{frameNr}.jpg', frame)
 
-        else:
-            break
+            else:
+                break
 
-        frameNr = frameNr+10
-        
-    img=cv2.imread(class_d+'/frame_0.jpg')
-    
-    return img, here
+            frameNr = frameNr+10
+
+        img=cv2.imread(class_d+'/frame_0.jpg')
+
+        return img, class_d
 demo = gr.Interface(video_identity, 
                     inputs=[gr.Video(source='upload'),
+                            gr.Text(),
+                            gr.Text(),
                             gr.Text(),
                             gr.Text()],
                     outputs=[gr.Image(),

app.py

@@ -5,36 +5,38 @@ from encoded_video import EncodedVideo, write_video
 import torch
 import numpy as np
 
-def video_identity(video,user_name,class_name):
+def video_identity(video,user_name,class_name,trainortest,ready):
+    if ready=='yes':
+        return user_name
+    else:
+        capture = cv2.VideoCapture(video)
+   
+        user_d=str(trainortest)+str(user_name)
+        class_d=str(trainortest)+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):
 
-    here='nothing'
-    capture = cv2.VideoCapture(video)
-    user_d=str(user_name)
-    class_d=str(user_name)+'/'+str(class_name)
-    if os.path.exists(class_d):
-        here='something'
-    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()
+            success, frame = capture.read()
 
-        if success:
-            cv2.imwrite(f'{class_d}/frame_{frameNr}.jpg', frame)
+            if success:
+                cv2.imwrite(f'{class_d}/frame_{frameNr}.jpg', frame)
 
-        else:
-            break
+            else:
+                break
 
-        frameNr = frameNr+10
-        
-    img=cv2.imread(class_d+'/frame_0.jpg')
-    
-    return img, here
+            frameNr = frameNr+10
+
+        img=cv2.imread(class_d+'/frame_0.jpg')
+
+        return img, class_d
 demo = gr.Interface(video_identity, 
                     inputs=[gr.Video(source='upload'),
+                            gr.Text(),
+                            gr.Text(),
                             gr.Text(),
                             gr.Text()],
                     outputs=[gr.Image(),