Update app.py

app.py

@@ -41,13 +41,13 @@ def verify(model, detection_threshold, verification_threshold):
     # Build results array
     results = []
     ver_images= []
-    for file in os.listdir(os.path.join('')):
-      if file[len(file)-4:] == '.jpg':
-        ver_images.append(file)
+    for file in os.listdir(os.path.join('application_data', 'verification_images')):
+        if file[len(file)-4:] == '.jpg':
+            ver_images.append(file)
     ver_images_len= len(ver_images)
     for image in ver_images:
-        input_img = preprocess(os.path.join('input_image.jpg'))
-        validation_img = preprocess(os.path.join('', image))
+        input_img = preprocess(os.path.join('application_data', 'input_image', 'input_image.jpg'))
+        validation_img = preprocess(os.path.join('application_data', 'verification_images', image))
         # Make Predictions 
         result = model.predict(list(np.expand_dims([input_img, validation_img], axis=1)))
         results.append(result)
@@ -60,15 +60,19 @@ def verify(model, detection_threshold, verification_threshold):
     print('Verification -- ',verification)
     verified = verification > verification_threshold
     
-    return detection,verification,verified,ver_images_len
+    return detection,verification,verified,ver_images_len 
+
+
+       
 
 def take_ver_images (image):
-    count =0
-    cv2.imwrite(os.path.join('{}.jpg'.format(uuid.uuid1())), image)
+    for file in os.listdir(os.path.join('application_data', 'verification_images')):
+       os.remove(file)
+    cv2.imwrite(os.path.join('application_data', 'verification_images', '{}.jpg'.format(uuid.uuid1())), image)
     count+=1
     return '{} Image Collected!'.format(count)
 def verify_identity (image):
-  cv2.imwrite(os.path.join('input_image.jpg'), image)
+  cv2.imwrite(os.path.join('application_data', 'input_image', 'input_image.jpg'), image)
   detection,verification,verified,ver_images_len = verify(siamese_model, 0.8, 0.7)
   # return {'Detections': int(detection),'Confidence': float(verification),'Verified': bool(verified)}
   return 'Detected {} out of {} samples'.format(detection,ver_images_len),float(verification),'Verified' if verified else 'Not Verified'