Updated Application File

app.py

@@ -18,10 +18,8 @@ output_frames = []
 
 def find_hands(brain, img):
     if img is not None:
-        # print(type(img))
         img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)  # opencv image is in BGR form but mp is trained with RGB
-        results = brain.process(
-            img_rgb)  # process finds the hands and outputs classification and 21 landmarks for each hand
+        results = brain.process(img_rgb)  # process finds the hands and outputs classification and 21 landmarks for each hand
         all_hands = []  # initializing array to hold the dictionary for the hands
         h, w, _ = img.shape  # get height and width of image for scaling
         if results.multi_hand_landmarks:
@@ -43,7 +41,6 @@ def find_hands(brain, img):
         return 0
 
 
-
 def is_drawing(index, thumb):  # proximity function with arbitrary threshold
     npindex = np.array((index[0], index[1]))
     npthumb = np.array((thumb[0], thumb[1]))
@@ -190,7 +187,8 @@ def show(video): # main
 
     return 'any.webm'
 
-
+title = 'Air Draw'
+desc = 'A Mediapipe Hands Wrapper for Drawing in the Air'
 iface = gr.Interface(fn=show, inputs=gr.inputs.Video(source="webcam"), outputs='video')
 
 iface.launch(share=True, enable_queue=True)