Update app.py

app.py

@@ -88,18 +88,80 @@ listImg = os.listdir('model/street')
 imgList = [cv2.imread(f'model/street/{imgPath}') for imgPath in listImg]
 indexImg = 0
 
-def video_frame_callback(frame: av.VideoFrame) -> av.VideoFrame:
-    img = frame.to_ndarray(format="bgr24")
-    hands, img = detector.findHands(img, flipType=False)
 
-    # Render hand detection results
-    if hands:
-        hand = hands[0]
-        bbox = hand["bbox"]
-        cv2.rectangle(img, (bbox[0], bbox[1]), (bbox[0]+bbox[2], bbox[1]+bbox[3]), (255, 0, 0), 2)
+Function to process the video frame from the webcam
+def process_video_frame(frame: av.VideoFrame, detector, segmentor, imgList, indexImg, keys, session_state)-> av.VideoFrame:
+    # Convert the frame to a numpy array (BGR format)
+    image = frame.to_ndarray(format="bgr24")
+    
+    # Remove background using SelfiSegmentation
+    imgOut = segmentor.removeBG(image, imgList[indexImg])
 
+    # Detect hands on the background-removed image
+    hands, img = detector.findHands(imgOut, flipType=False)
+    
+    # Create a blank canvas for the keyboard
+    keyboard_canvas = np.zeros_like(img)
+    buttonList = []
+
+    # Create buttons for the virtual keyboard based on the keys list
+    for key in keys[0]:
+        buttonList.append(Button([30 + keys[0].index(key) * 105, 30], key))
+    for key in keys[1]:
+        buttonList.append(Button([30 + keys[1].index(key) * 105, 150], key))
+    for key in keys[2]:
+        buttonList.append(Button([30 + keys[2].index(key) * 105, 260], key))
+
+    # Draw the buttons on the keyboard canvas
+    for button in buttonList:
+        x, y = button.pos
+        cv2.rectangle(keyboard_canvas, (x, y), (x + button.size[0], y + button.size[1]), (255, 255, 255), -1)
+        cv2.putText(keyboard_canvas, button.text, (x + 20, y + 70), cv2.FONT_HERSHEY_PLAIN, 5, (0, 0, 0), 3)
+
+    # Handle input and gestures from detected hands
+    if hands:
+        for hand in hands:
+            lmList = hand["lmList"]
+            if lmList:
+                # Get the coordinates of the index finger tip (landmark 8)
+                x8, y8 = lmList[8][0], lmList[8][1]
+                for button in buttonList:
+                    bx, by = button.pos
+                    bw, bh = button.size
+                    # Check if the index finger is over a button
+                    if bx < x8 < bx + bw and by < y8 < by + bh:
+                        # Highlight the button and update the text
+                        cv2.rectangle(img, (bx, by), (bx + bw, by + bh), (0, 255, 0), -1)
+                        cv2.putText(img, button.text, (bx + 20, by + 70), cv2.FONT_HERSHEY_PLAIN, 5, (255, 255, 255), 3)
+                        # Update the output text in session_state
+                        session_state["output_text"] += button.text
+
+    # Corrected return: Create a video frame from the ndarray image
     return av.VideoFrame.from_ndarray(img, format="bgr24")
 
+
+
+
+
+
+
+
+
+
+
+
+# def video_frame_callback(frame: av.VideoFrame) -> av.VideoFrame:
+#     img = frame.to_ndarray(format="bgr24")
+#     hands, img = detector.findHands(img, flipType=False)
+
+#     # Render hand detection results
+#     if hands:
+#         hand = hands[0]
+#         bbox = hand["bbox"]
+#         cv2.rectangle(img, (bbox[0], bbox[1]), (255, 0, 0), 2)
+
+#     return av.VideoFrame.from_ndarray(img, format="bgr24")
+
 # Shared state for output text
 if "output_text" not in st.session_state:
     st.session_state["output_text"] = ""