Update app.py

app.py

@@ -1,21 +1,19 @@
 import logging
 import queue
-from pathlib import Path
 from typing import List, NamedTuple
-import mediapipe as mp
 import av
 import cv2
 import numpy as np
 import streamlit as st
 from streamlit_webrtc import WebRtcMode, webrtc_streamer
-from sample_utils.download import download_file
 from sample_utils.turn import get_ice_servers
 from cvzone.HandTrackingModule import HandDetector
 from cvzone.SelfiSegmentationModule import SelfiSegmentation
 import os
 import time
 
-# logger = logging.getLogger(_name_)
+# Logger Setup
+logger = logging.getLogger(__name__)
 
 # Streamlit settings
 st.set_page_config(page_title="Virtual Keyboard", page_icon="🏋️")
@@ -23,9 +21,8 @@ st.title("Interactive Virtual Keyboard")
 st.subheader('''Turn on the webcam and use hand gestures to interact with the virtual keyboard.
 Use 'a' and 'd' from the keyboard to change the background.''')
 
-
 # Initialize modules
-detector = HandDetector(maxHands=1, detectionCon=0.8)
+detector = HandDetector(maxHands=1, detectionCon=0.85)
 segmentor = SelfiSegmentation()
 
 # Define virtual keyboard layout
@@ -46,40 +43,42 @@ class Detection(NamedTuple):
 
 result_queue: "queue.Queue[List[Detection]]" = queue.Queue()
 
+# Load background images
 listImg = os.listdir('model/street') if os.path.exists('model/street') else []
 if not listImg:
     st.error("Error: 'street' directory is missing or empty. Please add background images.")
     st.stop()
 else:
-    imgList = [cv2.imread(f'model/street/{imgPath}') for imgPath in listImg if cv2.imread(f'model/street/{imgPath}') is not None]
+    imgList = [cv2.imread(f'model/street/{imgPath}') for imgPath in listImg]
+    imgList = [img for img in imgList if img is not None]
 
 indexImg = 0
-prev_key_time = [time.time()] * 2
 output_text = ""
 
 if "output_text" not in st.session_state:
     st.session_state["output_text"] = ""
 
+# Video Frame Callback
 def video_frame_callback(frame: av.VideoFrame) -> av.VideoFrame:
     global indexImg, output_text
 
     img = frame.to_ndarray(format="bgr24")
-    hands = detector.findHands(img, draw=False)
+    hands, img = detector.findHands(img, draw=True)
 
     detections = []
     if hands:
-        for i, hand in enumerate(hands):
-            lmList = hand['lmList']
+        for hand in hands:
             bbox = hand['bbox']
             label = "Hand"
             score = hand['score']
             box = np.array([bbox[0], bbox[1], bbox[0] + bbox[2], bbox[1] + bbox[3]])
-    detections.append(Detection(label=label, score=score, box=box))
-    cv2.imshow('WebCam with Virtual Keyboard', img)
+            detections.append(Detection(label=label, score=score, box=box))
+
     result_queue.put(detections)
     st.session_state["output_text"] = output_text
     return av.VideoFrame.from_ndarray(img, format="bgr24")
 
+# WebRTC Streamer
 webrtc_streamer(
     key="virtual-keyboard",
     mode=WebRtcMode.SENDRECV,
@@ -88,6 +87,3 @@ webrtc_streamer(
     video_frame_callback=video_frame_callback,
     async_processing=True,
 )
-
-            
-