Update app.py

app.py

@@ -1,36 +1,17 @@
 import gradio as gr
 import cv2
-from gradio_webrtc import WebRTC
 import mediapipe as mp
-import time
 
 # 初始化 MediaPipe Hands
 mp_hands = mp.solutions.hands
 mp_drawing = mp.solutions.drawing_utils
-hands = mp_hands.Hands(min_detection_confidence=0.3, min_tracking_confidence=0.3)  # 降低置信度提升速度
-
-# WebRTC 配置
-rtc_configuration = {
-    "iceServers": [{"urls": "stun:stun.l.google.com:19302"}],
-    "iceTransportPolicy": "relay"
-}
+hands = mp_hands.Hands(min_detection_confidence=0.3, min_tracking_confidence=0.3)
 
 # 手势检测函数
-last_process_time = time.time()  # 用于控制处理频率
-
 def detection(image, conf_threshold=0.5):
     """
     使用 MediaPipe Hands 进行手势检测。
     """
-    global last_process_time
-    current_time = time.time()
-    
-    # 只每隔一定时间（比如0.1秒）才进行一次处理，减少计算负载
-    if current_time - last_process_time < 0.1:
-        return image  # 如果时间间隔太短，则直接返回原图像
-
-    last_process_time = current_time
-
     # 将图像从 BGR 转换为 RGB（MediaPipe 需要 RGB 格式）
     image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
 
@@ -58,7 +39,7 @@ with gr.Blocks(css=css) as demo:
     gr.HTML(
         """
         <h1 style='text-align: center'>
-        Hand Gesture Detection with MediaPipe (Powered by WebRTC ⚡️)
+        Hand Gesture Detection with MediaPipe
         </h1>
         """
     )
@@ -71,7 +52,7 @@ with gr.Blocks(css=css) as demo:
     )
     with gr.Column(elem_classes=["my-column"]):
         with gr.Group(elem_classes=["my-group"]):
-            image = WebRTC(label="Stream", rtc_configuration=rtc_configuration)
+            image = gr.Image(label="Upload Image")  # 使用图像上传代替 WebRTC 流
             conf_threshold = gr.Slider(
                 label="Confidence Threshold",
                 minimum=0.0,