Update app.py

app.py

@@ -1,34 +1,23 @@
-import streamlit as st
 import cv2
-import numpy as np
-from PIL import Image
+from streamlit_webrtc import VideoTransformerBase, webrtc_streamer
 
-# 创建一个摄像头捕捉函数
-def capture_camera():
-    cap = cv2.VideoCapture(0)  # 参数0表示默认摄像头
-    if not cap.isOpened():
-        st.error("无法打开摄像头")
-        return None, None
-    ret, frame = cap.read()
-    cap.release()
-    if not ret:
-        st.error("无法从摄像头获取图像")
-        return None, None
-    return frame, cap
+faceCascade = cv2.CascadeClassifier(cv2.haarcascades+'haarcascade_frontalface_default.xml')
 
-def main():
-    st.title("摄像头拍照应用")
 
-    # 添加一个按钮用于拍照
-    if st.button("打开摄像头拍照"):
-        frame, cap = capture_camera()
-        if frame is not None:
-            # 转换颜色从BGR到RGB
-            frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-            # 将图像显示在Streamlit界面上
-            st.image(frame, use_column_width=True, caption="捕捉到的图像")
+class VideoTransformer(VideoTransformerBase):
+    def __init__(self):
+        self.i = 0
 
-    st.text("点击上方按钮打开摄像头并拍照。")
+    def transform(self, frame):
+        img = frame.to_ndarray(format="bgr24")
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        faces = faceCascade.detectMultiScale(gray, 1.3, 5)
+        i =self.i+1
+        for (x, y, w, h) in faces:
+            cv2.rectangle(img, (x, y), (x + w, y + h), (95, 207, 30), 3)
+            cv2.rectangle(img, (x, y - 40), (x + w, y), (95, 207, 30), -1)
+            cv2.putText(img, 'F-' + str(i), (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 0), 2)
 
-if __name__ == "__main__":
-    main()
+        return img
+
+webrtc_streamer(key="example", video_transformer_factory=VideoTransformer)