Python程序：调用电脑摄像头同时识别摄像头中心处的颜色、二维码以及画面中存在的字符串、手势、人脸、物体的形状

import cv2
import numpy as np
import pyzbar.pyzbar as pyzbar
import mediapipe as mp
import pytesseract
import webbrowser

# 初始化MediaPipe解决方案
mp_hands = mp.solutions.hands
mp_face_detection = mp.solutions.face_detection
mp_drawing = mp.solutions.drawing_utils

hands = mp_hands.Hands(max_num_hands=4)
face_detection = mp_face_detection.FaceDetection(min_detection_confidence=0.5)

# 颜色范围定义 (HSV颜色空间)
COLOR_RANGES = {
    "red":    ([0, 100, 100], [10, 255, 255]),
    "green":  ([40, 40, 40],  [80, 255, 255]),
    "blue":   ([100, 100, 50], [140, 255, 255]),
    "yellow": ([20, 100, 100], [40, 255, 255]),
    "black":  ([0, 0, 0],      [180, 255, 30]),
    "white":  ([0, 0, 200],    [180, 30, 255])
}

def detect_color(hsv_img):
    center = hsv_img.shape[0]//2, hsv_img.shape[1]//2
    radius = 5
    roi = hsv_img[center[1]-radius:center[1]+radius, 
                 center[0]-radius:center[0]+radius]
    mean_hsv = np.mean(roi, axis=(0,1))
    
    for color, (lower, upper) in COLOR_RANGES.items():
        if (mean_hsv >= np.array(lower)).all() and (mean_hsv <= np.array(upper)).all():
            return color
    return "unknown"

def detect_shape(cnt):
    peri = cv2.arcLength(cnt, True)
    approx = cv2.approxPolyDP(cnt, 0.04 * peri, True)
    
    if len(approx) == 3:
        return "triangle"
    elif len(approx) == 4:
        x, y, w, h = cv2.boundingRect(approx)
        aspect_ratio = w / float(h)
        return "square" if 0.95 <= aspect_ratio <= 1.05 else "rectangle"
    elif len(approx) == 5:
        return "pentagon"
    elif 6 <= len(approx) <= 8:
        return "circle"
    return "polygon"

def detect_gesture(hand_landmarks):
    tip_ids = [4, 8, 12, 16, 20]
    fingers = []
    
    # Thumb
    if hand_landmarks.landmark[tip_ids[0]].x < hand_landmarks.landmark[tip_ids[0]-1].x:
        fingers.append(1)
    else:
        fingers.append(0)
    
    # Other fingers
    for id in range(1,5):
        if hand_landmarks.landmark[tip_ids[id]].y < hand_landmarks.landmark[tip_ids[id]-2].y:
            fingers.append(1)
        else:
            fingers.append(0)
    
    count = fingers.count(1)
    if count == 0:
        return "fist"
    elif count == 5:
        return "open hand"
    return f"finger_{count}"

cap = cv2.VideoCapture(0)

# 界面布局参数
INFO_PANEL_WIDTH = 300
TEXT_COLOR = (255, 255, 255)
PANEL_COLOR = (50, 50, 50)

while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        break
    
    # 创建信息面板
    info_panel = np.zeros((frame.shape[0], INFO_PANEL_WIDTH, 3), dtype=np.uint8)
    info_panel[:] = PANEL_COLOR
    
    # QR Code检测
    decoded = pyzbar.decode(frame)
    if decoded:
        url = decoded[0].data.decode()
        webbrowser.open(url)
    
    # 颜色识别
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    color = detect_color(hsv)
    
    # 形状检测
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    blurred = cv2.GaussianBlur(gray, (5,5), 0)
    edges = cv2.Canny(blurred, 50, 150)
    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    
    detected_shapes = []
    for cnt in contours:
        if cv2.contourArea(cnt) < 1000:
            continue
        shape = detect_shape(cnt)
        x,y,w,h = cv2.boundingRect(cnt)
        detected_shapes.append(shape)
        cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 2)
        cv2.putText(frame, shape, (x, y+h+20), 
                   cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0,255,0), 2)
    
    # 手势识别
    gesture = "none"
    rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    results = hands.process(rgb)
    if results.multi_hand_landmarks:
        for hand_landmarks in results.multi_hand_landmarks:
            mp_drawing.draw_landmarks(frame, hand_landmarks, mp_hands.HAND_CONNECTIONS)
            gesture = detect_gesture(hand_landmarks)
    
    # 人脸检测
    face_count = 0
    rgb_face = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    results_faces = face_detection.process(rgb_face)
    if results_faces.detections:
        face_count = len(results_faces.detections)
        for detection in results_faces.detections:
            mp_drawing.draw_detection(frame, detection)
    
    # 文字识别
    gray_text = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    data = pytesseract.image_to_data(gray_text, output_type=pytesseract.Output.DICT)
    
    detected_text = []
    for i in range(len(data['text'])):
        if int(data['conf'][i]) > 40:
            x,y,w,h = data['left'][i], data['top'][i], data['width'][i], data['height'][i]
            text = data['text'][i].strip()
            if text:
                detected_text.append(text)
                cv2.rectangle(frame, (x,y), (x+w,y+h), (255,0,0), 2)
                cv2.putText(frame, text, (x, y+h+15), 
                          cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255,0,0), 2)
    
    # 更新信息面板
    y_offset = 20
    cv2.putText(info_panel, f"Color: {color}", (10, y_offset), 
               cv2.FONT_HERSHEY_SIMPLEX, 0.6, TEXT_COLOR, 1)
    y_offset += 40
    cv2.putText(info_panel, f"Gesture: {gesture}", (10, y_offset), 
               cv2.FONT_HERSHEY_SIMPLEX, 0.6, TEXT_COLOR, 1)
    y_offset += 40
    cv2.putText(info_panel, f"Faces: {face_count}", (10, y_offset), 
               cv2.FONT_HERSHEY_SIMPLEX, 0.6, TEXT_COLOR, 1)
    y_offset += 40
    cv2.putText(info_panel, "Shapes detected:", (10, y_offset), 
               cv2.FONT_HERSHEY_SIMPLEX, 0.6, TEXT_COLOR, 1)
    y_offset += 30
    for shape in set(detected_shapes):
        cv2.putText(info_panel, f"- {shape}", (10, y_offset), 
                   cv2.FONT_HERSHEY_SIMPLEX, 0.5, TEXT_COLOR, 1)
        y_offset += 25
    y_offset += 20
    cv2.putText(info_panel, "Text detected:", (10, y_offset), 
               cv2.FONT_HERSHEY_SIMPLEX, 0.6, TEXT_COLOR, 1)
    y_offset += 30
    for text in set(detected_text):
        cv2.putText(info_panel, f"- {text}", (10, y_offset), 
                   cv2.FONT_HERSHEY_SIMPLEX, 0.5, TEXT_COLOR, 1)
        y_offset += 25
    
    # 合并主画面和信息面板
    combined = np.hstack((frame, info_panel))
    
    cv2.imshow('Multi Detection System', combined)
    
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()