Python OpenCV人脸识别视频卡顿 跳帧优化后不显示识别框如何解决

• 第一，帧率间隔逻辑写错：你原本想实现每10帧处理1次，但是代码里写的是count%(10*fps) == 0，fps是摄像头每秒帧率，一般默认是30，这就变成每300帧（也就是10秒）才处理1次，自然很难看到标注
• 第二，识别结果没有缓存：你仅在处理帧的时候给当前帧画标注，剩下9帧都是新读取的原始画面，没有复用之前的识别结果画框，所以非处理帧不会显示任何标注

1. 修正间隔判断逻辑，改为每10帧处理1次：把if count%(10*fps) == 0改成if count % 10 == 0
2. 新增变量缓存上一次识别到的人脸位置、匹配姓名列表，每次处理帧更新缓存，所有帧都用缓存的结果绘制标注
3. 可以根据需要调整间隔帧数，比如改成每5帧处理一次，平衡流畅度和识别实时性

import cv2
import os
import face_recognition

KNOWN_FACES_DIR = 'known_faces'
TOLERANCE = 0.5
FRAME_THICKNESS = 3
FONT_THICKNESS = 2
MODEL = 'hog'  # 可选'cnn'，有CUDA加速时性能更好

video = cv2.VideoCapture(0)
fps = int(video.get(cv2.CAP_PROP_FPS))

print('Loading known faces...')
known_faces = []
known_names = []

for name in os.listdir(KNOWN_FACES_DIR):
    for filename in os.listdir(f'{KNOWN_FACES_DIR}/{name}'):
        image = face_recognition.load_image_file(f'{KNOWN_FACES_DIR}/{name}/{filename}')
        encoding = face_recognition.face_encodings(image)[0]
        known_faces.append(encoding)
        known_names.append(name)
        

def check_face(known_faces, known_names):
    count = 0
    # 新增缓存变量，保存上一次识别的人脸位置和对应姓名
    last_face_info = []
    
    while True:
        ret, image = video.read()
        if not ret:
            break
        
        if count % 10 == 0:       # 每10帧处理一次识别
            current_face_info = []
            locations = face_recognition.face_locations(image, model=MODEL)
            encodings = face_recognition.face_encodings(image, locations)
        
            for face_encoding, face_location in zip(encodings, locations):
                results = face_recognition.compare_faces(known_faces, face_encoding, TOLERANCE)
                match = None
                if True in results:
                    match = known_names[results.index(True)]
                    print(f"Match found: {match}")
                # 把识别到的位置和姓名存入临时列表
                current_face_info.append((face_location, match))
            # 更新缓存
            last_face_info = current_face_info
        
        # 所有帧都用缓存的人脸信息画标注
        for face_location, match in last_face_info:
            if match is None:
                continue
            # 画人脸框
            top_left = (face_location[3], face_location[0])
            bottom_right = (face_location[1], face_location[2])
            color = [0,255,0]
            cv2.rectangle(image, top_left, bottom_right, color, FRAME_THICKNESS)
            # 画姓名标签
            top_left = (face_location[3], face_location[2])
            bottom_right = (face_location[1], face_location[2] + 22)
            cv2.rectangle(image, top_left, bottom_right, color, cv2.FILLED)
            cv2.putText(image, match, (face_location[3] + 10, face_location[2] + 15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (200, 200, 200), FONT_THICKNESS)
    
        count += 1                    
    
        # 显示画面
        cv2.imshow("", image)
        if cv2.waitKey(1) & 0xFF == ord("q"):
            cv2.destroyAllWindows()
            break

check_face(known_faces, known_names)

如果人物移动速度快，觉得标注滞后明显，可以把间隔帧数从10调低到5~8，兼顾流畅度和标注跟随性。

内容的提问来源于stack exchange，提问作者user572575