人体识别是一种计算机视觉技术,通过图像或视频分析来检测、跟踪和识别人体。它通常涉及以下几个步骤:
原因:
解决方法:
原因:
解决方法:
import cv2
import numpy as np
# 加载预训练的人体检测模型
net = cv2.dnn.readNetFromCaffe("deploy.prototxt", "res10_300x300_ssd_iter_140000.caffemodel")
def detect_people(frame):
(h, w) = frame.shape[:2]
blob = cv2.dnn.blobFromImage(cv2.resize(frame, (300, 300)), 1.0, (300, 300), (104.0, 177.0, 123.0))
net.setInput(blob)
detections = net.forward()
for i in range(0, detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence > 0.5:
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(startX, startY, endX, endY) = box.astype("int")
cv2.rectangle(frame, (startX, startY), (endX, endY), (0, 255, 0), 2)
return frame
# 打开摄像头
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
if not ret:
break
frame = detect_people(frame)
cv2.imshow("Frame", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
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