[Python Study Notes]行人检测

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# --------------------------------------------------------------
# @文件: 行人识别.py
# @工程: blog
# @时间: 2018/3/16 21:12
# @作者: liu yang
# @博客: liuyang1.club
# @邮箱: liuyang0001@outlook.com
# -------------------------------------------------------------
# 编码格式
# -*- coding: utf-8 -*-
# Python版本
# #!/usr/bin/python3import cv2def draw_detection(img, rects):
for x, y, w, h in rects:
pad_w, pad_h = int(0.05 * w), int(0.05 * h)
cv2.rectangle(img, (x + pad_w, y + pad_h), (x + w - pad_w, y + h - pad_h), (0, 255, 0), 2)def draw_alart(img, rects):
area = [0, 2]
size = img.shape
area_img = size[0] * size[1]
for x, y, w, h in rects:
area.append(w * h)
thresh = 0.25
if max(area) / area_img > thresh:
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img, "Incoming Peaple", (round(size[0] / 2) - 80, round(size[1] / 2) - 50),
font, 6, (0, 0, 255), 25)# 传入opencv里默认的参数
hog = cv2.HOGDescriptor()
# 得到行人的特征值
hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
# 调用摄像头，也可以传入一个路径视频文件
cap = cv2.VideoCapture(0)
while True:
# ret是一个表
# 循环读取每一帧的数据
ret, frame = cap.read()
# 扫描图像，如果检测不到进行缩小检测
found, w = hog.detectMultiScale(frame, 0, winStride=(8, 8), padding=(8, 8), scale=1.05)
draw_detection(frame, found)
draw_alart(frame, found)
# 显示每一帧的画面
cv2.imshow("pd", frame)
# 按q退出
key = cv2.waitKey(1) & 0xff
if key == ord('q'):
break# 运行结束后释放摄像头
cap.release()
cv2.destroyAllWindows()