【Python+OpenCV】實現檢測場景內是否有物體移動,並進行人臉檢測抓拍
阿新 • • 發佈:2019-01-05
可以當個家庭安防用吧0.0
import cv2
import time
save_path = './face/'
face_cascade = cv2.CascadeClassifier('./cascades/haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('./cascades/haarcascade_eye.xml')
camera = cv2.VideoCapture(0) # 引數0表示第一個攝像頭
# 判斷視訊是否開啟
if (camera.isOpened()):
print ('Open')
else:
print('攝像頭未開啟')
# 測試用,檢視視訊size
size = (int(camera.get(cv2.CAP_PROP_FRAME_WIDTH)),
int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT)))
print('size:'+repr(size))
fps = 5 # 幀率
pre_frame = None # 總是取視訊流前一幀做為背景相對下一幀進行比較
i = 0
while True:
start = time.time()
grabbed, frame_lwpCV = camera.read () # 讀取視訊流
gray_lwpCV = cv2.cvtColor(frame_lwpCV, cv2.COLOR_BGR2GRAY) # 轉灰度圖
if not grabbed:
break
end = time.time()
# 人臉檢測部分
faces = face_cascade.detectMultiScale(gray_lwpCV, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(frame_lwpCV, (x, y), (x + w, y + h), (255 , 0, 0), 2)
roi_gray_lwpCV = gray_lwpCV[y:y + h / 2, x:x + w] # 檢出人臉區域後,取上半部分,因為眼睛在上邊啊,這樣精度會高一些
roi_frame_lwpCV = frame_lwpCV[y:y + h / 2, x:x + w]
cv2.imwrite(save_path + str(i) + '.jpg', frame_lwpCV[y:y + h, x:x + w]) # 將檢測到的人臉寫入檔案
i += 1
eyes = eye_cascade.detectMultiScale(roi_gray_lwpCV, 1.03, 5) # 在人臉區域繼續檢測眼睛
for (ex, ey, ew, eh) in eyes:
cv2.rectangle(roi_frame_lwpCV, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
cv2.imshow('lwpCVWindow', frame_lwpCV)
# 運動檢測部分
seconds = end - start
if seconds < 1.0 / fps:
time.sleep(1.0 / fps - seconds)
gray_lwpCV = cv2.resize(gray_lwpCV, (500, 500))
# 用高斯濾波進行模糊處理,進行處理的原因:每個輸入的視訊都會因自然震動、光照變化或者攝像頭本身等原因而產生噪聲。對噪聲進行平滑是為了避免在運動和跟蹤時將其檢測出來。
gray_lwpCV = cv2.GaussianBlur(gray_lwpCV, (21, 21), 0)
# 在完成對幀的灰度轉換和平滑後,就可計算與背景幀的差異,並得到一個差分圖(different map)。還需要應用閾值來得到一幅黑白影象,並通過下面程式碼來膨脹(dilate)影象,從而對孔(hole)和缺陷(imperfection)進行歸一化處理
if pre_frame is None:
pre_frame = gray_lwpCV
else:
img_delta = cv2.absdiff(pre_frame, gray_lwpCV)
thresh = cv2.threshold(img_delta, 25, 255, cv2.THRESH_BINARY)[1]
thresh = cv2.dilate(thresh, None, iterations=2)
image, contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for c in contours:
if cv2.contourArea(c) < 1000: # 設定敏感度
continue
else:
print("咦,有什麼東西在動0.0")
break
pre_frame = gray_lwpCV
key = cv2.waitKey(1) & 0xFF
# 按'q'健退出迴圈
if key == ord('q'):
break
# When everything done, release the capture
camera.release()
cv2.destroyAllWindows()
手動打碼,啊哈哈哈啊哈
本文運動檢測部分參考自:這裡作者用樹莓派在家裡衛生間檢測有人進入,然後播放音樂,哈哈哈啊哈,太好玩了