Question

我训练了Darkflow来检测5个自定义objetcts，现在我想发出一个仅在检测到对象时发出蜂鸣声的警报（5类中的任何对象）。因此，我需要有关在暗流代码中进行更改的信息。如果您可以帮助一段示例代码，那将更有帮助。从darkflow.net.build导入TFNet 导入cv2 将numpy导入为np 导入imutils cap = cv2.VideoCapture（'rtsp：// admin：123456@192.168.226.201：554 / profile1'）

options = {'model': 'cfg/tiny-yolo-voc-5c.cfg','load': 118800, 
'threshold': 0.7, 'gpu': 1.0}

tfnet = TFNet(options)

while True:
    ret, frame = cap.read()
    #frame = cv2.resize(frame,(720,480))
    frame = imutils.resize(frame, width=600)
    #cv2.imshow('frame',frame)
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(gray,(5,5),0)
    edges = cv2.Canny(blur,100,200)
    th3 = cv2.adaptiveThreshold(edges,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINA RY,11,2)
    contours,_ = cv2.findContours(th3, cv2.RETR_TREE, 
    cv2.CHAIN_APPROX_SIMPLE)
    height, width = edges.shape
    min_x, min_y = width, height
    max_x = max_y = 0
    for cnt in contours:
        area = cv2.contourArea(cnt)
        # if area < 10000 and area > 13000:
        #       continue
        (x,y,w,h) = cv2.boundingRect(cnt)
        min_x, max_x = min(x, min_x), max(x+w, max_x)     #if (w< 400 and w>300) and (h<400 and w>300):
        min_y, max_y = min(y, min_y), max(y+h, max_y)
        #if (w< 670 and w>50) and (h <670 and w>50):
        #roi = frame[y:y+h, x:x+w]
        result = tfnet.return_predict(frame)            
        for elem in result:
            top_x, top_y = elem["topleft"]["x"], elem["topleft"]["y"] 
            bot_x, bot_y = elem["bottomright"]["x"] , elem["bottomright"]["y"] 

            cv2.rectangle(frame,(top_x,top_y),(bot_x,bot_y),(0,0,255),2)    
            cv2.putText(frame, elem["label"], (top_x-10, top_y- 
   10),cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), 1, cv2.LINE_AA)
        cv2.imshow('roi',frame)
        #cv2.imshow('frame',frame)          
        key = cv2.waitKey(30)
        if key == ord('q'):
            break

cap.release()
cv2.destroyAllWindows()

使用Darkflow检测到特定物体时如何发出警报

0 个答案: