解释readNetFromCaffe的forward方法返回的值

问题描述

net = cv2.dnn.readNetFromCaffe(prototxt,model)
detections = net.forward()

检测将具有形状为（1、1、200、7）的4D阵列。有什么不同的值？

    for i in range(0,detections.shape[2]):
        confidence = detections[0,i,2]

上面的循环在第3维获得置信度值，条件是行数和第4维是列数，因此很明显，检测到的对象具有如此高的置信度或概率。但是我不明白其他参数。

        box = detections[0,3:7] * np.array([w,h,w,h])

要创建一个框，上面的代码用于3到6列及其值。那么第2列到第6列中的这些值是什么？

下面的代码可重现值...

from imutils.video import VideoStream
import imutils
import numpy as np
import cv2
import argparse
import time

# construct the argument parser
ap = argparse.ArgumentParser()
ap.add_argument("-p","--prototxt",required=True,help="path to caffe deploy prototxt file")
ap.add_argument("-m","--model",help="path to pre-trained caffe model")
ap.add_argument("-c","--confidence",type=float,default=0.5,help="minimum confidence required")
args = vars(ap.parse_args())

# MODEL - load the model which will be used to predict
print("[INFO] loading model...")
net = cv2.dnn.readNetFromCaffe(args["prototxt"],args["model"])

# INPUT - start video to capture frames
print("[INFO] starting video stream...")
vs = VideoStream(src=0).start()
# vs = VideoStream(usePiCamera=True).start()  # this is to stream video for Raspberry Pi camera
# vs = FileVideoStream(path='/path to file')  # this is to get video content from file
time.sleep(2)  # allow the cam to warm up

# for live streaming,while loop will be required to capture frames
while True:
    frame = vs.read()
    frame = imutils.resize(frame,width=400)

    # get the dimensions of the frame
    print('shape of frame:',frame.shape)
    (h,w) = frame.shape[:2]

    # blob the frame
    blob = cv2.dnn.blobFromImage(frame,scalefactor=1.0,size=(300,300),mean=(104.0,177.0,123.0))

    # use the blob for detection
    net.setInput(blob)
    detections = net.forward()
    print(detections)
    # loop over the detections
    for i in range(0,2]
        if confidence < args['confidence']:
            continue

        # create box
        box = detections[0,h])
        (startX,startY,endX,endY) = box.astype("int")

        # draw the box on the face
        text = "{:.2f}%".format(confidence * 100)
        y = startY - 10 if startY - 10 > 10 else startY + 10
        cv2.rectangle(frame,(startX,startY),(endX,endY),(0,255,0),thickness=2)
        cv2.putText(frame,text,y),cv2.FONT_HERSHEY_SIMPLEX,0.45,255),2)

    # show on screen
    cv2.imshow("frame",frame)
    if cv2.waitKey(1) & 0xFF == 27:
        break

cv2.destroyAllWindows()
vs.stop()

解决方法

第一列代表它所属的类id 第二列代表置信度值，通过与置信度阈值进行比较，帧中是否有任何对象 [3:7] 即 3,4,5,6 列表示在对象周围创建框的坐标/点，它们存储为 numpy 数组，因此要转换为 int 类型以制作框。