Question

我在树莓派中使用HOG（定向梯度直方图）进行人体检测，但它是如此缓慢，因此为了使其快速运行，我将运动检测与HOG一起使用。因此，如果有任何动作，该代码将从动作检测开始，将裁剪出该动作所在的部分，并将其输入到HOG中，以查看裁剪后的图像是否有人。但是我得到这个错误

    (rects, weights) = hog.detectMultiScale(gray_frame)
    cv2.error: OpenCV(3.4.3) /home/pi/packaging/opencv- 
    python/opencv/modules/core/src/matrix.cpp:423: error: (-215:Assertion 
    failed) 0 <= _rowRange.start && _rowRange.start <= _rowRange.end && 
    _rowRange.end <= m.rows in function 'Mat'

和

    Segmentation fault

这是我的代码：

from picamera.array import PiRGBArray
import picamera
import warnings
import datetime
import imutils
import time
import cv2
import numpy as np

client = None

camera = picamera.PiCamera()
camera.resolution = (368,240)
camera.framerate = 20
camera.rotation = 180
rawCapture = PiRGBArray(camera, size=(368,240))

hog = cv2.HOGDescriptor()
hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())

print("[INFO] warming up...")
time.sleep(2.5)
avg = None
for f in camera.capture_continuous(rawCapture, format="bgr", 
use_video_port=True):
    frame = f.array

    orig = frame.copy()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (21, 21), 0)
    if avg is None:

        avg = gray.copy().astype("float")
        rawCapture.truncate(0)
        continue

    cv2.accumulateWeighted(gray, avg, 0.5)
    frameDelta = cv2.absdiff(gray, cv2.convertScaleAbs(avg))

    thresh = cv2.threshold(frameDelta, 10, 255, cv2.THRESH_BINARY)[1]
    thresh = cv2.dilate(thresh, None, iterations=2)
    cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
        cv2.CHAIN_APPROX_SIMPLE)
    cnts = cnts[0] if imutils.is_cv2() else cnts[1]

    for c in cnts:
        if cv2.contourArea(c) < 2500:
            continue
        print("MOTION DETECTED")
        time.sleep(1)
        (x, y, w, h) = cv2.boundingRect(c)
        framea = frame[y:y+h, x:x+w]

        gray_frame = cv2.cvtColor(framea, cv2.COLOR_RGB2GRAY)
        (rects, weights) = hog.detectMultiScale(gray_frame)
        for i, (x, y, w, h) in enumerate(rects):
            if weights[i] < 0.7:
                continue
            cv2.rectangle(frame, (x,y), (x+w,y+h),(0,255,0),2) 
            print("*******WARNING******")               
        cv2.imshow("cropped image", framea)
        key = cv2.waitKey(1) & 0xFF
        if key == ord("q"):
            break

    cv2.imshow("Security Feed", frame)
    key = cv2.waitKey(1) & 0xFF
    if key == ord("q"):
        break
    rawCapture.truncate(0)

我认为问题出在裁剪部分，但是我现在不解决该问题

        (x, y, w, h) = cv2.boundingRect(c)
        framea = frame[y:y+h, x:x+w]

        gray_frame = cv2.cvtColor(framea, cv2.COLOR_RGB2GRAY)
        (rects, weights) = hog.detectMultiScale(gray_frame)

如何修复“分段故障”，运动检测+ HOG

0 个答案: