python - 如何修复项目中的 openCV cvtColor 错误？

Question

我正在构建手写识别项目，但cvtColor在尝试将图像从BGR2HSV.

cap = cv2.VideoCapture(0)
Lower_blue = np.array([110, 50, 50])
Upper_blue = np.array([130, 255, 255])
pred_class = 0
pts = deque(maxlen = 512)
blackboard = np.zeros((480, 640, 3), dtype = np.uint8)
digit = np.zeros((200, 200, 3), dtype = np.uint8)
while(cap.isOpened()):
    ret, img = cap.read()
    img = cv2.flip(img, 1)
    imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(imgHSV, Lower_blue, Upper_blue)
    blur = cv2.medianBlur(mask, 15)
    blur = cv2.GaussianBlur(blur, (5, 5), 0)
    thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY +   cv2.THRESH_OTSU)[1]
    cnts = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[1]
    center = None
    if len(cnts) >= 1:
        contour = max(cnts, key = cv2.contourArea)
        if cv2.contourArea(contour) > 250:
            ((x, y), radius) = cv2.minEnclosingCircle(contour)
            cv2.circle(img, (int(x), int(y)), int(radius), (0, 255, 255), 2)
            cv2.circle(img, center, 5, (0, 255, 255), -1)
            M = cv2.moments(contour)
            center = (int(M['m10'] / M['m00']), int(M['m01'] / M['m00']))
            pts.appendleft(center)
            for i in range (1, len(pts)):
                if pts[i - 1] is None or pts[i] is None:
                    continue
                cv2.line(blackboard, pts[i - 1], pts[i], (255, 255, 255), 10)
                cv2.line(img, pts[i - 1], pts[i], (0, 0,255), 5)
    elif len(cnts) == 0:
        if len(pts) != []:
            blackboard_gray = cv2.cvtColor(blackboard, cv2.COLOR_BGR2GRAY)
            blur1 = cv2.medianBlur(blackboard_gray, 15)
            blur1 = cv2.GaussianBlur(blur1, (5, 5), 0)
            thresh1 = cv2.threshold(blur1, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
            blackboard_cnts = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[1]
            if len(blackboard_cnts) >= 1:
                cnt = max(blackboard_cnts, key = cv2.contourArea)
                print(cv2.contourArea(cnt))
                if cv2.contourArea(cnt) > 2000:
                    x, y, w, h = cv2.boundingRect(cnt)
                    digit = blackboard_gray[y:y + h, x:x + w]
                    #new Image = process_letter(digit)
                    pred_probab, pred_class = keras_predict(model1, digit)
                    print(pred_class, pred_probab)

            pts = deque(maxlen = 512)
            blackboard = np.zeros((480, 640, 3), dtype = uint8)
        cv2.putText(img, "Conv Network : " + str(letter_count    [pred_class]), (10, 470),
                cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
        cv2.imshow("Frame", img)
        cv2.imshow("Contours", thresh)

        k = cv2.waitkey(10)
        if k == 27:
            break

如何解决这个 OpenCV 错误问题？请帮忙！

我收到以下错误：

error: OpenCV(3.4.1) C:\Miniconda3\conda-bld\opencv-suite_1533128839831\work\modules\imgproc\src\color.cpp:11214: error: (-215) (scn == 3 || scn == 4) && (depth == 0 || depth == 5) in function cv::cvtColor

标签： pythonpython-3.xopencvmachine-learning

Answer 1

我认为以下错误：error: (-215) (scn == 3 || scn == 4) && (depth == 0 || depth == 5) in function cv::cvtColor是因为相机无法正确捕获帧。通过打印ret值进行检查。它相机能够正确捕获帧，它将返回True，否则False。发生上述错误是因为None已传递给cv2.cvtColor函数。您可以使用以下代码作为安全检查：

if ret is True:
   # your code goes here
else:
   break

此外，请考虑以下几点：

• 它是cv2.waitKey(10), 不是cv2.waitkey(10)[大写 'K']
• cv2.findContours函数返回3值（即图像、轮廓和层次结构），OpenCV 3.x但仅返回2值（即轮廓、层次结构）openCV 4.x
• len(pts) != []没有意义。在这里，您试图将一个数字与一个空列表进行比较。将其更改为len(pts) != 0.
• letter_countcv2 里面有什么。putText功能。请重新检查一下。
• 代替在and的情况下重新初始化 deque( pts = deque(maxlen = 512)) ，您可以通过简单地使用清除它来使用旧的。只是一个想法！len(cnts)==0len(pts) != 0ptspts.clear()

• 另外，在最后添加以下代码：

  cap.release() 
  cv2.destroyAllWindows() 
  

试试下面的修改代码（使用测试openCV v4.0.0）：

import cv2
import numpy as np
from collections import deque

cap = cv2.VideoCapture(0)
Lower_blue = np.array([110, 50, 50])
Upper_blue = np.array([130, 255, 255])
pred_class = 0
pts = deque(maxlen = 512)
blackboard = np.zeros((480, 640, 3), dtype = np.uint8)
digit = np.zeros((200, 200, 3), dtype = np.uint8)

while(cap.isOpened()):
    ret, img = cap.read()
    img = cv2.flip(img, 1)
    imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(imgHSV, Lower_blue, Upper_blue)
    blur = cv2.medianBlur(mask, 15)
    blur = cv2.GaussianBlur(blur, (5, 5), 0)
    thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY +   cv2.THRESH_OTSU)[1]
    cnts = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[0]
    center = None
    if len(cnts) >= 1:
        contour = max(cnts, key = cv2.contourArea)
        if cv2.contourArea(contour) > 250:
            ((x, y), radius) = cv2.minEnclosingCircle(contour)
            cv2.circle(img, (int(x), int(y)), int(radius), (0, 255, 255), 2)
            cv2.circle(img, center, 5, (0, 255, 255), -1)
            M = cv2.moments(contour)
            center = (int(M['m10'] / M['m00']), int(M['m01'] / M['m00']))
            pts.appendleft(center)
            # print(pts)
            for i in range (1, len(pts)):
                if pts[i - 1] is None or pts[i] is None:
                    print("Continue")
                    continue
                cv2.line(blackboard, pts[i - 1], pts[i], (255, 255, 255), 10)
                cv2.line(img, pts[i - 1], pts[i], (0, 0,255), 5)
            cv2.imshow("Frame", img)
            cv2.imshow("Contours", thresh)

            # press q to stop
            if cv2.waitKey(1) & 0xFF == ord('q'):
                break

    else:
        if len(pts) != 0:
            blackboard_gray = cv2.cvtColor(blackboard, cv2.COLOR_BGR2GRAY)
            blur1 = cv2.medianBlur(blackboard_gray, 15)
            blur1 = cv2.GaussianBlur(blur1, (5, 5), 0)
            thresh1 = cv2.threshold(blur1, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
            print('Hello')
            blackboard_cnts = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[0]
            if len(blackboard_cnts) >= 1:
                cnt = max(blackboard_cnts, key = cv2.contourArea)
                print(cv2.contourArea(cnt))
                if cv2.contourArea(cnt) > 2000:
                    x, y, w, h = cv2.boundingRect(cnt)
                    digit = blackboard_gray[y:y + h, x:x + w]
                    #new Image = process_letter(digit)
                    #pred_probab, pred_class = keras_predict(model1, digit)
                    print(digit.shape)

            #pts = deque(maxlen = 512)
            pts.clear()
            blackboard = np.zeros((480, 640, 3), dtype = np.uint8)
            #cv2.putText(img, "Conv Network : " + str(letter_count[pred_class]), (10, 470), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
            cv2.putText(img, "Conv Network :", (10, 470), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)

            cv2.imshow("Frame", img)
            cv2.imshow("Contours", thresh)

            if cv2.waitKey(1) & 0xFF == ord('q'):
                break

cap.release()
cv2.destroyAllWindows()