Python OpenCV发现RGBA图像的轮廓不起作用

输入图像为Contours_X.png[Contors_X.png:PNG图像数据，819 x 1154，8位灰度，非隔行扫描]:

从Python Find Contours white region only OpenCV个代码中窃取代码:

import cv2 as cv
import numpy as np

def generate_X_Y(image_path):
    
    image = cv.imread(image_path)
    
    # image = cv.imread(image_path, cv.IMREAD_UNCHANGED)
    
    cv.imwrite("image_ori.png" , image)
    
    print('image[0] : ', image[0])
    
    gray = cv.cvtColor(image, cv.COLOR_RGBA2GRAY)
    
    print('gray[0] : ', gray[0])
    
    ## CHANGED TO:
    ret, thresh = cv.threshold(gray, 128, 255, cv.THRESH_BINARY_INV)
    
    cv.imwrite("image2.png", thresh)
    
    contours, hierarchies = cv.findContours(thresh, cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)
    blank = np.zeros(thresh.shape[:2], dtype='uint8')
    cv.drawContours(blank, contours, -1, (255, 0, 0), 1)
    cv.imwrite("Contours.png", blank)
    
    print('len(contours) : ' , len(contours))
    
    for i in contours:
        
        cv.drawContours(image, [i], -1, (0, 255, 0), 2)
        
    cv.imwrite("image.png", image)
    

if __name__ == '__main__':
    
    image_path = 'Contours_X.png'  # Provide the correct path in Colab
    
    # image_path = 'input_alpha.png' 
    
    generate_X_Y(image_path)

我得到输出image.png[Image.png:PNG图像数据，819 x 1154，8位/彩色RGB，非隔行扫描 ]:

使用input_alpha_2.png[Input_Alpha_2.png:PNG图像数据，input_alpha_2.png0 x 1200，8位/彩色RGBA，非隔行扫描]:

和代码:

import cv2 as cv
import numpy as np


def generate_X_Y(image_path):
    
    # image = cv.imread(image_path)
    
    image = cv.imread(image_path, cv.IMREAD_UNCHANGED)
    
    cv.imwrite("image_ori.png" , image)
    
    print('image[0] : ', image[0])
    
    gray = cv.cvtColor(image, cv.COLOR_RGBA2GRAY)
    
    print('gray[0] : ', gray[0])
    
    ## CHANGED TO:
    ret, thresh = cv.threshold(gray, 128, 255, cv.THRESH_BINARY_INV)
    
    cv.imwrite("image2.png", thresh)
    
    contours, hierarchies = cv.findContours(thresh, cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)
    blank = np.zeros(thresh.shape[:2], dtype='uint8')
    cv.drawContours(blank, contours, -1, (255, 0, 0), 1)
    cv.imwrite("Contours.png", blank)
    
    print('len(contours) : ' , len(contours))
    
    for i in contours:
        
        cv.drawContours(image, [i], -1, (0, 255, 0), 20)
        

    cv.imwrite("image.png", image)
    

if __name__ == '__main__':
    
    # image_path = 'Contours_X.png'  # Provide the correct path in Colab
    
    image_path = 'input_alpha_2.png' 
    
    generate_X_Y(image_path)

我得到image.png[Image.png:PNG图像数据，image.png0 x 1200，8位/彩色RGBA，非隔行扫描]:

为什么我不像第一个例子那样在主题周围画一个漂亮的绿色边框？

正如 comments 中所建议的:

您的基本BGR图像(在Alpha通道下)具有您的绿色线条.Alpha通道正在覆盖它).移除Alpha通道以查看它.

并做到这一点:

cv.imwrite("image.png", image[:,:,:3])

我得到image.png: PNG image data, 1000 x 1200, 8-bit/color RGBA, non-interlaced分:

但我仍然不明白透明的Alpha通道如何隐藏轮廓，为什么我会得到灰色背景，我相信这可能是我图像中最大轮廓的区域，即方形外部黑色边框？

有关这方面的更多信息，请使用:

cntsSorted = sorted(contours, key = lambda x: cv.contourArea(x) , reverse=True)
    
for index , i in enumerate(cntsSorted) :
        
    print(cv.contourArea(i))
        
    if index > 0 :

        cv.drawContours(image, [i], -1, (0, 255, 0), 20)
  
cv.imwrite("image.png", image)    

cv.imwrite("image_rem.png", image[:,:,:3])
    

第二幅图像没有更多的外部绿色边框，但仍然保持深灰色背景.