我有一个源图像（黑色背景和白色对象），我想从该图像中找到轮廓，创建一个具有黑色背景的新空白图像，并在该图像上一一绘制轮廓，就像它们在源图像中一样。我知道如何找到轮廓并创建空白图像，但我无法以与源图像中相同的方式绘制轮廓。我得到了一些结果，但颜色填充有时填充不正确或看起来不正确。我一直在考虑是否应该得到轮廓的倒数并填充它，但我不确定如何做到这一点或是否有可能。我基本上想做的就是在视频上一个一个地画出图像的形状。
这是我的代码。
import cv2
import numpy as np
import sys
import statistics as st
# Function to denoise images
def denoise(contours):
# Array that contains contours that will be removed
filtered_cont = []
sample = []
# Gathering sample
for contour in contours:
sample.append(len(contour))
# Calculating standard deviation
stdev = st.stdev(sample)
for contour in contours:
# Comparing contour length to standard deviation divided by 3
if len(contour) < stdev/3:
# Appending small contours to an array
filtered_cont.append(contour)
return filtered_cont
img = cv2.imread(sys.argv[1])
# Getting image dimensions
h,w,l = img.shape
size = (w,h)
gray_image=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
contours,hierarchy=cv2.findContours(gray_image,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
noisy_contours = denoise(contours)
# Filtering out noise
cv2.drawContours(img,noisy_contours,-1,color=(0,0,0),thickness=cv2.FILLED)
# Saving denoised image
cv2.imwrite('contours-denoised.png',img)
filtered=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edged=cv2.Canny(filtered,20,100)
# Creating blank black image
blank_image= np.zeros((h, w, 3), np.uint8)
# Finding contours from denoised image
contours,hierarchy=cv2.findContours(edged,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
# Sorting contours from large to small
contours.sort(key=len,reverse=True)
# Initializing video output
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
out = cv2.VideoWriter('project.mp4',fourcc, 10, size)
# Iterating through contours
for cont in contours:
# Drawing one contour and filling it with white
cv2.drawContours(blank_image, [cont], -1, color=(255, 255, 255), thickness=cv2.FILLED)
# Writing image into video stream
out.write(blank_image)
out.release()
# Saving image
cv2.imwrite('contours-denoised-drawn.png',blank_image)
