OpenCV BodyPix掩模
我试图在图像上画一个遮罩,遮罩是body pix(在NodeJS中)处理的结果。出于性能原因,我想使用OpenCV来绘制遮罩,而不是htmlcanvaOpenCV BodyPix掩模,opencv,bodypix,Opencv,Bodypix,我试图在图像上画一个遮罩,遮罩是body pix(在NodeJS中)处理的结果。出于性能原因,我想使用OpenCV来绘制遮罩,而不是htmlcanva const segmentation = await net.segmentPersonParts(img, { flipHorizontal: false, internalResolution: 'medium', segmentationThreshold: 0.7 });
const segmentation = await net.segmentPersonParts(img, {
flipHorizontal: false,
internalResolution: 'medium',
segmentationThreshold: 0.7
});
//Mask into opencv Mat
const segmentationMask = new cv.Mat(segmentation.data, segmentation.height, segmentation.width, cv.CV_8UC4);
const mask = segmentationMask.cvtColor(cv.COLOR_BGRA2BGR);
//Application of mask
const result = mat.bitwiseAnd(mask);
cv.imwrite('mask.jpg', mask);
cv.imwrite('result.jpg', result);
这项工作非常完美,并实现了在检测到的人身上绘制黑色面具(语义分割)的预期结果。但是SegmentPersonParts
比SegmentPerson
方法慢得多,我希望使用最后一种方法。问题是,面具不起作用。执行以下操作时:
const segmentation = await net.segmentPerson(img, {
flipHorizontal: false,
internalResolution: 'medium',
segmentationThreshold: 0.7
});
//Mask into opencv Mat
const segmentationMask = new cv.Mat(segmentation.data, segmentation.height, segmentation.width, cv.CV_8UC4);
const mask = segmentationMask.cvtColor(cv.COLOR_BGRA2BGR);
//Application of mask
const result = mat.bitwiseAnd(mask);
cv.imwrite('mask.jpg', mask);
cv.imwrite('result.jpg', result);
结果只是一个黑色图像,因为遮罩没有正确构建。如何解决这个问题?我有一个脚本,可以使用OpenCV Python在图像中实现这一点:
import cv2
def pixelate(image):
# Get input size
height, width, _ = image.shape
# Desired "pixelated" size
h, w = (16, 16)
# Resize image to "pixelated" size
temp = cv2.resize(image, (w, h), interpolation=cv2.INTER_LINEAR)
# Initialize output image
return cv2.resize(temp, (width, height), interpolation=cv2.INTER_NEAREST)
# Load image
image = cv2.imread('1.png')
# ROI bounding box coordinates
x,y,w,h = 122,98,283,240
# Extract ROI
ROI = image[y:y+h, x:x+w]
# Pixelate ROI
pixelated_ROI = pixelate(ROI)
# Paste pixelated ROI back into original image
image[y:y+h, x:x+w] = pixelated_ROI
cv2.imshow('pixelated_ROI', pixelated_ROI)
cv2.imshow('image', image)
cv2.waitKey()
您需要获取边界框
坐标,并在ROI
上使用它