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带有ORB的OpenCV中密集致残图生成

[英]Dense dispairity map generation in OpenCV with ORB

I am trying to generate a dense disparity map with OpenCV's ORB detectors. 我正在尝试使用OpenCV的ORB检测器生成密集的视差图。 I followed this tutorial and understand how it generates its disparity map. 我遵循了本教程,并了解了它如何生成视差图。

However, I don't understand how the code in the tutorial generates a dense disparity map because I cannot find any portion of the code that calculates the disparity of pixels that are not key points. 但是,我不理解本教程中的代码如何生成密集的视差图,因为我找不到代码的任何部分来计算不是关键点的像素的视差。

By replicating the code in the tutorial with Python, I got an accurate disparity map of only the pixels at the key point, but not the dense disparity map of the whole image, can anyone explain how did the tutorial find the dense disparity map of the whole image with the code? 通过使用Python复制本教程中的代码,我得到了仅关键点处像素的准确视差图,而不是整个图像的密集视差图,任何人都可以解释该教程如何找到该像素的密集视差图。整个图像与代码?

I hope this answers your question. 我希望这回答了你的问题。 All the pixels in the image are keypoints. 图像中的所有像素都是关键点。 The set of keypoints is initialized manually to contain all the pixels in the image. 手动初始化关键点集以包含图像中的所有像素。 This is done in the following lines copied from the website you refered to: 这是从您引用的网站复制的以下行中完成的:

for (int i = 0; i < img_left.cols; i++) {
    for (int j = 0; j < img_left.rows; j++) {
        kpl.push_back(KeyPoint(i,j,1));
        kpr.push_back(KeyPoint(i,j,1));
    }
}

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