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how do i resolve the error in the code below "When there is only a single output, the loss_weights argument must be a Python float. Received instead: loss_weights=[0.5] of type <class 'list'>" I AM USING A CODE FROM https://github.com/bnsreenu/python_for_microscopists/blob/master/251_satellite_image_to_maps_translation/251_pix2pix_maps.py https://github.com/bnsreenu/python_for_microscopists/blob/master/252_generating_realistic_scientific_images_using_pix2pix/252_pix2pix_sandstone.py But i am using it with my images. I still get the same error. I tried using both png and tiff images on spyder...

A key technique in image editing applications is determining the dominant colors. The identification of these dominant colors is essential for creating an image's palette, which, in turn, accurately reflects the effect of selected tools and the results of editing. This article will delve into how to determine an image's palette within a restricted color space, identify an image's dominant colors, and differentiate between...

I have a set of points [x,y] representing edge of a road and i want to find a way to represent the curve or sharpness of turn of that road. In the image above, I need to find curve of the road edge marked in green. Example points: [[180 11] [191 11] [199 12] [192 12] [206 13] [200 13] [208 14] [207 14]...

i am using BRISK to extract feature from remote sensing images but the extracted feature are not right the result the code on matlab is as follows: original1 = imread('im1.tif'); ptsOriginalBRISK1 = detectBRISKFeatures(original1,'MinContrast',0.01,'MinQuality',0.7); [featuresO1,validPtsO1] = extractFeatures(original1,ptsOriginalBRISK1); distorted1 = imread('im2.tif'); ptsDistortedBRISK1 = detectBRISKFeatures(distorted1,'MinContrast',0.01,'MinQuality',0.7); [featuresD1,validPtsD1] = extractFeatures(distorted1,ptsDistortedBRISK1); Pairs11 = matchFeatures(featuresO1,featuresD1,'MatchThreshold',90,'MaxRatio',0.9); matchedO = validPtsO1(Pairs11(:,1)); matchedD = validPtsD1(Pairs11(:,2)); [tform, inlierDistorted,inlierOriginal] = estimateGeometricTransform(matchedD,matchedO,'similarity'); figure showMatchedFeatures(original1,distorted1,inlierOriginal,inlierDistorted,'montage') title('Matching points (inliers only)')...