}) with rasterio.open(opt.ctifdir + imname_P + '.tif', "w", **out_meta) as dest: dest.write(crop_image) dest = rasterio.open(opt.ctifdir + imname_P + '.tif') masked_image, mt = rasterio.mask.mask( dest, [feature["geometry"] for feature in transformed_gt]) mask = masked_image.mean(axis=0) mask[mask > 0] = 255 mask[mask < 255] = 0 Image.fromarray(mask.astype(np.uint8)).save(opt.B + '/' + imname_P + '.png', cmap=cm.gray) tifimg = crop_image tifimg = convertMbandstoRGB(tifimg, imname_P) savetif = tifimg savetif = np.transpose(savetif, (1, 2, 0)) sdsaveim(savetif, opt.A + '/' + imname_P + '.png') Pim_size = tifimg.shape MBANDIMG = rasterio.open(TIFim_M) crop_image_pband, ct = rasterio.mask.mask( MBANDIMG, [po['geometry'] for po in bb], crop=True) out_meta = MBANDIMG.meta.copy() out_meta.update({ "driver": "GTiff", "height": crop_image_pband.shape[1], "width": crop_image_pband.shape[2], "transform": ct })
print(Im2.meta) out_meta = Im1.meta.copy() out_meta.update({"count": out_meta["count"] + 1}) X = Im1.read() print(X.shape) GT = Im2.read() GT = GT[0:1, :, :] x1, y1 = np.where(GT[0, :, :] != 255) maxx = np.max(x1) + padding minx = np.min(x1) - padding maxy = np.max(y1) + padding miny = np.min(y1) - padding im = X[:, minx:maxx, miny:maxy] im = convertMbandstoRGB(im, file2) mask = GT[:, minx:maxx, miny:maxy] mask[mask != 255] = 1 mask[mask == 255] = 0 mask[mask == 1] = 255 print(im.shape) print(mask.shape) im = np.transpose(im, (1, 2, 0)) mask = np.transpose(mask, (1, 2, 0)) mask = np.squeeze(mask) sdsaveim(im, opt.A + file2.replace('.tif', '.png')) sdsaveim(mask, opt.B + file2.replace('.tif', '.png')) #X_and_GT = np.concatenate((X,GT),axis=0) #with rasterio.open( opt.resdir+file2,"w",**out_meta) as dest: