})
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: