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Hello @miguel-geo,
I think you are rights because rasterio reads images to shape (bands, rows, columns). I'll look at this in the code.
Thanks for your contribution.
While im trying to run the segment anything workflow. I ran into some issues.
TypeError: unhashable type: 'numpy.ndarray'
while trying to run the image_to_cloud function in the line :
if rgb not in unique_values:
my solution was
rgb=tuple(rgb)
.Another issue i was running into is when rearraring the array that rasterio returns when reading a tif.
image_rgb = image_rgb.reshape((image_rgb.shape[1], image_rgb.shape[2], image_rgb.shape[0]))
instead i use:
image_rgb = np.transpose(image_rgb, (1, 2, 0))
And finally in the part of the segment method:
the error was that most of the points didnt pass the if stament:
if not (0 <= pixel_x < image.shape[1]) or not (0 <= pixel_y < image.shape[0]):
because rasterio arrange width, height,bands different than the classic.
so i use
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