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Thanks for the PR! As mentioned in #32 I'll be able to look over this and merge within a few days. |
LandingEllipse
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LandingEllipse
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Thanks again for your interest in SLDTk! I've looked at the pull request and added some comments/feedback. Mostly I'm interested in conserving support for uint8 images, which is easily achievable by moving towards fraction based arguments and adapting ranges on the fly based on the treated image's dtype.
I've changed the status to "request changes" in case you'd like to make the tweaks yourself (or continue the discussion); if not I'd be happy to do so myself, just let me know. I'd of course be happy to add you as a contributor when your pull request is accepted.
Cheers,
Ariel
| "profile.") | ||
| ap.add_argument("-t", "--threshold", | ||
| type=_uint8, | ||
| type=int, |
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Type too broad. e.g. "-1337" would be a valid threshold which, assuming by 16-bit we're talking about uint16, is not desirable. If support for uint8 is to be kept (see below), I propose threshold and bias arguments are converted to fractions to remain agnostic of a given image's dtype.
| disk = (disk / flat) * bias | ||
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| img[d_y-d_r:d_y+d_r, d_x-d_r:d_x+d_r] = np.clip(disk, 0, 255).round() | ||
| img[d_y-d_r:d_y+d_r, d_x-d_r:d_x+d_r] = np.clip(disk, 0, 2**16 - 1).round() |
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Want to use np.iinfo(img.dtype).max in place of hardcoded values to conserve support for uint8 images.
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| blur = cv2.GaussianBlur(img, (5, 5), 0) | ||
| mask = cv2.inRange(blur, threshold, 255) | ||
| mask = cv2.inRange(blur, threshold, 2**16 - 1) |
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Want to use np.iinfo(img.dtype).max in place of hardcoded values to conserve support for
| "threshold": 10, | ||
| "slices": 1000, | ||
| "bias": 175, | ||
| "bias": 44975, |
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Should be converted to a fraction as per comment for helpers.py
| paths = generate_output_paths(args) | ||
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| image = cv2.imread(args['image']) | ||
| image = cv2.imread(args['image'], -1) |
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Please use explicit constants instead of integer values for flags, i.e. cv2.IMREAD_UNCHANGED in this case.
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I created a new branch adding support for 16bit images