Added Image Segmentation which fixes #13516#13518
Added Image Segmentation which fixes #13516#13518NANDAGOPALNG wants to merge 8 commits intoTheAlgorithms:masterfrom
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require tests
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| os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1" | ||
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| def setup_device(): |
There was a problem hiding this comment.
Please provide return type hint for the function: setup_device. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function setup_device
| rng = np.random.default_rng(3) | ||
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| def show_mask(mask, ax, random_color=False, borders=True): |
There was a problem hiding this comment.
Please provide return type hint for the function: show_mask. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function show_mask
Please provide type hint for the parameter: mask
Please provide type hint for the parameter: ax
Please provide type hint for the parameter: random_color
Please provide type hint for the parameter: borders
| ax.imshow(mask_image) | ||
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| def show_points(coords, labels, ax, marker_size=375): |
There was a problem hiding this comment.
Please provide return type hint for the function: show_points. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function show_points
Please provide type hint for the parameter: coords
Please provide type hint for the parameter: labels
Please provide type hint for the parameter: ax
Please provide type hint for the parameter: marker_size
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| def show_box(box, ax): |
There was a problem hiding this comment.
Please provide return type hint for the function: show_box. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function show_box
Please provide type hint for the parameter: box
Please provide type hint for the parameter: ax
| ) | ||
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| def show_masks( |
There was a problem hiding this comment.
Please provide return type hint for the function: show_masks. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function show_masks
| return masks, scores | ||
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| def demonstrate_box_prompt(predictor, image): |
There was a problem hiding this comment.
Please provide return type hint for the function: demonstrate_box_prompt. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function demonstrate_box_prompt
Please provide type hint for the parameter: predictor
Please provide type hint for the parameter: image
| return masks, scores | ||
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| def demonstrate_combined_prompts(predictor, image): |
There was a problem hiding this comment.
Please provide return type hint for the function: demonstrate_combined_prompts. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function demonstrate_combined_prompts
Please provide type hint for the parameter: predictor
Please provide type hint for the parameter: image
| return masks, scores | ||
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| def demonstrate_batched_prompts(predictor, image): |
There was a problem hiding this comment.
Please provide return type hint for the function: demonstrate_batched_prompts. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function demonstrate_batched_prompts
Please provide type hint for the parameter: predictor
Please provide type hint for the parameter: image
| return masks, scores | ||
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| def demonstrate_batched_images(predictor): |
There was a problem hiding this comment.
Please provide return type hint for the function: demonstrate_batched_images. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function demonstrate_batched_images
Please provide type hint for the parameter: predictor
| plt.show() | ||
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| def main(): |
There was a problem hiding this comment.
Please provide return type hint for the function: main. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function main
for more information, see https://pre-commit.ci
There was a problem hiding this comment.
Click here to look at the relevant links ⬇️
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Repository:
Python:
Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.
algorithms-keeper commands and options
algorithms-keeper actions can be triggered by commenting on this PR:
@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
| os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1" | ||
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||
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|
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| def setup_device(): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function setup_device
Please provide return type hint for the function: setup_device. If the function does not return a value, please provide the type hint as: def function() -> None:
| rng = np.random.default_rng(3) | ||
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| def show_mask(mask, ax, random_color=False, borders=True): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function show_mask
Please provide return type hint for the function: show_mask. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: mask
Please provide type hint for the parameter: ax
Please provide type hint for the parameter: random_color
Please provide type hint for the parameter: borders
| ax.imshow(mask_image) | ||
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| def show_points(coords, labels, ax, marker_size=375): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function show_points
Please provide return type hint for the function: show_points. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: coords
Please provide type hint for the parameter: labels
Please provide type hint for the parameter: ax
Please provide type hint for the parameter: marker_size
| ) | ||
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| def show_box(box, ax): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function show_box
Please provide return type hint for the function: show_box. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: box
Please provide type hint for the parameter: ax
| ) | ||
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| def show_masks( |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function show_masks
Please provide return type hint for the function: show_masks. If the function does not return a value, please provide the type hint as: def function() -> None:
| return masks, scores | ||
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| def demonstrate_box_prompt(predictor, image): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function demonstrate_box_prompt
Please provide return type hint for the function: demonstrate_box_prompt. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: predictor
Please provide type hint for the parameter: image
| return masks, scores | ||
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| def demonstrate_combined_prompts(predictor, image): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function demonstrate_combined_prompts
Please provide return type hint for the function: demonstrate_combined_prompts. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: predictor
Please provide type hint for the parameter: image
| return masks, scores | ||
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| def demonstrate_batched_prompts(predictor, image): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function demonstrate_batched_prompts
Please provide return type hint for the function: demonstrate_batched_prompts. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: predictor
Please provide type hint for the parameter: image
| return masks, scores | ||
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| def demonstrate_batched_images(predictor): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function demonstrate_batched_images
Please provide return type hint for the function: demonstrate_batched_images. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: predictor
| plt.show() | ||
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| def main(): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file computer_vision/image_segmentation_sam2.py, please provide doctest for the function main
Please provide return type hint for the function: main. If the function does not return a value, please provide the type hint as: def function() -> None:
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1 participant
Describe your change:
This project demonstrates text-driven image segmentation using Meta's Segment Anything Model 2 (SAM 2). The implementation focuses on converting various input prompts (points, boxes) into precise object segmentation masks.
can you assign me this under Hacktoberfest 2025
Checklist: