# mask2bbox
[](https://pypi.org/project/mask2bbox/)
[](https://pypi.org/project/mask2bbox/)
[](https://pypi.org/project/mask2bbox/)
[](https://pypi.org/project/mask2bbox/)
[](https://github.com/schapirolabor/mask2bbox/actions)
For a given mask, gets the coordinates of bounding box of each element of the mask. It will also allow for more operations in the future.
## Installation
```bash
pip install mask2bbox
```
## CLI
```bash
isolate-cells -h
isolate-cells-from-file -h
get-average-iou -h
```
## Usage
```python
import numpy as np
from mask2bbox import BBoxes
# Create a BBoxes object
all_boxes = BBoxes.from_mask("path/to/mask.png")
# Expand the bounding boxes
all_boxes = all_boxes.expand(n=10)
# Remove the bounding boxes that are located on the edge of the image
all_boxes = all_boxes.remove_from_edge()
# Get the sides of all the bounding boxes
sides = all_boxes.get("sides")
# Filter the bounding boxes by the sides
filtered_boxes = all_boxes.filter("sides", np.greater_equal, (35, 35))
# Get the IoU matrix of all the bounding boxes
iou = filtered_boxes.iou_matrix()
# Save the overlapping pairs to
filtered_boxes.save_overlapping_pairs("path/to/save/overlapping_pairs.csv")
# Save the IOU matrix to a csv file
filtered_boxes.save_iou_matrix("path/to/save/iou_matrix.csv")
# Plot the bounding boxes on the mask image
filtered_boxes.draw(to="image", method="matplotlib", show="False", save="path/to/save/image.png")
# Save your bounding boxes
filtered_boxes.save_csv("path/to/bounding_boxes.csv")
# Get resize factors to resize the bounding boxes to a given size
resize_factors = filtered_boxes.de(desired_ratio=0.7, size=(256, 256))
# Extract the bounding boxes as images
filtered_boxes.extract(resize_factors, size=(256, 256), output="path/to/save/images")
```
## License
mask2bbox offers a dual licensing mode the [GNU Affero General Public License v3.0](LICENSE) - see [LICENSE](LICENSE) and [ESSENTIAL_LICENSE_CONDITIONS.txt](ESSENTIAL_LICENSE_CONDITIONS.txt)
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"description": "# mask2bbox\n[](https://pypi.org/project/mask2bbox/)\n[](https://pypi.org/project/mask2bbox/)\n[](https://pypi.org/project/mask2bbox/)\n[](https://pypi.org/project/mask2bbox/)\n[](https://github.com/schapirolabor/mask2bbox/actions)\n\nFor a given mask, gets the coordinates of bounding box of each element of the mask. It will also allow for more operations in the future.\n\n## Installation\n\n```bash\npip install mask2bbox\n```\n\n## CLI\n\n```bash\nisolate-cells -h\nisolate-cells-from-file -h\nget-average-iou -h\n```\n\n## Usage\n\n```python\nimport numpy as np\nfrom mask2bbox import BBoxes\n\n# Create a BBoxes object\nall_boxes = BBoxes.from_mask(\"path/to/mask.png\")\n\n# Expand the bounding boxes\nall_boxes = all_boxes.expand(n=10)\n\n# Remove the bounding boxes that are located on the edge of the image\nall_boxes = all_boxes.remove_from_edge()\n\n# Get the sides of all the bounding boxes\nsides = all_boxes.get(\"sides\")\n\n# Filter the bounding boxes by the sides\nfiltered_boxes = all_boxes.filter(\"sides\", np.greater_equal, (35, 35))\n\n# Get the IoU matrix of all the bounding boxes\niou = filtered_boxes.iou_matrix()\n\n# Save the overlapping pairs to\nfiltered_boxes.save_overlapping_pairs(\"path/to/save/overlapping_pairs.csv\")\n\n# Save the IOU matrix to a csv file\nfiltered_boxes.save_iou_matrix(\"path/to/save/iou_matrix.csv\") \n\n# Plot the bounding boxes on the mask image\nfiltered_boxes.draw(to=\"image\", method=\"matplotlib\", show=\"False\", save=\"path/to/save/image.png\")\n\n# Save your bounding boxes\nfiltered_boxes.save_csv(\"path/to/bounding_boxes.csv\")\n\n# Get resize factors to resize the bounding boxes to a given size\nresize_factors = filtered_boxes.de(desired_ratio=0.7, size=(256, 256))\n\n# Extract the bounding boxes as images\nfiltered_boxes.extract(resize_factors, size=(256, 256), output=\"path/to/save/images\")\n```\n\n## License\n\nmask2bbox offers a dual licensing mode the [GNU Affero General Public License v3.0](LICENSE) - see [LICENSE](LICENSE) and [ESSENTIAL_LICENSE_CONDITIONS.txt](ESSENTIAL_LICENSE_CONDITIONS.txt)\n",
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