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Merge pull request #7 from ksugar/dev
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v0.2.0 -> v0.3.0
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@ksugar
ksugar authored Jul 4, 2023
2 parents a6f77a9 + 8cf7c75 commit b41f3a9
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57 changes: 57 additions & 0 deletions .github/workflows/ci.yaml
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name: Build and upload to PyPI

on:
push:
branches:
- wheels
release:
types:
- published

jobs:
build:
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest, windows-latest, macos-latest]
python-version: ["3.9", "3.10", "3.11"]
poetry-version: [1.5.1]
name: ${{ matrix.os }} py${{ matrix.python-version }}
runs-on: ${{ matrix.os }}
steps:
- uses: actions/checkout@v2
- uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Run image
uses: abatilo/[email protected]
with:
poetry-version: ${{ matrix.poetry-version }}
- name: Install dependencies
run: poetry install

publish:
name: Upload to PyPI
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest]
python-version: [3.9, 3.10, 3.11]
poetry-version: [1.5.1]
runs-on: ${{ matrix.os }}
if: github.event_name == 'release' && github.event.action == 'published'
steps:
- uses: actions/checkout@v2
- uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Run image
uses: abatilo/[email protected]
with:
poetry-version: ${{ matrix.poetry-version }}
- name: Publish
env:
PYPI_TOKEN: ${{ secrets.PYPI_TOKEN }}
run: |
poetry config pypi-token.pypi $PYPI_TOKEN
poetry publish --build
2 changes: 1 addition & 1 deletion .gitignore
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Expand Up @@ -133,7 +133,7 @@ ipython_config.py
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock
poetry.lock

# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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21 changes: 21 additions & 0 deletions .vscode/launch.json
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{
// Use IntelliSense to learn about possible attributes.
// Hover to view descriptions of existing attributes.
// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
"version": "0.2.0",
"configurations": [
{
"name": "Python: FastAPI",
"type": "python",
"request": "launch",
"module": "uvicorn",
"args": [
"src.samapi.main:app",
"--host=0.0.0.0",
"--reload"
],
"jinja": true,
"justMyCode": false
}
]
}
54 changes: 52 additions & 2 deletions README.md
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Expand Up @@ -4,7 +4,7 @@

A web API for [SAM](https://github.com/facebookresearch/segment-anything) implemented with [FastAPI](https://fastapi.tiangolo.com).

This is a part of the following paper. Please [cite](#citation) it when you use this project. You will also cite [the original SAM paper](https://arxiv.org/abs/2304.02643).
This is a part of the following paper. Please [cite](#citation) it when you use this project. You will also cite [the original SAM paper](https://arxiv.org/abs/2304.02643) and [the MobileSAM paper](https://arxiv.org/abs/2306.14289).

- Sugawara, K. [*Training deep learning models for cell image segmentation with sparse annotations.*](https://biorxiv.org/cgi/content/short/2023.06.13.544786v1) bioRxiv 2023. doi:10.1101/2023.06.13.544786

Expand Down Expand Up @@ -48,6 +48,7 @@ export LD_LIBRARY_PATH=/usr/lib/wsl/lib:$LD_LIBRARY_PATH
### Launch a server

```bash
export PYTORCH_ENABLE_MPS_FALLBACK=1 # Required for running on Apple silicon
uvicorn samapi.main:app
```

Expand All @@ -64,6 +65,8 @@ For more information, see [uvicorn documentation](https://www.uvicorn.org/#comma

### Request body

#### Endpoint `/sam/`

```python
class SAMBody(BaseModel):
type: Optional[ModelType] = ModelType.vit_h
Expand All @@ -77,6 +80,47 @@ class SAMBody(BaseModel):
| bbox | Coordinate of a bbox `(x1, y1, x2, y2)` |
| b64img | Base64-encoded image data |

#### Endpoint `/sam/automask/`

```python
class SAMAutoMaskBody(BaseModel):
type: Optional[ModelType] = ModelType.vit_h
b64img: str
points_per_side: Optional[int] = 32
points_per_batch: int = 64
pred_iou_thresh: float = 0.88
stability_score_thresh: float = 0.95
stability_score_offset: float = 1.0
box_nms_thresh: float = 0.7
crop_n_layers: int = 0
crop_nms_thresh: float = 0.7
crop_overlap_ratio: float = 512 / 1500
crop_n_points_downscale_factor: int = 1
min_mask_region_area: int = 0
output_type: str = "Single Mask"
include_image_edge: bool = False
```

| key | value |
| ------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| type | One of `vit_h`, `vit_l`, or `vit_b`. |
| b64img | Base64-encoded image data. |
| points_per_side | The number of points to be sampled along one side of the image. The total number of points is points_per_side**2. |
| points_per_batch | Sets the number of points run simultaneously by the model. Higher numbers may be faster but use more GPU memory. |
| pred_iou_thresh | A filtering threshold in [0,1], using the model's predicted mask quality. |
| stability_score_thresh | A filtering threshold in [0,1], using the stability of the mask under changes to the cutoff used to binarize the model's mask predictions. |
| stability_score_offset | The amount to shift the cutoff when calculated the stability score. |
| box_nms_thresh | The box IoU cutoff used by non-maximal suppression to filter duplicate masks. |
| crop_n_layers | If >0, mask prediction will be run again on crops of the image. Sets the number of layers to run, where each layer has 2**i_layer number of image crops. |
| crop_nms_thresh | The box IoU cutoff used by non-maximal suppression to filter duplicate masks between different crops. |
| crop_overlap_ratio | Sets the degree to which crops overlap. In the first crop layer, crops will overlap by this fraction of the image length. Later layers with more crops scale down this overlap. |
| crop_n_points_downscale_factor | The number of points-per-side sampled in layer n is scaled down by crop_n_points_downscale_factor**n. |
| min_mask_region_area | If >0, postprocessing will be applied to remove disconnected regions and holes in masks with area smaller than min_mask_region_area. Requires opencv. |
| output_type | If 'Single Mask' is selected, the model will return single masks per prompt. If 'Multi-mask' is selected, the model will return three masks per prompt. 'Multi-mask (all)' keeps all three masks. One of the three masks is kept if the option 'Multi-mask (largest)', 'Multi-mask (smallest)', or 'Multi-mask (best quality)' is selected. |
| include_image_edge | If True, include a crop area at the edge of the original image. |

- [point_grids](https://github.com/facebookresearch/segment-anything/blob/6fdee8f2727f4506cfbbe553e23b895e27956588/segment_anything/automatic_mask_generator.py#L86-L88) is not supported.

### Response body

The response body contains a list of [GeoJSON Feature objects](https://geojson.org).
Expand Down Expand Up @@ -104,4 +148,10 @@ Please cite my paper on [bioRxiv](https://biorxiv.org/cgi/content/short/2023.06.
eprint = {https://www.biorxiv.org/content/early/2023/06/13/2023.06.13.544786.full.pdf},
journal = {bioRxiv}
}
```
```

## Acknowledgements

- [segment-anything](https://github.com/facebookresearch/segment-anything)
- [MobileSAM](https://github.com/ChaoningZhang/MobileSAM)
- [FastAPI](https://fastapi.tiangolo.com)
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