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Add README and environment files
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README.md

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# SegmentAnything for Microscopy
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## Installation and Requirements
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Tools for segmentation and tracking in microscopy build on top of [SegmentAnything](https://segment-anything.com/).
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We implement napari applications for:
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- interactive 2d segmentation
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- interactive 3d segmentation
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- interactive tracking of 2d image data
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Install [PyTorch](https://pytorch.org/get-started/locally/), [SegmentAnything](https://github.com/facebookresearch/segment-anything#installation) and elf in your conda env.
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Then install the `micro_sam` library via
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**Early beta version**
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This is an early beta version. Any feedback is welcome, but please be aware that the functionality is evolving fast and not fully tested.
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## Functionality overview
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TODO
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## Installation
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You need to install [PyTorch](https://pytorch.org/get-started/locally/), [SegmentAnything](https://github.com/facebookresearch/segment-anything#installation), [napari](https://napari.org/stable/) and [elf](https://github.com/constantinpape/elf).
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We recommend to use conda and provide two conda environment files with all necessary requirements:
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- `environment_gpu.yaml`: sets up an environment with GPU support.
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- `environment_cpu.yaml`: sets up an environment with CPU support.
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You can create the corresponding environment via
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```
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conda env create -f <ENV_FILE>.yaml
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```
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You can then activate the environment via
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```
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conda activate sam
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```
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And install our napari applications and the `micro_sam` library via
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```
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pip install -e .
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```
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## Structure
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## Usage
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TODO
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### Tips & Tricks
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TODO
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## Using the micro_sam library
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TODO
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## Contributing
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```
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micro_sam <- library with utility functionality for using SAM for microscopy data
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/sam_annotator <- the napari plugins for annotation
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```
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## Citation
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If you are using this repository in your research please cite
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- [SegmentAnything](https://arxiv.org/abs/2304.02643)
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- and our repository on [zenodo](TODO) (we are working on a full publication)

environment_cpu.yaml

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channels:
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- pytorch
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- conda-forge
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name:
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sam
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dependencies:
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- cpuonly
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- napari
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- python-elf
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- pytorch
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- torchvision
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- tqdm
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- pip:
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- git+https://github.com/facebookresearch/segment-anything.git

environment_gpu.yaml

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channels:
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- pytorch
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- nvidia
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- conda-forge
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name:
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sam
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dependencies:
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- napari
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- python-elf
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- pytorch
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- pytorch-cuda>=11.7 # you may need to update the cuda version to match your system
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- torchvision
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- tqdm
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- pip:
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- git+https://github.com/facebookresearch/segment-anything.git

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