Metadata-Version: 2.1
Name: arm-segmentation
Version: 0.0.8
Summary: Training and inference of instance segmentation
Author-email: Peter Mitrano <pmitrano@umich.edu>
Maintainer-email: Peter Mitrano <pmitrano@umich.edu>
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: torch
Requires-Dist: torchvision
Requires-Dist: pycocotools
Requires-Dist: numpy
Requires-Dist: matplotlib
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'

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This repository contains very simple training, inference, and visualization code for instance segmentation.
This is a good choice for when you don't want to get into the details and just want a model that works well and is cheap
and fast (compared to services like AWS)

# Data

This repository assumes you have used RoboFlow to annotate your dataset.
You should export your dataset as a COCO style dataset, which stores annotations in JSON.

# Installation & Setup

You can install via pip
```
pip install arm_segmentation
```

Or you can clone the source code and install it that way.

1. Clone this repository
   ```
   git clone git@github.com:UM-ARM-Lab/arm_segmentation.git
   ```
2. In an existing or new python virtual environment, install the dependencies
    ```
    pip install -r requirements.txt
    ```
3. Train
    ```
    # You may need export PYTHONPATH=./src, or you can try pip install -e .
    ./scripts/train.py path_to_dataset
    ./scripts/visualize_validation.py path_to_dataset
   ```
