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.

Clone this repository

git clone git@github.com:UM-ARM-Lab/arm_segmentation.git

In an existing or new python virtual environment, install the dependencies
```
pip install -r requirements.txt
```

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

Metadata

Release files for arm-segmentation 0.0.8

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Source distribution for arm-segmentation 0.0.8
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Table of built distributions (wheels) for arm-segmentation 0.0.8
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arm_segmentation-0.0.8-py3-none-any.whl 13.4 kB Oct 19, 2023 Without provenance	Python 3	none	any	Details

Total release size: 24.9 kB

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Download URL	arm_segmentation-0.0.8.tar.gz
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Release files / arm_segmentation-0.0.8-py3-none-any.whl

Download URL	arm_segmentation-0.0.8-py3-none-any.whl
Size	13.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`6153b4e125086e4a800acb57951a39ca19380b3678000671a5c0a0a9558aaa79`
BLAKE2b-256 checksum How to use checksums	`22683d1d868cd52fad3e8261f015a27993ef41fa3454cf73a3aa2c2e0d51b677`
Upload date	Oct 19, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/4.0.2 CPython/3.11.6`

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