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Mask R-CNN for Fine-Grained segmentation

Project description

# fine-grained-segmentation library

Python library for segmenting clothing items in images, implemented in Python 3 and ONNX. A deep learning model generates bounding boxes and segmentation masks for each instance of an object in the image. It’s based on [Matterport Mask R-CNN](https://github.com/matterport/Mask_RCNN)

The library is also available on the [Python Package Index](https://pypi.org/project/fine-grained-segmentation/)

A demo web app is up at https://fine-grained-segmentation.vinnypalumbo.com

## Requirements

Python 3.5, ONNX runtime, and other common packages listed in requirements.txt.

## Installation

  1. Clone this repository
  2. Run setup to install the library `bash python3 setup.py install ` If it failed to install the dependencies, run `bash pip3 install -r requirements.txt `
  3. Download pre-trained weights (mrcnn.onnx) from the [releases page](https://github.com/vinny-palumbo/fine_grained_segmentation/releases)

## Usage

Here is how to use the library from the command line: `bash fashion-segmentator --image=<path/to/image/file> ` This will generate a `result.png` file in the current directory

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