Skip to main content

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](

The library is also available on the [Python Package Index](

A demo web app is up at

## 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 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](

## 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

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for fine-grained-segmentation, version 0.1.9
Filename, size File type Python version Upload date Hashes
Filename, size fine_grained_segmentation-0.1.9-py3-none-any.whl (15.7 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size fine_grained_segmentation-0.1.9.tar.gz (10.1 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page