Mask R-CNN for Fine-Grained segmentation
Project description
# Fine-Grained Segmentation
This is a project for fine-grained segmentation on 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)
## Requirements
Python 3.5, ONNX runtime, and other common packages listed in requirements.txt.
## Installation
Clone this repository
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 `
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
## Getting Started
[main.py](fine_grained_segmentation/main.py) detects and segments fashion items in an image
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