ONNX and OpenVINO Compatible Yolact Model

The yolact model is a simple, fully convolutional model for real-time instance segmentation
YOLACT is an acronym for "You Only Look At CoefficienTs," which reflects the core philosophy behind this state-of-the-art real-time instance segmentation model
It leverages the openvino and onnx frameworks for inference.
Currently, only the image inference functionality is operational.
After the conversion process, refactoring the remaining parts becomes easier.

Installation and Issue Resolution

To explore the original model or download the pretrained weights visit the Yolact GitHub Repo.
For OpenVino installation issues and further details, please refer to the OpenVino GitHub Repo.

You Only Look At CoefficienTs

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      ╚██╔╝  ██║   ██║██║     ██╔══██║██║        ██║   
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       ╚═╝    ╚═════╝ ╚══════╝╚═╝  ╚═╝ ╚═════╝   ╚═╝

Installation

Clone this repository and enter it:

git clone https://github.com/Abdullah-Elkasaby/yolact-isntance-segmentation-openvino.git
cd 238-yolact-image-segmentation

Set up the environment using one of the following methods:
- Using Anaconda
  - Run conda env create -f environment.yml
- Manually with pip
  - Set up a Python3 environment (e.g., using virtenv).
  - Install Pytorch 1.0.1 (or higher) and TorchVision.
  - Install some other packages:
```
# Cython needs to be installed before pycocotools
pip install cython
pip install opencv-python pillow pycocotools matplotlib 
```