SAMYOL 1.0.4

Combines YOLO models and SAM

======= SAMYOL

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🤔 What is this?

SAMYOL is a Python library that combines an object detection model and a segmentation model. It provides a unified interface for performing object detection and segmentation tasks using different versions of the YOLO model (YOLOv6, YOLOv7, YOLOv8, or YOLO-NAS) and the Segment Anything Model (SAM).

🧩 Features

• Integrated object detection and segmentation capabilities
• Support for multiple versions of the YOLO model
• Flexible input options for image paths
• Easy-to-use interface for obtaining object detection predictions and segmentation masks

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⏳ Quick Installation

SAMYOL is installed using pip.

This python library requires python>=3.11, as well as pytorch>=1.7.0 and torchvision>=0.8.1. Installing both PyTorch and TorchVision with CUDA support is strongly recommended. We will also need the models checkpoints. These will be installed automatically if they are not already installed.

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Install SAMYOL:

pip install SAMYOL

or

conda install SAMYOL -c conda-forge

or

pip install git+https://github.com/Jawher-Ben-Abdallah/SAMYOL.git

or clone the repository locally and install

git clone [e-mail]:Jawher-Ben-Abdallah/SAMYOL.git cd segment-anything; pip install -e .

🚀 Getting Started

The following notebook has detailed examples and usage instructions for each YOLO model:

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💁 Contributing

As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation. For detailed information on how to contribute, see here <https://github.com/Jawher-Ben-Abdallah/SAMYOL/blob/main/CONTRIBUTING.md>_