yolov5 Valve detector

This project provides a containerized environment to seamlessly run PyTorch and YOLO for deep learning tasks. Our setup ensures compatibility and ease of deployment across various systems.

Overview

We start with a Dockerfile that sets up an environment with all necessary dependencies for PyTorch and YOLO, ensuring stability and reproducibility. This approach allows users to bypass the complexities of configuring dependencies and focus on developing and training models.

Features

• Ready-to-use Dockerfile: Streamlined for PyTorch and YOLO usage.
• Dependency Management: Automatically installs all required libraries and dependencies.
• System Compatibility: Ensures a consistent environment across different machines.

Run within the Docker

clone yolov5

git clone git@github.com:ultralytics/yolov5.git

cd yolov5

pip install -r requirements.txt

Sample command

python detect.py --weights runs/train/exp/weights/best.pt --img 640 --source /path/to/images