- Clone the repository:
git clone https://github.com/poran-dip/odstream.git- Navigate into the project directory:
cd odstream- Navigate to the frontend directory:
cd frontend- Install frontend dependencies:
npm install- Start the frontend dev server:
npm run dev- Open a separate terminal window/tab and go to the backend directory:
cd backend- Create a virtual environment:
python -m venv venv
venv\Scripts\activate # or source venv/bin/activate on macOS/Linux- Install Python dependencies:
pip install -r requirements.txt- Install additional binaries:
python setup.py- Run the Flask backend:
python app.pyEnsure the Flask server runs on the expected port (typically 5000) and is accessible to the frontend.
Close the servers by killing the terminals or by pressing Ctrl + C.
pip install ultralyticsSet your YOLO_MODEL_PATH to new Ultralytics YOLO models such as 'models/yolov8n.pt' or 'models/yolov5nu.pt'.
- Clone the YOLOv5 repository:
cd backend
venv\Scripts\activate
git clone https://github.com/ultralytics/yolov5.git
pip install -r yolov5/requirements.txt-
Place your custom-trained
.ptmodel inbackend/models/. -
Update
YOLO_MODEL_PATHinconfig.pyto point to it.
cd frontend
npm run devcd backend
venv\Scripts\activate
python app.pyMake sure you're working on a separate feature branch and pulling latest changes before pushing.
- Stage changes:
git add .- Commit with a descriptive message:
git commit -m "your commit message"- Push to the correct branch:
git push -u origin [your-branch-name]git branchgit checkout branch-namegit pullgit remote add origin https://github.com/poran-dip/odstream.git