Welcome to our furniture segmentation project, where we leverage the cutting-edge capabilities of YOLOv8m, combined with the data management and augmentation powers of Roboflow, to accurately identify and segment various furniture items in images. This project aims to facilitate applications in interior design, e-commerce, and augmented reality, among others.
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Furniture Detection: Accurately detect multiple furniture categories within an image.
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Segmentation: Percise segmentation of each detected furniture item.
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Efficiency: Optimized for both speed and accuracy, making it suitable for real-time applications.
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Dataset Management: Utilization of Roboflow for dataset augmentation and preprocessing, ensuring robust model performance.
What things you need to install the software and how to install them:
python >= 3.8
torch
roboflow
ultralytics > 1.08You can install the required Python packages using:
pip install -r requirements.txtA step-by-step series of commands that tells you how to get a development environment running.
Clone the repository:
git clone https://github.com/maher-mohsen/Furniture-Segmentation.gitNavigate into the project directory:
cd Furniture-Segmentation\ModelInstall the dependencies:
pip install -r requirements.txtInstructions on how to train the model, including any specific settings or parameters used.
python train.py --img 640 --epochs 1 --model yolov8m.ptInstructions on how to run the model to segment furniture in new images.
python run_model.py --model yolov8x-seg.pt --image sample.jpg
- Maher Mohsen maher-mohsen
- Hat tip to anyone whose code was used
- This project presented for El-Jamel Architecture
You can find online Streamlit demo here
