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centbueze/nigeria-sign-language1

Domain:

natural language processing

Record type:

project
Creator:
cen
Host:
Computer vision project for Nigeria Sign Language gesture recognition.(continuous) # Nigerian Sign Language (NSL) Recognition with YOLOv8 and ESP32-CAM This project recognizes **Nigerian Sign Language (NSL)** hand gestures using an **ESP32-CAM** for data collection and a **YOLOv8** model for training/inference. A **Flask web app** serves real-time predictions from the trained model. πŸ”— **Main Repository:** centbueze/nigeria-signs-lan… --- ## πŸ“Œ Project Overview - πŸ“· **Data Collection:** Images captured with **ESP32-CAM** (programmed via **Arduino IDE**). - πŸ“ **Annotation:** Labeled with LabelImg/Roboflow in **YOLO format**. - πŸ€– **Model Training:** Trained a **YOLOv8** model producing `best.pt`. - 🌍 **Deployment:** **Flask** API for real-time hand gesture recognition. - 🎯 **Goal:** Practical NSL recognition to support accessibility & inclusion. --- ## πŸ“‚ Repository Structure nigeria-signs-language/ │── app.py # Flask server (inference) │── requirements.txt # Python dependencies │── README.md │── .gitignore │── dataset/ # Optional: sample or link to dataset β”‚ β”œβ”€β”€ train/images/ train/labels/ β”‚ └── val/images/ val/labels/ │── output/ β”‚ └── nsl_yolo_train2/ β”‚ └── weights/ β”‚ └── best.pt # Trained YOLOv8 weights (provide or link) │── templates/ # Flask HTML (if UI is used) │── static/ # CSS/JS/assets (if UI is used) │── esp32_cam/ # Arduino sketches & notes (data collection) --- ## πŸ“œ requirements.txt (minimal) flask ultralytics opencv-python numpy torch torchvision --- ## 🧠 Model Path (important) from ultralytics import YOLO model_path = r"output/nsl_yolo_train2/weights/best.pt" model = YOLO(model_path) --- ## πŸ§ͺ Quick Inference (CLI) yolo predict model=output/nsl_yolo_train2/weights/best.pt source=0 # or yolo predict model=output/nsl_yolo_train2/weights/best.pt source="sample.jpg" --- ## 🎯 Training yolo detect train data=dataset/data.yaml model=yolov8n.pt epochs=50 imgsz=640 --- ## πŸ“„Dataset/data.yaml path: ./dataset train: train/images val: val/images nc: 26 names: [A, B, C, D, E, F, G, H, I, J, K, L …