{"id":31642289,"url":"https://github.com/ashishgoswami13/handgesture_recognition","last_synced_at":"2026-04-18T15:39:49.825Z","repository":{"id":311771251,"uuid":"1044954321","full_name":"ashishgoswami13/handgesture_recognition","owner":"ashishgoswami13","description":"Real-time hand gesture recognition using computer vision and deep learning. 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It is designed to collect gesture data, train a model, and perform live gesture classification, which can be used for applications such as drone control or human-computer interaction.\n\n--- \n\n## Folder Structure \u0026 File Explanations\n\n### data_collection\n- **datacollection.py**\n  - Used to collect hand gesture images from a webcam.\n  - Saves images into gesture-specific folders (e.g., `back/`, `down/`, etc.) for dataset creation.\n  - Helps build a labeled dataset for training the recognition model.\n\n- **test.py**\n  - Loads the trained model from the `Model/` folder.\n  - Uses the webcam to detect and classify hand gestures in real-time.\n  - Detects a hand, preprocesses the image, and predicts the gesture using the trained model.\n\n- **Gesture Folders** (`back/`, `down/`, `Go forward/`, `land/`, `left/`, `right/`, `stop/`, `up/`)\n  - Contain images of hands showing different gestures.\n  - Used for training and testing the recognition model.\n\n### Model/\n- **keras_model.h5**\n  - The trained Keras model for hand gesture recognition.\n  - Used by `test.py` to classify gestures.\n\n- **labels.txt**\n  - Contains the list of gesture labels corresponding to the model’s output classes.\n  - Used to map model predictions to human-readable gesture names.\n\n--- \n\n## How It Works\n1. **Data Collection**: Run `datacollection.py` to capture images of different hand gestures and save them in the respective folders.\n2. **Model Training**: (Not included here, but typically you would train a model using the collected images and save it as `keras_model.h5`.)\n3. **Gesture Recognition**: Run `test.py` to use your webcam for live gesture recognition using the trained model.\n   \n--- \n\n## Requirements\n- Python 3.x\n- OpenCV (`cv2`)\n- cvzone\n- numpy\n- Keras\n  \n---\n\n## Usage\n1. Install dependencies:\n   ```bash\n   pip install opencv-python cvzone numpy keras\n   ```\n2. Collect gesture images:\n   ```bash\n   python data_collection/datacollection.py\n   ```\n3. Upload samples of each gesture class (from each folder) as separate classes on [Google Teachable Machine](https://teachablemachine.withgoogle.com/). Train your model and export it as `keras_model.h5` and `labels.txt`, then place them in the `Model/` folder.\n\n4. Run real-time recognition:\n   ```bash\n   python data_collection/test.py\n   ```\n   \n--- \n\n## Author\n- ashishgoswami2121@gmail.com\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fashishgoswami13%2Fhandgesture_recognition","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fashishgoswami13%2Fhandgesture_recognition","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fashishgoswami13%2Fhandgesture_recognition/lists"}