{"id":26332673,"url":"https://github.com/prajwalamte/sign_language_recognition","last_synced_at":"2025-08-11T16:05:21.330Z","repository":{"id":190185843,"uuid":"681989108","full_name":"PrajwalAmte/Sign_Language_Recognition","owner":"PrajwalAmte","description":"This project centers around two primary aspects: the development of a model for the recognition of American Sign Language (ASL) gestures utilizing a dataset, and the real-time prediction of gestures via a camera feed, accompanied by the conversion of these predictions into spoken language.","archived":false,"fork":false,"pushed_at":"2023-08-24T05:45:59.000Z","size":33464,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-15T23:29:37.281Z","etag":null,"topics":["cnn-model-training","computer-vision","deep-learning","gtts-library","hand-gesture-recognition","image-processing","mediapipe","real-time-prediction"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/PrajwalAmte.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2023-08-23T07:40:00.000Z","updated_at":"2024-10-18T01:15:07.000Z","dependencies_parsed_at":null,"dependency_job_id":"c3a32754-3d86-44b8-945d-7970b037f99c","html_url":"https://github.com/PrajwalAmte/Sign_Language_Recognition","commit_stats":null,"previous_names":["prajwalamte/sign_language_recognition"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/PrajwalAmte/Sign_Language_Recognition","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PrajwalAmte%2FSign_Language_Recognition","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PrajwalAmte%2FSign_Language_Recognition/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PrajwalAmte%2FSign_Language_Recognition/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PrajwalAmte%2FSign_Language_Recognition/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/PrajwalAmte","download_url":"https://codeload.github.com/PrajwalAmte/Sign_Language_Recognition/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PrajwalAmte%2FSign_Language_Recognition/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":269915284,"owners_count":24495674,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-11T02:00:10.019Z","response_time":75,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cnn-model-training","computer-vision","deep-learning","gtts-library","hand-gesture-recognition","image-processing","mediapipe","real-time-prediction"],"created_at":"2025-03-15T23:29:59.918Z","updated_at":"2025-08-11T16:05:21.286Z","avatar_url":"https://github.com/PrajwalAmte.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Sign Language Recognition Project\n\n![ASL Gesture](sign_mnist/asl_sign.png)\n\n## Project Overview\n\nThis project focuses on two main parts: training a model to recognize American Sign Language (ASL) gestures using a dataset, and predicting gestures through a camera feed while converting predictions into speech.\n\n## Part 1: Model Training (`model.py`)\n\nThe `model.py` script is responsible for training a convolutional neural network (CNN) model to recognize ASL gestures. The key steps include:\n\n1. **Importing necessary libraries.**\n2. **Loading and preprocessing the ASL gesture dataset.**\n3. **Defining and compiling the CNN model architecture.**\n4. **Training the model using the preprocessed dataset.**\n5. **Saving the trained model as `smnist.h5`.**\n\nTo train the model, execute:\n\n```\npython model.py\n```\n\n## Part 2: Gesture Prediction and Speech Conversion (`prediction.py`)\n\nThe `prediction.py` script predicts ASL gestures in real-time through a camera feed. It further converts these predictions into speech using the Google Text-to-Speech (gTTS) library. The script's steps are as follows:\n\n1. **Importing Required Libraries**: Import the necessary libraries for the script.\n\n2. **Loading the Pre-trained CNN Model**: Load the pre-trained CNN model (`smnist.h5`) for gesture recognition.\n\n3. **Initializing the Camera Feed**: Initialize the camera feed to capture video frames.\n\n4. **Capturing and Processing Video Frames**: Continuously capture and process video frames from the camera.\n\n5. **Gesture Prediction**: Press the **Space** key to predict the ASL gesture. The predicted gesture will be displayed on the screen.\n\n6. **Closing the Window**: Press the **ESC** key to close the video feed window.\n\n7. **Converting Predictions into Speech using gTTS**: Utilize the gTTS library to convert predictions into speech.\n\n8. **Playing the Generated Speech**: Play the generated speech using an appropriate audio player.\n\n\nTo predict and convert ASL gestures, run the following command:\n\n\n```\npython prediction.py\n```\n\n## Requirements\n\n- Python (version 3.x)\n- Required libraries (install using pip):\n\n```bash\npip install numpy pandas matplotlib seaborn keras scikit-learn opencv-python mediapipe gTTS\n```\n\n## Acknowledgements\n\nThis project makes use of the Mediapipe library for hand gesture recognition and the Google Text-to-Speech (gTTS) library for speech synthesis. The ASL gesture dataset used for this project was obtained from [Kaggle](https://www.kaggle.com/datasets/datamunge/sign-language-mnist) and serves as the primary dataset for training and testing the ASL gesture recognition model.\n\n## License\n\nThis project is licensed under the MIT License. Refer to the `LICENSE` file for more information.\n\nFeel free to contribute and adapt this project to enhance accessibility and communication for individuals using American Sign Language.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprajwalamte%2Fsign_language_recognition","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprajwalamte%2Fsign_language_recognition","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprajwalamte%2Fsign_language_recognition/lists"}