{"id":27314598,"url":"https://github.com/alihassanml/self-driving-using-deep-learning","last_synced_at":"2025-04-12T07:59:24.052Z","repository":{"id":286261943,"uuid":"960890306","full_name":"alihassanml/Self-Driving-Using-Deep-learning","owner":"alihassanml","description":"Self Driving Using Deep learning","archived":false,"fork":false,"pushed_at":"2025-04-07T15:58:47.000Z","size":11316,"stargazers_count":6,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-04-12T07:59:20.981Z","etag":null,"topics":["cnn","computer-vision","deep","deep-learning","self-driving-car","udacity"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/alihassanml.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-04-05T09:37:16.000Z","updated_at":"2025-04-11T12:53:25.000Z","dependencies_parsed_at":"2025-04-05T10:38:33.958Z","dependency_job_id":null,"html_url":"https://github.com/alihassanml/Self-Driving-Using-Deep-learning","commit_stats":null,"previous_names":["alihassanml/self-driving-using-deep-learning"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alihassanml%2FSelf-Driving-Using-Deep-learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alihassanml%2FSelf-Driving-Using-Deep-learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alihassanml%2FSelf-Driving-Using-Deep-learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alihassanml%2FSelf-Driving-Using-Deep-learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/alihassanml","download_url":"https://codeload.github.com/alihassanml/Self-Driving-Using-Deep-learning/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248537090,"owners_count":21120701,"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","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","computer-vision","deep","deep-learning","self-driving-car","udacity"],"created_at":"2025-04-12T07:59:23.546Z","updated_at":"2025-04-12T07:59:24.045Z","avatar_url":"https://github.com/alihassanml.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Self-Driving Car System Using Deep Learning\n\n![Project Banner](https://your-image-url.com/banner.png)\n\n## Table of Contents\n\n- [Overview](#overview)\n- [Features](#features)\n- [Installation](#installation)\n- [Usage](#usage)\n- [Model Architecture](#model-architecture)\n- [Dataset](#dataset)\n- [Results](#results)\n- [Contributing](#contributing)\n- [License](#license)\n- [Acknowledgements](#acknowledgements)\n\n## Overview\n\nThis project implements a self-driving car system utilizing a Convolutional Neural Network (CNN) to predict steering angles based on input images from a front-facing camera. The system is designed to operate within the Udacity Self-Driving Car Simulator, enabling autonomous navigation in a simulated environment.\n\n## Features\n\n- **Real-time Processing**: Utilizes `socketio` and `eventlet` for efficient real-time communication between the simulator and the model.\n- **Image Preprocessing**: Implements preprocessing techniques including region of interest selection, color space conversion, Gaussian blur, resizing, and normalization.\n- **Model Integration**: Loads a pre-trained CNN model (`model2.h5`) for predicting steering angles.\n- **Adaptive Throttle Control**: Adjusts the throttle based on current speed to maintain a predefined speed limit.\n\n## Installation\n\nTo set up the project, follow these steps:\n\n1. **Clone the Repository**:\n\n   ```bash\n   git clone https://github.com/alihassanml/Self-Driving-Using-Deep-learning.git\n   ```\n\n2. **Navigate to the Project Directory**:\n\n   ```bash\n   cd Self-Driving-Using-Deep-learning\n   ```\n\n3. **Install Required Dependencies**:\n\n   Ensure you have Python installed. Then, install the necessary packages:\n\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n   *Note: The `requirements.txt` file should list all necessary packages. If it's not present, install the following packages individually:*\n\n   ```bash\n   pip install eventlet socketio flask keras pillow opencv-python numpy\n   ```\n\n## Usage\n\nTo run the self-driving car system:\n\n1. **Launch the Udacity Self-Driving Car Simulator**:\n\n   - Select the autonomous mode.\n\n2. **Start the Python Server**:\n\n   Execute the provided Python script to start the server:\n\n   ```bash\n   python drive.py\n   ```\n\n   *Ensure that `drive.py` contains the provided code snippet and is located in the project directory.*\n\n3. **Monitor the Output**:\n\n   The server will display real-time predictions of steering angles, throttle values, and current speed.\n\n   Example output:\n\n   ```\n   Connected\n   Steering Angle: -0.045 Throttle: 0.9 Speed: 8.5\n   ```\n\n## Model Architecture\n\nThe CNN model (`model2.h5`) follows the architecture inspired by NVIDIA's End-to-End Learning for Self-Driving Cars. The architecture includes:\n\n- **Convolutional Layers**: Extract spatial features from input images.\n- **Activation Functions**: Introduce non-linearity using ReLU activations.\n- **Fully Connected Layers**: Interpret features and predict the steering angle.\n\n*Note: For detailed architecture and training procedures, refer to the model documentation or training script.*\n\n## Dataset\n\nThe model was trained using a dataset collected from the Udacity Self-Driving Car Simulator, comprising images from the front-facing camera and corresponding steering angles.\n\n## Results\n\nThe system successfully navigates the simulated environment, maintaining lane discipline and adapting to curves based on real-time predictions.\n\n*Include visual results or performance metrics if available.*\n\n## Contributing\n\nContributions are welcome! To contribute:\n\n1. Fork the repository.\n2. Create a new branch:\n\n   ```bash\n   git checkout -b feature/your-feature-name\n   ```\n\n3. Make your changes and commit them:\n\n   ```bash\n   git commit -m \"Add your message here\"\n   ```\n\n4. Push to your branch:\n\n   ```bash\n   git push origin feature/your-feature-name\n   ```\n\n5. Open a pull request detailing your changes.\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.\n\n## Acknowledgements\n\n- [Udacity Self-Driving Car Simulator](https://github.com/udacity/self-driving-car-sim)\n- NVIDIA's research on [End-to-End Learning for Self-Driving Cars](https://arxiv.org/abs/1604.07316)\n- [eventlet](http://eventlet.net/)\n- [socketio](https://python-socketio.readthedocs.io/en/latest/)\n- [Keras](https://keras.io/)\n- [OpenCV](https://opencv.org/)\n\n```\n\n**Notes**:\n\n- Replace `https://your-image-url.com/banner.png` with the actual URL of your project banner image.\n- Ensure that `requirements.txt` is present in your repository, listing all necessary dependencies. If not, consider creating one for ease of installation.\n- Include any additional sections or details relevant to your project to enhance clarity and usability.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falihassanml%2Fself-driving-using-deep-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falihassanml%2Fself-driving-using-deep-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falihassanml%2Fself-driving-using-deep-learning/lists"}