Welcome to FastMap, a fast structure from motion pipeline designed to work seamlessly with PyTorch. This repository offers a robust framework for those interested in computer vision and 3D reconstruction. Whether you're a researcher, developer, or enthusiast, FastMap provides tools to accelerate your projects in the realm of 3D modeling.
FastMap is designed to simplify the process of structure from motion (SfM). It utilizes advanced algorithms and optimizations to provide fast and reliable 3D reconstructions from image sequences. Built on the PyTorch framework, it leverages GPU acceleration for improved performance.
This project aims to bridge the gap between academic research and practical applications, making state-of-the-art SfM techniques accessible to a wider audience.
- Speed: FastMap is optimized for speed, enabling quick processing of large datasets.
- Accuracy: Achieve high-quality 3D reconstructions with minimal error.
- Flexibility: Adaptable to various use cases in computer vision and robotics.
- Ease of Use: Simple API that allows for quick integration into existing workflows.
To get started with FastMap, follow these steps:
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Clone the repository:
git clone https://github.com/toancontrai/fastmap.git cd fastmap -
Install dependencies:
Make sure you have Python and PyTorch installed. You can install the required packages using pip:
pip install -r requirements.txt
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Download the latest release:
You can find the latest release here. Download the file and execute it to get started.
FastMap provides a straightforward interface for running the structure from motion pipeline. Here’s how you can use it:
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Prepare your images: Ensure your images are in a suitable format and organized in a directory.
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Run the pipeline:
Use the following command to start the reconstruction process:
python run_fastmap.py --input_dir path/to/your/images --output_dir path/to/save/results
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Visualize results: After processing, you can visualize the 3D model using the provided tools.
We welcome contributions to FastMap! If you would like to help improve the project, please follow these steps:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Make your changes and test thoroughly.
- Submit a pull request detailing your changes.
Please ensure your code adheres to the project's style guidelines and includes relevant tests.
FastMap is licensed under the MIT License. Feel free to use, modify, and distribute the code, but please give appropriate credit.
For the latest releases and updates, visit the Releases section. Make sure to download the latest version and execute it to access new features and improvements.
We would like to thank the contributors and researchers in the field of computer vision whose work has inspired and guided the development of FastMap. Special thanks to the PyTorch community for providing a powerful framework that makes our work possible.
For any questions or issues, feel free to open an issue in the repository. We appreciate your interest in FastMap and look forward to your contributions!