lucasjinreal/alfred
alfred-py: A deep learning utility library for **human**, more detail about the usage of lib to: https://zhuanlan.zhihu.com/p/341446046
What it solves
Alfred-py provides a centralized toolkit for deep learning practitioners to handle repetitive tasks such as data visualization, annotation format conversion, and model deployment, reducing the need to write boilerplate code for common computer vision and 3D data workflows.
How it works
It operates as both a Python library and a command-line interface (CLI). Users can import its APIs directly into their scripts for tasks like drawing bounding boxes or logging, or use the alfred terminal command to perform data operations like viewing annotations in YOLO, VOC, or COCO formats, converting between formats, and extracting frames from videos.
Who it’s for
Deep learning engineers and researchers, particularly those working with computer vision, 3D point clouds, and pose estimation, who need efficient tools for data inspection and preprocessing.
Highlights
- Multi-format Data Viewer: Built-in CLI tools to view annotations for VOC, COCO, YOLO, and TXT formats.
- Annotation Conversion: Ability to convert COCO format annotations to VOC.
- Vision Utilities: Tools for extracting images from video and combining images back into video.
- 3D Visualization: Support for visualizing 3D boxes on point clouds and a Mesh3D visualizer server based on Open3D.
- Deployment Support: Utilities to help deploy TensorRT models.
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