YOLOX Object Detection
Use YOLOX object detection in Pixeltable by defining your schema, then using it
Building YOLOX Detection Apps
Pixeltable YOLOX apps work in two phases:
- Define your detection workflow (once)
- Use your app (anytime)
About Pixeltable YOLOX
pixeltable-yolox
is a lightweight, Apache-licensed object detection library built on PyTorch. It is a fork of the MegVii YOLOX package, modernized for recent versions of Python and refactored for easier use as a Python library. This library is designed for developers seeking a modern, accessible object detection solution for both academic and commercial projects.
Pixeltable YOLOX is still under development, and some features of the original YOLOX have not been ported yet. However, it offers a robust foundation for object detection tasks.
Developed by Pixeltable, Inc., a venture-backed AI infrastructure startup, this library aims to meet the vision community’s need for a lightweight object detection library with an untainted open source license. The Pixeltable team brings decades of collective experience in open source development from companies like Google, Cloudera, Twitter, Amazon, and Airbnb.
Install Dependencies
Define Your Detection Workflow
Create table.py
:
Use Your App
Create app.py
:
Advanced Inference with YOLOX
Beyond basic object detection, pixeltable-yolox
provides detailed output including bounding boxes, confidence scores, and class labels based on the COCO dataset categories.
Contribute to Pixeltable YOLOX
Join our community and contribute to the development of Pixeltable YOLOX