metadata
library_name: pytorch
YOLOX modernizes one-stage object detection by adopting an anchor-free design and decoupled classification and regression heads, improving both accuracy and convergence speed.
Original paper: YOLOX: Exceeding YOLO Series in 2021
YOLOX-S
YOLOX-S (Small) is a lightweight variant optimized for fast inference while maintaining competitive detection accuracy. It is well suited for real-time object detection in applications such as video analytics, robotics, and edge deployment where low latency is critical.
Model Configuration:
- Reference implementation: YOLOX
- Original Weight: YOLOX_S_Weights.COCO2017
- Resolution: 3x640x640
- Support Cooper version:
- Cooper SDK: [2.5.2]
- Cooper Foundry: [2.2]
| Model | Device | Model Link |
|---|---|---|
| YOLOX-s | N1-655 | Model_Link |
| YOLOX-s | CV72 | Model_Link |
| YOLOX-s | CV75 | Model_Link |