Hailo's person Re-Identification network is based on RepVGG_A0 and was trained in-house using several Person ReID datasets. It can work under various lighting conditions and numerous camera angles. 2 Models were trained independently - using 512 & 2048 embedding dimensions.
- RepVGG_A0
- Number of parameters: 9.65M / 7.68M
- GMACS: 0.89 / 0.89
- Rank1* : 89.8% / 89.3%* Evaluated on Market1501 dataset
- RGB image with various input sizes
- Image resize to 256x128x3 occurs on-chip
- Image normalization occurs on-chip
- Single embedding vector (2048 / 512 dim) per query
The table below shows the performance of our trained network on Market1501 dataset.
| network | Person Rank1 |
|---|---|
| repvgg_a0_person_reid_512 | 89.3 |
| repvgg_a0_person_reid_2048 | 89.8 |
The pre-compiled network can be download from:
- Use the following command to measure model performance on hailo’s HW:
hailortcli benchmark repvgg_a0_person_reid_512.hef hailortcli benchmark repvgg_a0_person_reid_2048.hef
A guide for training the pre-trained model on a custom dataset can be found here