- Semantic Segmentation
All of the original and compressed models can be downloaded easily on the Model Compressor Model Zoo.
You can get Compressed results with Automatic Compression and Compressed (Adv.) results with Advanced Compression.
PyTorch
| Model | Best Practice | Type | Dataset | mIoU (%) | Global Correct (%) | FLOPs (M) | Params (M) | Latency (ms) | Model Size (MB) |
|---|---|---|---|---|---|---|---|---|---|
| FCN ResNet50 | Original | COCO | 60.5 | 91.4 | 306554.91 | 35.32 | 13167.17 | 135.09 | |
| FCN ResNet50 | Google Colab | Compressed-1 | COCO | 59.6 (-0.9) | 91.4 (-0.0) | 156106.03 (1.96x) | 17.58 (2.01x) | 6438.06 (2.04x) | 67.34 (2.01x) |
| FCN ResNet50 | Google Colab | Compressed-2 | COCO | 54.7 (-5.8) | 90.7 (-0.7) | 45826.66 (x6.68) | 4.84 (7.31x) | 2147.92 (6.13x) | 18.70 (7.22x) |
- We used a subset of COCO dataset to fine-tuning FCN ResNet50. You can check more details of dataset here.
- The model's latency is measured using a Raspberry Pi 4B (1.5GHz ARM Cortex).
- Options: FP32, ONNX runtime
Updated 5 months ago