Vision Models
Collection
Common computer vision class models, such as the YOLO family
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18 items
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Updated
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2
This version of RIFE has been converted to run on the Axera NPU using w8a16 quantization.
This model has been optimized with the following LoRA:
Compatible with Pulsar2 version: 4.2
For those who are interested in model conversion, you can try to export axmodel through
| Chips | model | cost |
|---|---|---|
| AX650 | RIFE | 200 ms |
Download all files from this repository to the device
root@ax650:~/rife# tree
.
|-- model
| `-- rife_x2_720p.axmodel
|-- video
| `-- demo.mp4
|`-- run_axmodel.py
|`-- ms_ssim.py
|`-- build_config.json
|`-- requirements.txt
Input Data:
|-- video
| `-- demo.mp4
root@ax650 ~/rife #python3 run_axmodel.py --model ./model/rife_x2_720p.axmodel --video ./video/demo.mp4
[INFO] Available providers: ['AxEngineExecutionProvider']
[INFO] Using provider: AxEngineExecutionProvider
[INFO] Chip type: ChipType.MC50
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Engine version: 2.12.0s
[INFO] Model type: 2 (triple core)
[INFO] Compiler version: 4.2 77cdc0c2
input name: onnx::Slice_0
demo.mp4, 128.0 frames in total, 25.0FPS to 50.0FPS
The audio will be merged after interpolation process
99%|βββββββββββββββββββββββββββββββββββββββ| 127/128.0 [01:38<00:00, 1.29it/s]
Output: [INFO]: