metadata
pipeline_tag: image-to-image
DeOldify
This version of DeOldify 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: 5.0-patch1
Convert tools links:
For those who are interested in model conversion, you can try to export axmodel through
The repo of AXera Platform, which you can get the detail of guide
Support Platform
| Chips | model | cost |
|---|---|---|
| AX650 | colorize_stable | 377 ms |
How to use
Download all files from this repository to the device
root@ax650:~/deoldify# tree
.
|-- model
| `-- colorize_stable.axmodel
|-- python
|`-- run_axmodel.py
|`-- requirements.txt
Inference
Input Data:
|-- image
| `-- 1850Geography.jpg
Inference with M.2 Accelerator card
$cd python
$python3 gradio_demo.py
[INFO] Available providers: ['AXCLRTExecutionProvider']
[INFO] Using provider: AXCLRTExecutionProvider
[INFO] SOC Name: AX650N
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Compiler version: 5.0-patch1 2295293f
[INFO] Using provider: AXCLRTExecutionProvider
[INFO] SOC Name: AX650N
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Compiler version: 5.0-patch1 2295293f
==================================================
🌐 AI图片上色 Web UI 已启动！
🔗 本地访问: http://127.0.0.1:7860
🔗 局域网访问: http://10.126.33.124:7860
==================================================
Then open the link in the browser to use the web UI:
Inference with AX650 Host, such as M4N-Dock(爱芯派Pro)
root@ax650 ~/realesrgan #python3 run_axmodel.py --input_path image/1850Geography.jpg --model_path colorize_stable.axmodel
[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: 5.0-patch1 2295293f
Color image save to `./sr_colorized.jpg`
Output:
