first commit

MixDehazeNet/README.md

@@ -1,89 +0,0 @@
----
-license: mit
-language:
-- en
-pipeline_tag: image-to-image
-tags:
-- dehazing
-- ImageEnhancement
-
-# ImageDehazing
-
-This is a collection of image dehazing algorithms, models have been converted to run on the Axera NPU using **w8a8** quantization.
-
-This model has been optimized with the following LoRA: 
-
-Compatible with Pulsar2 version: 6.0 115775d3
-
-## Convert tools links:
-
-For those who are interested in model conversion, you can try to export axmodel through 
-
-- [Pulsar2 Link, How to Convert ONNX to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html) 
-
-
-## Support Platform
-
-- AX650
-  - [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
-  - [M.2 Accelerator card](https://docs.m5stack.com/en/ai_hardware/LLM-8850_Card)
-  
-
-| 模型 | 输入分辨率 | AX650板端耗时 |
-|------|-----------|--------------|
-| AOD-Net | 640×480 | 2.4 ms |
-| Light-Dehazenet | 480×640 | 9.2 ms |
-| DehazeFormer_t | 512×512 | 161ms |
-| MixDehazeNet | 256×256 | 38 ms |
-| GCANet | 512×512 | 80 ms |
-| GridDehazeNet | 640×480 | 113 ms |
-| DEA-Net | 512×512 | 127 ms |
-| FFA-Net | 512×512 | 873 ms |
-
-
-## How to use
-
-Download all files from this repository to the device
-
-```
-所有模型文件组织方式均如下：
-.
-|-- model_convert
-|   |-- axmodel
-|   |   `-- dehazeformer-t-512-constant.axmodel
-|   `-- dehazeformer.json
-|-- pic
-|   `-- 00000_0_0.1800.png
-|-- python
-|   |-- axmodel_infer.py
-|   `-- onnx_infer.py
-`-- res
-    `-- output.png
-
-```
-
-### Inference
-#### Inference with AX650 Host, such as M4N-Dock(爱芯派Pro)
-模型推理，执行命令:
-```
-(base) root@ax650:~/GCANet# python axmodel_infer.py
-[INFO] Available providers:  ['AxEngineExecutionProvider', 'AXCLRTExecutionProvider']
-[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: 7.0 22923e4e
-Saved: axmodel_output/0051_0.8_0.2_input_dehaze_compare.png
-Saved: axmodel_output/0099_0.9_0.16_input_dehaze_compare.png
-
-
-```
-
-```
-推理结果样例：
-
-![](GCANet/res/0099_0.9_0.16_input_dehaze_compare.png)
-![](GCANet/res/0051_0.8_0.2_input_dehaze_compare.png)
-
-```

README.md

@@ -1,3 +1,89 @@
 ---
 license: mit
----
+language:
+- en
+pipeline_tag: image-to-image
+tags:
+- dehazing
+- ImageEnhancement
+
+# ImageDehazing
+
+This is a collection of image dehazing algorithms, models have been converted to run on the Axera NPU using **w8a8** quantization.
+
+This model has been optimized with the following LoRA: 
+
+Compatible with Pulsar2 version: 6.0 115775d3
+
+## Convert tools links:
+
+For those who are interested in model conversion, you can try to export axmodel through 
+
+- [Pulsar2 Link, How to Convert ONNX to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html) 
+
+
+## Support Platform
+
+- AX650
+  - [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
+  - [M.2 Accelerator card](https://docs.m5stack.com/en/ai_hardware/LLM-8850_Card)
+  
+
+| 模型 | 输入分辨率 | AX650板端耗时 |
+|------|-----------|--------------|
+| AOD-Net | 640×480 | 2.4 ms |
+| Light-Dehazenet | 480×640 | 9.2 ms |
+| DehazeFormer_t | 512×512 | 161ms |
+| MixDehazeNet | 256×256 | 38 ms |
+| GCANet | 512×512 | 80 ms |
+| GridDehazeNet | 640×480 | 113 ms |
+| DEA-Net | 512×512 | 127 ms |
+| FFA-Net | 512×512 | 873 ms |
+
+
+## How to use
+
+Download all files from this repository to the device
+
+```
+所有模型文件组织方式均如下：
+.
+|-- model_convert
+|   |-- axmodel
+|   |   `-- dehazeformer-t-512-constant.axmodel
+|   `-- dehazeformer.json
+|-- pic
+|   `-- 00000_0_0.1800.png
+|-- python
+|   |-- axmodel_infer.py
+|   `-- onnx_infer.py
+`-- res
+    `-- output.png
+
+```
+
+### Inference
+#### Inference with AX650 Host, such as M4N-Dock(爱芯派Pro)
+模型推理，执行命令:
+```
+(base) root@ax650:~/GCANet# python axmodel_infer.py
+[INFO] Available providers:  ['AxEngineExecutionProvider', 'AXCLRTExecutionProvider']
+[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: 7.0 22923e4e
+Saved: axmodel_output/0051_0.8_0.2_input_dehaze_compare.png
+Saved: axmodel_output/0099_0.9_0.16_input_dehaze_compare.png
+
+
+```
+
+```
+推理结果样例：
+
+![](GCANet/res/0099_0.9_0.16_input_dehaze_compare.png)
+![](GCANet/res/0051_0.8_0.2_input_dehaze_compare.png)
+
+```