Update README.md

README.md

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----
-license: bsd-3-clause
----
+---
+license: mit
+language:
+- en
+base_model:
+- Ultralytics/YOLOv8
+pipeline_tag: object-detection
+tags:
+- Ultralytics
+- YOLOv8
+- YOLOv8-Seg
+---
+
+# YOLOv8-Seg
+
+This version of YOLOv8-Seg 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: 3.4
+
+## Convert tools links:
+
+For those who are interested in model conversion, you can try to export axmodel through 
+
+- [The repo of AXera Platform](https://github.com/AXERA-TECH/ax-samples), which you can get the detial of guide
+
+- [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://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html)
+- AX630C
+  - [爱芯派2](https://axera-pi-2-docs-cn.readthedocs.io/zh-cn/latest/index.html)
+  - [Module-LLM](https://docs.m5stack.com/zh_CN/module/Module-LLM)
+  - [LLM630 Compute Kit](https://docs.m5stack.com/zh_CN/core/LLM630%20Compute%20Kit)
+  
+|Chips|yolov8s-seg|
+|--|--|
+|AX650| 4.6 ms |
+|AX630C| TBD ms |
+
+## How to use
+
+Download all files from this repository to the device
+
+```
+
+root@ax650:~/YOLOv8-Seg# tree
+.
+|-- ax650
+|   `-- yolov8s-seg.axmodel
+|-- ax_yolov8_seg
+|-- football.jpg
+`-- yolov8_seg_out.jpg
+```
+
+### Inference
+
+Input image:
+![](./football.jpg)
+
+#### Inference with AX650 Host, such as M4N-Dock(爱芯派Pro)
+
+```
+root@ax650:~/samples/AXERA-TECH/YOLOv8-Seg# ./ax_yolov8_seg -m ax650/yolov8s_seg.axmodel -i football.jpg
+--------------------------------------
+model file : ax650/yolov8s_seg.axmodel
+image file : football.jpg
+img_h, img_w : 640 640
+--------------------------------------
+Engine creating handle is done.
+Engine creating context is done.
+Engine get io info is done.
+Engine alloc io is done.
+Engine push input is done.
+--------------------------------------
+
+input size: 1
+    name:   images [UINT8] [BGR]
+        1 x 640 x 640 x 3
+
+
+output size: 7
+    name: /model.22/Concat_1_output_0 [FLOAT32]
+        1 x 80 x 80 x 144
+
+    name: /model.22/Concat_2_output_0 [FLOAT32]
+        1 x 40 x 40 x 144
+
+    name: /model.22/Concat_3_output_0 [FLOAT32]
+        1 x 20 x 20 x 144
+
+    name: /model.22/cv4.0/cv4.0.2/Conv_output_0 [FLOAT32]
+        1 x 80 x 80 x 32
+
+    name: /model.22/cv4.1/cv4.1.2/Conv_output_0 [FLOAT32]
+        1 x 40 x 40 x 32
+
+    name: /model.22/cv4.2/cv4.2.2/Conv_output_0 [FLOAT32]
+        1 x 20 x 20 x 32
+
+    name:  output1 [FLOAT32]
+        1 x 32 x 160 x 160
+
+post process cost time:16.21 ms
+--------------------------------------
+Repeat 1 times, avg time 4.69 ms, max_time 4.69 ms, min_time 4.69 ms
+--------------------------------------
+detection num: 8
+ 0:  92%, [1354,  340, 1629, 1035], person
+ 0:  91%, [   5,  359,  314, 1108], person
+ 0:  91%, [ 759,  220, 1121, 1153], person
+ 0:  88%, [ 490,  476,  661,  999], person
+32:  73%, [1233,  877, 1286,  923], sports ball
+32:  63%, [ 772,  888,  828,  937], sports ball
+32:  63%, [ 450,  882,  475,  902], sports ball
+ 0:  55%, [1838,  690, 1907,  811], person
+--------------------------------------
+```
+
+Output image:
+![](./yolov8_seg_out.jpg)