Add release note for v1.3.1

LICENSE

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+MIT License
+
+Copyright (c) 2021 Hust Visual Learning Team
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+---
+library_name: pytorch
+---
+
+![yolop_logo](resource/YOLOP.png)
+
+YOLOP is an efficient multi-task network for panoptic driving perception that jointly performs car detection, drivable area segmentation, and lane line segmentation with a shared encoder and three task-specific decoders, delivering strong accuracy–efficiency trade-offs for real-time onboard vision.
+
+Original paper: [YOLOP: You Only Look Once for Panoptic Driving Perception](https://link.springer.com/article/10.1007/s11633-022-1339-y)
+
+# YOLOP
+
+This model is the end-to-end YOLOP checkpoint trained for joint detection and segmentation on BDD100K. It is well suited for on-device panoptic driving perception where low latency and power efficiency are critical.
+
+Model Configuration:
+- Reference implementation: [YOLOP](https://github.com/hustvl/YOLOP)
+- Original Weight: [End-to-end.pth](https://github.com/hustvl/YOLOP/blob/main/weights/End-to-end.pth)
+- Resolution: 3x384x640
+- Support Cooper version:
+    - Cooper SDK: [2.5.4]
+    - Cooper Foundry: [2.3]
+
+| Model | Device | Compression | Model Link |
+| :-----: | :-----: | :-----: | ------- |
+| YOLOP | N1-655 | Amba_optimized | [Model_Link](https://huggingface.co/Ambarella/YOLOP/blob/main/n1-655_yolop_amba_optimized.bin) |
+| YOLOP | N1-655 | Activation_fp16 | [Model_Link](https://huggingface.co/Ambarella/YOLOP/blob/main/n1-655_yolop_act16.bin) |
+| YOLOP | CV7 | Amba_optimized | [Model_Link](https://huggingface.co/Ambarella/YOLOP/blob/main/cv7_yolop_amba_optimized.bin) |
+| YOLOP | CV7 | Activation_fp16 | [Model_Link](https://huggingface.co/Ambarella/YOLOP/blob/main/cv7_yolop_act16.bin) |
+| YOLOP | CV72 | Amba_optimized | [Model_Link](https://huggingface.co/Ambarella/YOLOP/blob/main/cv72_yolop_amba_optimized.bin) |
+| YOLOP | CV72 | Activation_fp16 | [Model_Link](https://huggingface.co/Ambarella/YOLOP/blob/main/cv72_yolop_act16.bin) |
+| YOLOP | CV75 | Amba_optimized | [Model_Link](https://huggingface.co/Ambarella/YOLOP/blob/main/cv75_yolop_amba_optimized.bin) |
+| YOLOP | CV75 | Activation_fp16 | [Model_Link](https://huggingface.co/Ambarella/YOLOP/blob/main/cv75_yolop_act16.bin) |

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