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@ -110,7 +110,7 @@ python u2net_portrait_composite.py -s 20 -a 0.5
**(2021-Feb-06)** Recently, some people asked the problem of using U<sup>2</sup>-Net for human segmentation, so we trained another example model for human segemntation based on [**Supervisely Person Dataset**](https://supervise.ly/explore/projects/supervisely-person-dataset-23304/datasets). <br/>
(1) To run the human segmentation model, please first downlowd the [**u2net_human_seg.pth**](https://drive.google.com/file/d/1-Yg0cxgrNhHP-016FPdp902BR-kSsA4P/view?usp=sharing) model weights into ``` ./saved_models/u2net_human_seg/```. <br/>
(1) To run the human segmentation model, please first downlowd the [**u2net_human_seg.pth**](https://drive.google.com/file/d/1m_Kgs91b21gayc2XLW0ou8yugAIadWVP/view?usp=sharing) model weights into ``` ./saved_models/u2net_human_seg/```. <br/>
(2) Prepare the to-be-segmented images into the corresponding directory, e.g. ```./test_data/test_human_images/```. <br/>
(3) Run the inference by command: ```python u2net_human_seg_test.py``` and the results will be output into the corresponding dirctory, e.g. ```./test_data/u2net_test_human_images_results/```<br/>
[**Notes: Due to the labeling accuracy of the Supervisely Person Dataset, the human segmentation model (u2net_human_seg.pth) here won't give you hair-level accuracy. But it should be more robust than u2net trained with DUTS-TR dataset on general human segmentation task. It can be used for human portrait segmentation, human body segmentation, etc.**](https://github.com/NathanUA/U-2-Net)<br/>