Fix some mistakes of model names in README.

README.md

@@ -1,84 +1,84 @@
----
-library_name: BiRefNet
-tags:
-- background-removal
-- mask-generation
-- Image Matting
-- pytorch_model_hub_mixin
-- model_hub_mixin
-repo_url: https://github.com/ZhengPeng7/BiRefNet
-pipeline_tag: image-segmentation
----
-<h1 align="center">Bilateral Reference for High-Resolution Dichotomous Image Segmentation</h1>
-
-<div align='center'>
-    <a href='https://scholar.google.com/citations?user=TZRzWOsAAAAJ' target='_blank'><strong>Peng Zheng</strong></a><sup> 1,4,5,6</sup>,&thinsp;
-    <a href='https://scholar.google.com/citations?user=0uPb8MMAAAAJ' target='_blank'><strong>Dehong Gao</strong></a><sup> 2</sup>,&thinsp;
-    <a href='https://scholar.google.com/citations?user=kakwJ5QAAAAJ' target='_blank'><strong>Deng-Ping Fan</strong></a><sup> 1*</sup>,&thinsp;
-    <a href='https://scholar.google.com/citations?user=9cMQrVsAAAAJ' target='_blank'><strong>Li Liu</strong></a><sup> 3</sup>,&thinsp;
-    <a href='https://scholar.google.com/citations?user=qQP6WXIAAAAJ' target='_blank'><strong>Jorma Laaksonen</strong></a><sup> 4</sup>,&thinsp;
-    <a href='https://scholar.google.com/citations?user=pw_0Z_UAAAAJ' target='_blank'><strong>Wanli Ouyang</strong></a><sup> 5</sup>,&thinsp;
-    <a href='https://scholar.google.com/citations?user=stFCYOAAAAAJ' target='_blank'><strong>Nicu Sebe</strong></a><sup> 6</sup>
-</div>
-
-<div align='center'>
-    <sup>1 </sup>Nankai University&ensp;  <sup>2 </sup>Northwestern Polytechnical University&ensp;  <sup>3 </sup>National University of Defense Technology&ensp; <sup>4 </sup>Aalto University&ensp;  <sup>5 </sup>Shanghai AI Laboratory&ensp;  <sup>6 </sup>University of Trento&ensp; 
-</div>
-
-<div align="center" style="display: flex; justify-content: center; flex-wrap: wrap;">
-  <a href='https://arxiv.org/pdf/2401.03407'><img src='https://img.shields.io/badge/arXiv-BiRefNet-red'></a>&ensp; 
-  <a href='https://drive.google.com/file/d/1aBnJ_R9lbnC2dm8dqD0-pzP2Cu-U1Xpt/view?usp=drive_link'><img src='https://img.shields.io/badge/中文版-BiRefNet-red'></a>&ensp; 
-  <a href='https://www.birefnet.top'><img src='https://img.shields.io/badge/Page-BiRefNet-red'></a>&ensp; 
-  <a href='https://drive.google.com/drive/folders/1s2Xe0cjq-2ctnJBR24563yMSCOu4CcxM'><img src='https://img.shields.io/badge/Drive-Stuff-green'></a>&ensp; 
-  <a href='LICENSE'><img src='https://img.shields.io/badge/License-MIT-yellow'></a>&ensp; 
-  <a href='https://huggingface.co/spaces/ZhengPeng7/BiRefNet_demo'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20HF%20Spaces-BiRefNet-blue'></a>&ensp; 
-  <a href='https://huggingface.co/ZhengPeng7/BiRefNet'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20HF%20Models-BiRefNet-blue'></a>&ensp; 
-  <a href='https://colab.research.google.com/drive/14Dqg7oeBkFEtchaHLNpig2BcdkZEogba?usp=drive_link'><img src='https://img.shields.io/badge/Single_Image_Inference-F9AB00?style=for-the-badge&logo=googlecolab&color=525252'></a>&ensp; 
-  <a href='https://colab.research.google.com/drive/1MaEiBfJ4xIaZZn0DqKrhydHB8X97hNXl#scrollTo=DJ4meUYjia6S'><img src='https://img.shields.io/badge/Inference_&_Evaluation-F9AB00?style=for-the-badge&logo=googlecolab&color=525252'></a>&ensp; 
-</div>
-
-## This repo holds the official weights of BiRefNet_lite trained in 2K resolution.
-
-### Training Sets:
-+ P3M-10k (except TE-P3M-500-NP)
-+ TR-humans
-+ AM-2k
-+ AIM-500
-+ Human-2k (synthesized with BG-20k)
-+ Distinctions-646 (synthesized with BG-20k)
-+ HIM2K
-+ PPM-100
-
-
-### Validation Sets:
-+ TE-P3M-500-NP
-
-### Performance:
-|    Dataset    |                Method               | maxFm | wFmeasure | MSE  | Smeasure | meanEm | HCE  | maxEm | meanFm | adpEm | adpFm | mBA  | maxBIoU | meanBIoU |
-|     :------:    | :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |
-| TE-P3M-500-NP | BiRefNet_lite-2K-general--epoch_100 |  .979   |  .996 |  .988  | .003 |  .997 |  .986  |    .988   |  .864 |  .885 | .000 | .830 |   .940  |   .888   |
-
-
-**Check the main BiRefNet model repo for more info and how to use it:**  
-https://huggingface.co/ZhengPeng7/BiRefNet/blob/main/README.md
-
-**Also check the GitHub repo of BiRefNet for all things you may want:**  
-https://github.com/ZhengPeng7/BiRefNet
-
-## Acknowledgement:
-
-+ Many thanks to @freepik for their generous support on GPU resources for training this model!
-
-
-## Citation
-
-```
-@article{zheng2024birefnet,
-  title={Bilateral Reference for High-Resolution Dichotomous Image Segmentation},
-  author={Zheng, Peng and Gao, Dehong and Fan, Deng-Ping and Liu, Li and Laaksonen, Jorma and Ouyang, Wanli and Sebe, Nicu},
-  journal={CAAI Artificial Intelligence Research},
-  volume = {3},
-  pages = {9150038},
-  year={2024}
-}
-```
+---
+library_name: BiRefNet
+tags:
+- background-removal
+- mask-generation
+- Image Matting
+- pytorch_model_hub_mixin
+- model_hub_mixin
+repo_url: https://github.com/ZhengPeng7/BiRefNet
+pipeline_tag: image-segmentation
+---
+<h1 align="center">Bilateral Reference for High-Resolution Dichotomous Image Segmentation</h1>
+
+<div align='center'>
+    <a href='https://scholar.google.com/citations?user=TZRzWOsAAAAJ' target='_blank'><strong>Peng Zheng</strong></a><sup> 1,4,5,6</sup>,&thinsp;
+    <a href='https://scholar.google.com/citations?user=0uPb8MMAAAAJ' target='_blank'><strong>Dehong Gao</strong></a><sup> 2</sup>,&thinsp;
+    <a href='https://scholar.google.com/citations?user=kakwJ5QAAAAJ' target='_blank'><strong>Deng-Ping Fan</strong></a><sup> 1*</sup>,&thinsp;
+    <a href='https://scholar.google.com/citations?user=9cMQrVsAAAAJ' target='_blank'><strong>Li Liu</strong></a><sup> 3</sup>,&thinsp;
+    <a href='https://scholar.google.com/citations?user=qQP6WXIAAAAJ' target='_blank'><strong>Jorma Laaksonen</strong></a><sup> 4</sup>,&thinsp;
+    <a href='https://scholar.google.com/citations?user=pw_0Z_UAAAAJ' target='_blank'><strong>Wanli Ouyang</strong></a><sup> 5</sup>,&thinsp;
+    <a href='https://scholar.google.com/citations?user=stFCYOAAAAAJ' target='_blank'><strong>Nicu Sebe</strong></a><sup> 6</sup>
+</div>
+
+<div align='center'>
+    <sup>1 </sup>Nankai University&ensp;  <sup>2 </sup>Northwestern Polytechnical University&ensp;  <sup>3 </sup>National University of Defense Technology&ensp; <sup>4 </sup>Aalto University&ensp;  <sup>5 </sup>Shanghai AI Laboratory&ensp;  <sup>6 </sup>University of Trento&ensp; 
+</div>
+
+<div align="center" style="display: flex; justify-content: center; flex-wrap: wrap;">
+  <a href='https://arxiv.org/pdf/2401.03407'><img src='https://img.shields.io/badge/arXiv-BiRefNet-red'></a>&ensp; 
+  <a href='https://drive.google.com/file/d/1aBnJ_R9lbnC2dm8dqD0-pzP2Cu-U1Xpt/view?usp=drive_link'><img src='https://img.shields.io/badge/中文版-BiRefNet-red'></a>&ensp; 
+  <a href='https://www.birefnet.top'><img src='https://img.shields.io/badge/Page-BiRefNet-red'></a>&ensp; 
+  <a href='https://drive.google.com/drive/folders/1s2Xe0cjq-2ctnJBR24563yMSCOu4CcxM'><img src='https://img.shields.io/badge/Drive-Stuff-green'></a>&ensp; 
+  <a href='LICENSE'><img src='https://img.shields.io/badge/License-MIT-yellow'></a>&ensp; 
+  <a href='https://huggingface.co/spaces/ZhengPeng7/BiRefNet_demo'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20HF%20Spaces-BiRefNet-blue'></a>&ensp; 
+  <a href='https://huggingface.co/ZhengPeng7/BiRefNet'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20HF%20Models-BiRefNet-blue'></a>&ensp; 
+  <a href='https://colab.research.google.com/drive/14Dqg7oeBkFEtchaHLNpig2BcdkZEogba?usp=drive_link'><img src='https://img.shields.io/badge/Single_Image_Inference-F9AB00?style=for-the-badge&logo=googlecolab&color=525252'></a>&ensp; 
+  <a href='https://colab.research.google.com/drive/1MaEiBfJ4xIaZZn0DqKrhydHB8X97hNXl#scrollTo=DJ4meUYjia6S'><img src='https://img.shields.io/badge/Inference_&_Evaluation-F9AB00?style=for-the-badge&logo=googlecolab&color=525252'></a>&ensp; 
+</div>
+
+## This repo holds the official weights of BiRefNet for general matting.
+
+### Training Sets:
++ P3M-10k (except TE-P3M-500-NP)
++ TR-humans
++ AM-2k
++ AIM-500
++ Human-2k (synthesized with BG-20k)
++ Distinctions-646 (synthesized with BG-20k)
++ HIM2K
++ PPM-100
+
+
+### Validation Sets:
++ TE-P3M-500-NP
+
+### Performance:
+|    Dataset    |                Method               | maxFm | wFmeasure | MSE  | Smeasure | meanEm | HCE  | maxEm | meanFm | adpEm | adpFm | mBA  | maxBIoU | meanBIoU |
+|     :------:    | :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |  :------: |
+| TE-P3M-500-NP | BiRefNet-matting--epoch_100 |  .979   |  .996 |  .988  | .003 |  .997 |  .986  |    .988   |  .864 |  .885 | .000 | .830 |   .940  |   .888   |
+
+
+**Check the main BiRefNet model repo for more info and how to use it:**  
+https://huggingface.co/ZhengPeng7/BiRefNet/blob/main/README.md
+
+**Also check the GitHub repo of BiRefNet for all things you may want:**  
+https://github.com/ZhengPeng7/BiRefNet
+
+## Acknowledgement:
+
++ Many thanks to @freepik for their generous support on GPU resources for training this model!
+
+
+## Citation
+
+```
+@article{zheng2024birefnet,
+  title={Bilateral Reference for High-Resolution Dichotomous Image Segmentation},
+  author={Zheng, Peng and Gao, Dehong and Fan, Deng-Ping and Liu, Li and Laaksonen, Jorma and Ouyang, Wanli and Sebe, Nicu},
+  journal={CAAI Artificial Intelligence Research},
+  volume = {3},
+  pages = {9150038},
+  year={2024}
+}
+```