update readme

README.md

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+---
+license: other
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+widget:
+- src: >-
+    https://media.istockphoto.com/id/515788534/photo/cheerful-and-confidant.jpg?s=612x612&w=0&k=20&c=T0Z4DfameRpyGhzevPomrm-wjZp7wmGjpAyjGcTzpkA=
+  example_title: Person
+- src: >-
+    https://storage.googleapis.com/pai-images/1484fd9ea9d746eb9f1de0d6778dbea2.jpeg
+  example_title: Person
+datasets:
+- sayeed99/human_parsing_fashion_dataset
+model-index:
+- name: segformer-b2-human
+  results: []
+pipeline_tag: image-segmentation
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# segformer-b2-fashion
+
+This model is a fine-tuned version of [nvidia/mit-b2](https://huggingface.co/nvidia/mit-b2) on the sayeed99/human_parsing_fashion_dataset dataset.
+
+
+```python
+from transformers import SegformerImageProcessor, AutoModelForSemanticSegmentation
+from PIL import Image
+import requests
+import matplotlib.pyplot as plt
+import torch.nn as nn
+
+processor = SegformerImageProcessor.from_pretrained("sayeed99/segformer-b2-human")
+model = AutoModelForSemanticSegmentation.from_pretrained("sayeed99/segformer-b2-human")
+
+url = "https://plus.unsplash.com/premium_photo-1673210886161-bfcc40f54d1f?ixlib=rb-4.0.3&ixid=MnwxMjA3fDB8MHxzZWFyY2h8MXx8cGVyc29uJTIwc3RhbmRpbmd8ZW58MHx8MHx8&w=1000&q=80"
+
+image = Image.open(requests.get(url, stream=True).raw)
+inputs = processor(images=image, return_tensors="pt")
+
+outputs = model(**inputs)
+logits = outputs.logits.cpu()
+
+upsampled_logits = nn.functional.interpolate(
+    logits,
+    size=image.size[::-1],
+    mode="bilinear",
+    align_corners=False,
+)
+
+pred_seg = upsampled_logits.argmax(dim=1)[0]
+plt.imshow(pred_seg)
+```
+
+Labels : {"0":"Background","1":"shirt, blouse","2":"top, t-shirt, sweatshirt","3":"sweater","4":"cardigan","5":"jacket","6":"vest","7":"pants","8":"shorts","9":"skirt","10":"coat","11":"dress","12":"jumpsuit","13":"cape","14":"glasses","15":"hat","16":"headband, head covering, hair accessory","17":"tie","18":"glove","19":"watch","20":"belt","21":"leg warmer","22":"tights, stockings","23":"sock","24":"shoe","25":"bag, wallet","26":"scarf","27":"umbrella","28":"hood","29":"collar","30":"lapel","31":"epaulette","32":"sleeve","33":"pocket","34":"neckline","35":"buckle","36":"zipper","37":"applique","38":"bead","39":"bow","40":"flower","41":"fringe","42":"ribbon","43":"rivet","44":"ruffle","45":"sequin","46":"tassel","47":"Hair","48":"Sunglasses","49":"Upper-clothes","50":"Left-shoe","51":"Right-shoe","52":"Face","53":"Left-leg","54":"Right-leg","55":"Left-arm","56":"Right-arm"}
+
+### Framework versions
+
+- Transformers 4.30.0
+- Pytorch 2.2.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.13.3
+
+
+### License
+
+The license for this model can be found [here](https://github.com/NVlabs/SegFormer/blob/master/LICENSE).
+
+### BibTeX entry and citation info
+
+```bibtex
+@article{DBLP:journals/corr/abs-2105-15203,
+  author    = {Enze Xie and
+               Wenhai Wang and
+               Zhiding Yu and
+               Anima Anandkumar and
+               Jose M. Alvarez and
+               Ping Luo},
+  title     = {SegFormer: Simple and Efficient Design for Semantic Segmentation with
+               Transformers},
+  journal   = {CoRR},
+  volume    = {abs/2105.15203},
+  year      = {2021},
+  url       = {https://arxiv.org/abs/2105.15203},
+  eprinttype = {arXiv},
+  eprint    = {2105.15203},
+  timestamp = {Wed, 02 Jun 2021 11:46:42 +0200},
+  biburl    = {https://dblp.org/rec/journals/corr/abs-2105-15203.bib},
+  bibsource = {dblp computer science bibliography, https://dblp.org}
+}