Update README.md

README.md

@@ -1,3 +1,63 @@
+### YOLOS (small-sized) model Finetuned For Seal Detection Task
+
+#### YOLOS model based on `hustvl/yolos-small` and fine-tuned on Our Seal Image Dataset.
+
+#### Model description
+YOLOS is a Vision Transformer (ViT) trained using the DETR loss. 
+
+#### How to use
+Here is how to use this model:
+```
+from transformers import YolosFeatureExtractor, YolosForObjectDetection
+from PIL import Image
+import requests
+
+image = Image.open("xxxxxxxxxxxxx")
+
+feature_extractor = YolosFeatureExtractor.from_pretrained('fantast/yolos-small-finetuned-for-seal')
+model = YolosForObjectDetection.from_pretrained('fantast/yolos-small-finetuned-for-seal')
+
+inputs = feature_extractor(images=image, return_tensors="pt")
+outputs = model(**inputs)
+```
+
+# model predicts bounding boxes
+```
+logits = outputs.logits
+bboxes = outputs.pred_boxes
+```
+Currently, both the feature extractor and model support PyTorch.
+
+#### Training data
+The YOLOS model based on `hustvl/yolos-small` and fine-tuned on Our Own Seal Image Dataset, a dataset consisting of 118k/5k annotated images for training/validation respectively.
+
+
+BibTeX entry and citation info
+```
+@article{DBLP:journals/corr/abs-2106-00666,
+  author    = {Yuxin Fang and
+               Bencheng Liao and
+               Xinggang Wang and
+               Jiemin Fang and
+               Jiyang Qi and
+               Rui Wu and
+               Jianwei Niu and
+               Wenyu Liu},
+  title     = {You Only Look at One Sequence: Rethinking Transformer in Vision through
+               Object Detection},
+  journal   = {CoRR},
+  volume    = {abs/2106.00666},
+  year      = {2021},
+  url       = {https://arxiv.org/abs/2106.00666},
+  eprinttype = {arXiv},
+  eprint    = {2106.00666},
+  timestamp = {Fri, 29 Apr 2022 19:49:16 +0200},
+  biburl    = {https://dblp.org/rec/journals/corr/abs-2106-00666.bib},
+  bibsource = {dblp computer science bibliography, https://dblp.org}
+}
+```
+
+
 ---
 license: mit
 ---