edit: model card

README.md

@@ -3,4 +3,46 @@ language:
 - ko
 tags:
 - ocr
----
+widget:
+- src: https://raw.githubusercontent.com/ddobokki/ocr_img_example/master/g.jpg
+  example_title: word1
+- src: https://raw.githubusercontent.com/ddobokki/ocr_img_example/master/khs.jpg
+  example_title: word2
+- src: https://raw.githubusercontent.com/ddobokki/ocr_img_example/master/m.jpg
+  example_title: word3
+---
+
+# korean trocr model
+
+## train datasets
+AI Hub
+- [다양한 형태의 한글 문자 OCR](https://aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=realm&dataSetSn=91)
+- [공공행정문서 OCR](https://aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=realm&dataSetSn=88)
+
+## model structure
+- encoder : [trocr-base-stage1's encoder](https://huggingface.co/microsoft/trocr-base-stage1)
+- decoder : [KR-BERT-char16424](https://huggingface.co/snunlp/KR-BERT-char16424)
+
+## how to use
+
+```python
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel, AutoTokenizer
+import requests 
+import unicodedata
+from io import BytesIO
+from PIL import Image
+
+processor = TrOCRProcessor.from_pretrained("ddobokki/ko-trocr") 
+model = VisionEncoderDecoderModel.from_pretrained("ddobokki/ko-trocr")
+tokenizer = AutoTokenizer.from_pretrained("ddobokki/ko-trocr")
+
+url = "https://raw.githubusercontent.com/ddobokki/ocr_img_example/master/g.jpg"
+response = requests.get(url)
+img = Image.open(BytesIO(response.content))
+
+pixel_values = processor(img, return_tensors="pt").pixel_values 
+generated_ids = model.generate(pixel_values, max_length=64)
+generated_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+generated_text = unicodedata.normalize("NFC", generated_text)
+print(generated_text)
+```