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| import base64 | |
| import json | |
| from io import BytesIO | |
| import pandas as pd | |
| from PIL import Image | |
| import gradio as gr | |
| import requests | |
| def ocr(image): | |
| image = Image.open(image) | |
| img_buffer = BytesIO() | |
| image.save(img_buffer, format=image.format) | |
| byte_data = img_buffer.getvalue() | |
| base64_bytes = base64.b64encode(byte_data) # bytes | |
| base64_str = base64_bytes.decode() | |
| url = "https://www.modelscope.cn/api/v1/studio/damo/ofa_ocr_pipeline/gradio/api/predict/" | |
| payload = json.dumps({ | |
| "data": [f"data:image/jpeg;base64,{base64_str}"], | |
| "dataType": ["image"] | |
| }) | |
| headers = { | |
| 'Content-Type': 'application/json' | |
| } | |
| response = requests.request("POST", url, headers=headers, data=payload) | |
| jobj = json.loads(response.text) | |
| out_img_base64 = jobj['data'][0].replace('data:image/png;base64,','') | |
| out_img = Image.open(BytesIO(base64.urlsafe_b64decode(out_img_base64))) | |
| ocr_result = jobj['data'][1]['data'] | |
| result = pd.DataFrame(ocr_result, columns=['Box ID', 'Text']) | |
| return out_img, result | |
| title = "Chinese OCR" | |
| description = """<p>Gradio Demo for OFA-OCR for Chinese text recognition. <br><br> | |
| Upload your own image or click any one of the examples, and click "Submit" and then wait for the generated OCR result. <br> | |
| 中文OCR体验区。欢迎上传图片，静待检测文字返回~<br><br> | |
| Paper: <a href='https://arxiv.org/abs/2212.09297'>https://arxiv.org/abs/2212.09297</a> <br> | |
| Github: <a href='https://github.com/OFA-Sys/Chinese-CLIP'>https://github.com/OFA-Sys/OFA</a> <br><br> | |
| You can duplicate this space and run it privately: <a href='https://huggingface.co/spaces/OFA-Sys/chinese-clip-zero-shot-image-classification?duplicate=true'><img src='https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14' alt='Duplicate Space'></a></p>""" | |
| article = "<p style='text-align: center'><a href='https://github.com/OFA-Sys/OFA' target='_blank'>OFA Github " \ | |
| "Repo</a></p> " | |
| examples = [['shupai.png'], ['chinese.jpg'], ['gaidao.jpeg'],['qiaodaima.png']] | |
| io = gr.Interface(fn=ocr, inputs=gr.inputs.Image(type='filepath', label='Image'), | |
| examples=examples, | |
| outputs=[gr.outputs.Image(type='pil', label='Image'), | |
| gr.outputs.Dataframe(headers=['Box ID', 'Text'], type='pandas', label='OCR Results')], | |
| title=title, description=description, article=article) | |
| io.launch() |