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Add app
Browse files- app.py +41 -0
- examples/01.png +0 -0
- examples/02.png +0 -0
- examples/03.png +0 -0
- examples/04.png +0 -0
- examples/05.png +0 -0
- examples/06.png +0 -0
- examples/07.png +0 -0
- requirements.txt +3 -0
app.py
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import numpy as np
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import gradio as gr
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from transformers import AutoFeatureExtractor, AutoTokenizer, VisionEncoderDecoderModel
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import re
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import jaconv
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#load model
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model_path = "kha-white/manga-ocr-base"
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feature_extractor = AutoFeatureExtractor.from_pretrained(model_path)
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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model = VisionEncoderDecoderModel.from_pretrained(model_path)
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def post_process(text):
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text = ''.join(text.split())
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text = text.replace('…', '...')
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text = re.sub('[・.]{2,}', lambda x: (x.end() - x.start()) * '.', text)
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text = jaconv.h2z(text, ascii=True, digit=True)
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return text
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def infer(image):
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image = image.convert('L').convert('RGB')
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pixel_values = feature_extractor(image, return_tensors="pt").pixel_values
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ouput = model.generate(pixel_values)[0]
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text = tokenizer.decode(ouput, skip_special_tokens=True)
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text = post_process(text)
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return text
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iface = gr.Interface(
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fn=infer,
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inputs=[gr.inputs.Image(label="Input", type="pil")],
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outputs="text",
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layout="horizontal",
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theme="huggingface",
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title="Optical character recognition for Japanese text",
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description="A simple interface for OCR from Japanese manga",
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article= "Author: <a href=\"https://huggingface.co/vumichien\">Vu Minh Chien</a>. ",
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allow_flagging='never',
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)
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iface.launch(enable_queue=True, share=True, debug=True)
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examples/01.png
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examples/02.png
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examples/03.png
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examples/04.png
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examples/05.png
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examples/06.png
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examples/07.png
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requirements.txt
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fugashi
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unidic_lite
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jaconv
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