Zengyf-CVer
commited on
Commit
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c6d26b8
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Parent(s):
3b93977
app update
Browse files- .gitignore +64 -0
- app.py +180 -0
- data/test.png +0 -0
- data/test02.png +0 -0
- data/test03.png +0 -0
- packages.txt +1 -0
- requirements.txt +8 -0
- style.css +7 -0
.gitignore
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# OCR Translate
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# 创建人:曾逸夫
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# 项目地址:https://gitee.com/CV_Lab/ocr-translate
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# 图片格式
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*.jpg
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*.jpeg
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*.png
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*.svg
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*.gif
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# 视频格式
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*.mp4
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*.avi
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.ipynb_checkpoints
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/__pycache__
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*/__pycache__
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# 日志格式
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*.log
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*.data
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*.txt
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# 生成文件
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*.pdf
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*.xlsx
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*.csv
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# 参数文件
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*.yaml
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*.json
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# 压缩文件格式
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*.zip
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*.tar
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*.tar.gz
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*.rar
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# 字体格式
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*.ttc
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*.ttf
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*.otf
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*.pkl
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# 模型文件
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*.pt
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*.db
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/flagged
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/run
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/opus-mt-en-zh
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!requirements.txt
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!cls_name/*
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!model_config/*
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!img_examples/*
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!data/*
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!requirements.txt
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!packages.txt
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!.pre-commit-config.yaml
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test.py
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test*.py
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app.py
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# OCR Translate v0.2
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# 创建人:曾逸夫
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# 创建时间:2022-07-19
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import os
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os.system("sudo apt-get install xclip")
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import gradio as gr
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import nltk
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import pyclip
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import pytesseract
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from nltk.tokenize import sent_tokenize
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from transformers import MarianMTModel, MarianTokenizer
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nltk.download('punkt')
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OCR_TR_DESCRIPTION = '''# OCR Translate v0.2
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<div id="content_align">OCR translation system based on Tesseract</div>'''
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# 图片路径
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img_dir = "./data"
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# 获取tesseract语言列表
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choices = os.popen('tesseract --list-langs').read().split('\n')[1:-1]
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# 翻译模型选择
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def model_choice(src="en", trg="zh"):
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# https://huggingface.co/Helsinki-NLP/opus-mt-zh-en
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# https://huggingface.co/Helsinki-NLP/opus-mt-en-zh
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model_name = f"Helsinki-NLP/opus-mt-{src}-{trg}" # 模型名称
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tokenizer = MarianTokenizer.from_pretrained(model_name) # 分词器
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model = MarianMTModel.from_pretrained(model_name) # 模型
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return tokenizer, model
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# tesseract语言列表转pytesseract语言
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def ocr_lang(lang_list):
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lang_str = ""
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lang_len = len(lang_list)
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if lang_len == 1:
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return lang_list[0]
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else:
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for i in range(lang_len):
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lang_list.insert(lang_len - i, "+")
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lang_str = "".join(lang_list[:-1])
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return lang_str
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# ocr tesseract
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def ocr_tesseract(img, languages):
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ocr_str = pytesseract.image_to_string(img, lang=ocr_lang(languages))
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return ocr_str
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# 清除
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def clear_content():
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return None
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# 复制到剪贴板
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def cp_text(input_text):
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# sudo apt-get install xclip
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try:
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pyclip.copy(input_text)
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except Exception as e:
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print("sudo apt-get install xclip")
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print(e)
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# 清除剪贴板
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def cp_clear():
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pyclip.clear()
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# 翻译
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def translate(input_text, inputs_transStyle):
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# 参考:https://huggingface.co/docs/transformers/model_doc/marian
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if input_text is None or input_text == "":
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return "System prompt: There is no content to translate!"
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# 选择翻译模型
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trans_src, trans_trg = inputs_transStyle.split("-")[0], inputs_transStyle.split("-")[1]
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tokenizer, model = model_choice(trans_src, trans_trg)
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translate_text = ""
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input_text_list = input_text.split("\n\n")
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translate_text_list_tmp = []
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for i in range(len(input_text_list)):
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if input_text_list[i] != "":
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translate_text_list_tmp.append(input_text_list[i])
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for i in range(len(translate_text_list_tmp)):
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translated_sub = model.generate(
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**tokenizer(sent_tokenize(translate_text_list_tmp[i]), return_tensors="pt", truncation=True, padding=True))
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tgt_text_sub = [tokenizer.decode(t, skip_special_tokens=True) for t in translated_sub]
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translate_text_sub = "".join(tgt_text_sub)
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translate_text = translate_text + "\n\n" + translate_text_sub
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return translate_text[2:]
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def main():
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with gr.Blocks(css='style.css') as ocr_tr:
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gr.Markdown(OCR_TR_DESCRIPTION)
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# -------------- OCR 文字提取 --------------
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with gr.Box():
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with gr.Row():
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gr.Markdown("### Step 01: Text extraction")
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with gr.Row():
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with gr.Column():
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with gr.Row():
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inputs_img = gr.Image(image_mode="RGB", source="upload", type="pil", label="image")
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with gr.Row():
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inputs_lang = gr.CheckboxGroup(choices=["chi_sim", "eng"],
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type="value",
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value=['eng'],
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label='language')
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with gr.Row():
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clear_img_btn = gr.Button('Clear')
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ocr_btn = gr.Button(value='OCR extraction', variant="primary")
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with gr.Column():
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with gr.Row():
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outputs_text = gr.Textbox(label="Extract content", lines=20)
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with gr.Row():
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inputs_transStyle = gr.Radio(choices=["zh-en", "en-zh"],
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type="value",
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value="zh-en",
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label='translation mode')
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with gr.Row():
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clear_text_btn = gr.Button('Clear')
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translate_btn = gr.Button(value='translate', variant="primary")
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with gr.Row():
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example_list = [["./data/test.png", ["eng"]], ["./data/test02.png", ["eng"]],
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["./data/test03.png", ["chi_sim"]]]
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gr.Examples(example_list, [inputs_img, inputs_lang], outputs_text, ocr_tesseract, cache_examples=False)
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# -------------- 翻译 --------------
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with gr.Box():
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with gr.Row():
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gr.Markdown("### Step 02: Translation")
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with gr.Row():
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outputs_tr_text = gr.Textbox(label="translate content", lines=20)
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with gr.Row():
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cp_clear_btn = gr.Button(value='clear clipboard')
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cp_btn = gr.Button(value='copy to clipboard', variant="primary")
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# ---------------------- OCR Tesseract ----------------------
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ocr_btn.click(fn=ocr_tesseract, inputs=[inputs_img, inputs_lang], outputs=[
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outputs_text,])
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clear_img_btn.click(fn=clear_content, inputs=[], outputs=[inputs_img])
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# ---------------------- 翻译 ----------------------
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translate_btn.click(fn=translate, inputs=[outputs_text, inputs_transStyle], outputs=[outputs_tr_text])
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clear_text_btn.click(fn=clear_content, inputs=[], outputs=[outputs_text])
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# ---------------------- 复制到剪贴板 ----------------------
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cp_btn.click(fn=cp_text, inputs=[outputs_tr_text], outputs=[])
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cp_clear_btn.click(fn=cp_clear, inputs=[], outputs=[])
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ocr_tr.launch(inbrowser=True)
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if __name__ == '__main__':
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main()
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data/test.png
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data/test02.png
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data/test03.png
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packages.txt
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tesseract-ocr-all
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requirements.txt
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pytesseract>=0.3.9
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pyclip>=0.6.0
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gradio>=3.0.18
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nltk>=3.7
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sentencepiece>=0.1.96
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transformers>=4.20.0
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sacremoses>=0.0.53
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torch>=1.11.0
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style.css
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h1 {
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text-align: center;
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}
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#content_align {
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text-align: center;
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}
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