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Update app.py
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app.py
CHANGED
@@ -1,43 +1,64 @@
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#
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#
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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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img_dir = "./data"
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#
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choices = os.popen('tesseract --list-langs').read().split('\n')[1:-1]
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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}" #
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tokenizer = MarianTokenizer.from_pretrained(model_name) #
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model = MarianMTModel.from_pretrained(model_name) #
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return tokenizer, model
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# tesseract
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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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return lang_str
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def ocr_tesseract(img, languages):
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return ocr_str
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#
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def clear_content():
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return None
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#
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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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@@ -105,21 +135,36 @@ def translate(input_text, inputs_transStyle):
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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.
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with gr.Row():
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gr.Markdown("### Step 01:
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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",
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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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label='language')
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with gr.Row():
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clear_img_btn = gr.Button('
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ocr_btn = gr.Button(value='
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with gr.Column():
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with gr.Row():
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outputs_text = gr.Textbox(label="
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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='
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with gr.Row():
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clear_text_btn = gr.Button('
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translate_btn = gr.Button(value='
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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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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.
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with gr.Row():
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gr.Markdown("### Step 02:
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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='
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cp_btn = gr.Button(value='
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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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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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# ----------------------
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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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# AI Meeting note parser
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# Author:Alec Li
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# Date:2024-01-26
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# Location: Richmond Hospital Canada
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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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import openai
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nltk.download('punkt')
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OCR_TR_DESCRIPTION = '''
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<div id="content_align">
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<span style="color:darkred;font-size:32px;font-weight:bold">
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模多多会议记录总结神器
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</span>
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</div>
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<div id="content_align">
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<span style="color:blue;font-size:16px;font-weight:bold">
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会议记录拍照 -> 转文字 -> 翻译 -> 提炼会议纪要 -> 识别待办事项 -> 分配任务
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</div>
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<div id="content_align" style="margin-top: 10px;">
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作者: Dr. Alec Li
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</div>
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'''
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# Image path
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img_dir = "./data"
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# Get tesseract language list
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choices = os.popen('tesseract --list-langs').read().split('\n')[1:-1]
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# Translation model selection
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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}" # Model name
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tokenizer = MarianTokenizer.from_pretrained(model_name) # Tokenizer
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model = MarianMTModel.from_pretrained(model_name) # model
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return tokenizer, model
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# Convert tesseract language list to pytesseract language
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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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return lang_str
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import pytesseract
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import os
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# Set Tesseract executable path in Colab virtal environment
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pytesseract.pytesseract.tesseract_cmd = "/usr/bin/tesseract"
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# Set up the Tesseract data directory
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os.environ["TESSDATA_PREFIX"] = "/usr/share/tesseract-ocr/4.00/tessdata"
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def ocr_tesseract(img, languages):
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custom_config = f'--oem 3 --psm 6 -l {ocr_lang(languages)}'
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ocr_str = pytesseract.image_to_string(img, config=custom_config)
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return ocr_str
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# Clear content
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def clear_content():
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return None
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# copy to clipboard
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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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return translate_text[2:]
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# 在 https://platform.openai.com/signup 注册并获取 API 密钥
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openai.api_key = "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"
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def generate_summary(text_input):
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": text_input}
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]
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)
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summary = response["choices"][0]["message"]["content"].strip()
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return summary
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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.Column():
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with gr.Row():
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gr.Markdown("### Step 01: 文本抽取")
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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", 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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label='language')
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with gr.Row():
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clear_img_btn = gr.Button('清除')
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ocr_btn = gr.Button(value='图片文本抽取', 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="抽取的文本", 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='翻译模式')
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with gr.Row():
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clear_text_btn = gr.Button('清除')
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translate_btn = gr.Button(value='翻译', variant="primary")
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# Add a text box to display the generated summary
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with gr.Row():
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outputs_summary_text = gr.Textbox(label="生成的摘要", lines=20)
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with gr.Row():
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with gr.Row():
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generate_summary_btn = gr.Button('生成摘要', variant="primary")
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with gr.Row():
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clear_summary_btn = gr.Button('清除摘要')
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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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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.Column():
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with gr.Row():
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gr.Markdown("### Step 02: 翻译")
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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='清除剪贴板')
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cp_btn = gr.Button(value='复制到剪贴板', 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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# ---------------------- Summarization ----------------------
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# To update the click event of the button, use generate_summary directly
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generate_summary_btn.click(fn=generate_summary, inputs=[outputs_text],
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outputs=[outputs_summary_text])
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clear_summary_btn.click(fn=clear_content, inputs=[], outputs=[outputs_summary_text])
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# ---------------------- Translate ----------------------
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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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# ---------------------- Copy to clipboard ----------------------
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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, share=True)
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if __name__ == '__main__':
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main()
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