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同步操作将从 CV_Lab/OCR-Translate 强制同步,此操作会覆盖自 Fork 仓库以来所做的任何修改,且无法恢复!!!
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# OCR Translate v0.2
# 创建人:曾逸夫
# 创建时间:2022-07-19
import os
os.system("pip install gradio==3.0.26")
import gradio as gr
import nltk
import pyclip
import pytesseract
from nltk.tokenize import sent_tokenize
from transformers import MarianMTModel, MarianTokenizer
nltk.download('punkt')
OCR_TR_DESCRIPTION = '''# OCR Translate v0.2
<div id="content_align">基于Tesseract的OCR翻译系统</div>'''
# 图片路径
img_dir = "./data"
# 获取tesseract语言列表
choices = os.popen('tesseract --list-langs').read().split('\n')[1:-1]
# 翻译模型选择
def model_choice(src="en", trg="zh"):
# https://huggingface.co/Helsinki-NLP/opus-mt-en-zh
model_name = f"opus-mt-{src}-{trg}" # 模型名称
tokenizer = MarianTokenizer.from_pretrained(model_name) # 分词器
model = MarianMTModel.from_pretrained(model_name) # 模型
return tokenizer, model
# tesseract语言列表转pytesseract语言
def ocr_lang(lang_list):
lang_str = ""
lang_len = len(lang_list)
if lang_len == 1:
return lang_list[0]
else:
for i in range(lang_len):
lang_list.insert(lang_len - i, "+")
lang_str = "".join(lang_list[:-1])
return lang_str
# ocr tesseract
def ocr_tesseract(img, languages):
ocr_str = pytesseract.image_to_string(img, lang=ocr_lang(languages))
return ocr_str
# 示例
def set_example_image(example: list) -> dict:
return gr.Image.update(value=example[0])
# 清除
def clear_content():
return None
# 复制到剪贴板
def cp_text(input_text):
# sudo apt-get install xclip
pyclip.copy(input_text)
# 清除剪贴板
def cp_clear():
pyclip.clear()
# 翻译
def translate(input_text):
# 参考:https://huggingface.co/docs/transformers/model_doc/marian
if input_text is None or input_text == "":
return "系统提示:没有可翻译的内容!"
tokenizer, model = model_choice()
translate_text = ""
input_text_list = input_text.split("\n\n")
translate_text_list_tmp = []
for i in range(len(input_text_list)):
if input_text_list[i] != "":
translate_text_list_tmp.append(input_text_list[i])
for i in range(len(translate_text_list_tmp)):
translated_sub = model.generate(
**tokenizer(sent_tokenize(translate_text_list_tmp[i]), return_tensors="pt", truncation=True, padding=True))
tgt_text_sub = [tokenizer.decode(t, skip_special_tokens=True) for t in translated_sub]
translate_text_sub = "".join(tgt_text_sub)
translate_text = translate_text + "\n\n" + translate_text_sub
return translate_text[2:]
def main():
with gr.Blocks(css='style.css') as ocr_tr:
gr.Markdown(OCR_TR_DESCRIPTION)
# -------------- OCR 文字提取 --------------
with gr.Box():
with gr.Row():
gr.Markdown("### Step 01: 文字提取")
with gr.Row():
with gr.Column():
with gr.Row():
inputs_img = gr.Image(image_mode="RGB", source="upload", type="pil", label="图片")
with gr.Row():
inputs_lang = gr.CheckboxGroup(choices=["chi_sim", "eng"],
type="value",
value=['eng'],
label='语言')
# inputs_lang = gr.CheckboxGroup(choices=choices, type="value", value=['eng'], label='语言')
with gr.Row():
clear_img_btn = gr.Button('Clear')
ocr_btn = gr.Button(value='OCR 提取', variant="primary")
with gr.Column():
imgs_path = sorted(os.listdir(img_dir))
example_images = gr.Dataset(components=[inputs_img],
samples=[[f"{img_dir}/{i}"] for i in imgs_path])
# -------------- 翻译 --------------
with gr.Box():
with gr.Row():
gr.Markdown("### Step 02: 翻译")
with gr.Row():
with gr.Column():
with gr.Row():
outputs_text = gr.Textbox(label="提取内容", lines=20)
with gr.Row():
clear_text_btn = gr.Button('Clear')
translate_btn = gr.Button(value='翻译', variant="primary")
with gr.Column():
with gr.Row():
outputs_tr_text = gr.Textbox(label="翻译内容", lines=20)
with gr.Row():
cp_clear_btn = gr.Button(value='清除剪贴板')
cp_btn = gr.Button(value='复制到剪贴板', variant="primary")
# ---------------------- OCR Tesseract ----------------------
ocr_btn.click(fn=ocr_tesseract, inputs=[inputs_img, inputs_lang], outputs=[
outputs_text,])
clear_img_btn.click(fn=clear_content, inputs=[], outputs=[inputs_img])
example_images.click(fn=set_example_image, inputs=[
example_images,], outputs=[
inputs_img,])
# ---------------------- OCR Tesseract ----------------------
translate_btn.click(fn=translate, inputs=[outputs_text], outputs=[outputs_tr_text])
clear_text_btn.click(fn=clear_content, inputs=[], outputs=[outputs_text])
cp_btn.click(fn=cp_text, inputs=[outputs_tr_text], outputs=[])
cp_clear_btn.click(fn=cp_clear, inputs=[], outputs=[])
ocr_tr.launch(inbrowser=True)
if __name__ == '__main__':
main()
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