import gradio as gr import nltk import pytesseract from nltk.tokenize import sent_tokenize from transformers import MarianMTModel, MarianTokenizer nltk.download('punkt') OCR_TR_DESCRIPTION = '''# OCR Translate v0.2
OCR translation system based on Tesseract
''' # 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] # Função de escolha do modelo de tradução def model_choice(src, trg): model_name = f"Helsinki-NLP/opus-mt-tc-big-{src}-{trg}" tokenizer = MarianTokenizer.from_pretrained(model_name) model = MarianMTModel.from_pretrained(model_name) return tokenizer, model # Função de tradução def translate(input_text, trans_style): if not input_text: return "System prompt: There is no content to translate!" src, trg = trans_style.split("-") tokenizer, model = model_choice(src, trg) sentences = sent_tokenize(input_text) translated_text = "" for sentence in sentences: inputs = tokenizer.encode(sentence, return_tensors="pt", truncation=True, padding=True) translated = model.generate(inputs) translated_sentence = tokenizer.decode(translated[0], skip_special_tokens=True) translated_text += translated_sentence + " " return translated_text.strip() # 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 # 清除 def clear_content(): return None # 复制到剪贴板 def cp_text(input_text): # sudo apt-get install xclip try: pyclip.copy(input_text) except Exception as e: print("sudo apt-get install xclip") print(e) # 清除剪贴板 def cp_clear(): pyclip.clear() def main(): with gr.Blocks(css='style.css') as ocr_tr: gr.Markdown(OCR_TR_DESCRIPTION) # -------------- OCR 文字提取 -------------- with gr.Blocks(): with gr.Row(): gr.Markdown("### Step 01: Text Extraction") with gr.Row(): with gr.Column(): with gr.Row(): inputs_img = gr.Image(image_mode="RGB", sources="upload", type="pil", label="image") with gr.Row(): inputs_lang = gr.CheckboxGroup(choices=["por", "eng"], type="value", value=['eng'], label='language') with gr.Row(): clear_img_btn = gr.Button('Clear') ocr_btn = gr.Button(value='OCR Extraction', variant="primary") with gr.Column(): with gr.Row(): outputs_text = gr.Textbox(label="Extract content", lines=20) with gr.Row(): inputs_transStyle = gr.Radio(choices=["pt-en", "en-pt"], type="value", value="pt-en", label='translation mode') with gr.Row(): clear_text_btn = gr.Button('Clear') translate_btn = gr.Button(value='Translate', variant="primary") with gr.Row(): example_list = [["./data/test.png", ["eng"]], ["./data/test02.png", ["eng"]], ["./data/test03.png", ["por"]]] gr.Examples(example_list, [inputs_img, inputs_lang], outputs_text, ocr_tesseract, cache_examples=False) # -------------- 翻译 -------------- with gr.Blocks(): with gr.Row(): gr.Markdown("### Step 02: Translation") with gr.Row(): outputs_tr_text = gr.Textbox(label="Translate Content", lines=20) with gr.Row(): cp_clear_btn = gr.Button(value='Clear Clipboard') cp_btn = gr.Button(value='Copy to clipboard', 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]) # ---------------------- 翻译 ---------------------- translate_btn.click(fn=translate, inputs=[outputs_text, inputs_transStyle], outputs=[outputs_tr_text]) clear_text_btn.click(fn=clear_content, inputs=[], outputs=[outputs_text]) # ---------------------- 复制到剪贴板 ---------------------- 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()