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| # import os | |
| # os.system("sudo apt-get install xclip") | |
| # import nltk | |
| # from fastapi import FastAPI, File, Request, UploadFile, Body, Depends, HTTPException | |
| # from fastapi.security.api_key import APIKeyHeader | |
| # from typing import Optional, Annotated | |
| # from fastapi.encoders import jsonable_encoder | |
| # from PIL import Image | |
| # from io import BytesIO | |
| # import pytesseract | |
| # from nltk.tokenize import sent_tokenize | |
| # from transformers import MarianMTModel, MarianTokenizer | |
| # nltk.download('punkt') | |
| # API_KEY = os.environ.get("API_KEY") | |
| # app = FastAPI() | |
| # api_key_header = APIKeyHeader(name="api_key", auto_error=False) | |
| # def get_api_key(api_key: Optional[str] = Depends(api_key_header)): | |
| # if api_key is None or api_key != API_KEY: | |
| # raise HTTPException(status_code=401, detail="Unauthorized access") | |
| # return api_key | |
| # # Image path | |
| # img_dir = "./data" | |
| # # Get tesseract language list | |
| # choices = os.popen('tesseract --list-langs').read().split('\n')[1:-1] | |
| # # Convert tesseract language list to pytesseract language | |
| # 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): | |
| # print("[img]", img) | |
| # print("[languages]", languages) | |
| # ocr_str = pytesseract.image_to_string(img, lang=ocr_lang(languages)) | |
| # return ocr_str | |
| # @app.post("/api/ocr", response_model=dict) | |
| # async def ocr( | |
| # api_key: str = Depends(get_api_key), | |
| # image: UploadFile = File(...), | |
| # # languages: list = Body(["eng"]) | |
| # ): | |
| # try: | |
| # content = await image.read() | |
| # image = Image.open(BytesIO(content)) | |
| # print("[image]",image) | |
| # if hasattr(pytesseract, "image_to_string"): | |
| # print("Image to string function is available") | |
| # # print(pytesseract.image_to_string(image, lang = 'eng')) | |
| # text = ocr_tesseract(image, ['eng']) | |
| # else: | |
| # print("Image to string function is not available") | |
| # # text = pytesseract.image_to_string(image, lang="+".join(languages)) | |
| # except Exception as e: | |
| # return {"error": str(e)}, 500 | |
| # return {"ImageText": "text"} | |
| # @app.post("/api/translate", response_model=dict) | |
| # async def translate( | |
| # api_key: str = Depends(get_api_key), | |
| # text: str = Body(...), | |
| # src: str = "en", | |
| # trg: str = "zh", | |
| # ): | |
| # if api_key != API_KEY: | |
| # return {"error": "Invalid API key"}, 401 | |
| # tokenizer, model = get_model(src, trg) | |
| # translated_text = "" | |
| # for sentence in sent_tokenize(text): | |
| # translated_sub = model.generate(**tokenizer(sentence, return_tensors="pt"))[0] | |
| # translated_text += tokenizer.decode(translated_sub, skip_special_tokens=True) + "\n" | |
| # return jsonable_encoder({"translated_text": translated_text}) | |
| # def get_model(src: str, trg: str): | |
| # model_name = f"Helsinki-NLP/opus-mt-{src}-{trg}" | |
| # tokenizer = MarianTokenizer.from_pretrained(model_name) | |
| # model = MarianMTModel.from_pretrained(model_name) | |
| # return tokenizer, model | |
| # OCR Translate v0.2 | |
| import os | |
| os.system("sudo apt-get install xclip") | |
| # import gradio as gr | |
| import nltk | |
| import pyclip | |
| import pytesseract | |
| from nltk.tokenize import sent_tokenize | |
| from transformers import MarianMTModel, MarianTokenizer | |
| # Added below code | |
| from fastapi import FastAPI, File, Request, UploadFile, Body, Depends, HTTPException | |
| from fastapi.security.api_key import APIKeyHeader | |
| from typing import Optional, Annotated | |
| from fastapi.encoders import jsonable_encoder | |
| from PIL import Image | |
| from io import BytesIO | |
| API_KEY = os.environ.get("API_KEY") | |
| app = FastAPI() | |
| api_key_header = APIKeyHeader(name="api_key", auto_error=False) | |
| def get_api_key(api_key: Optional[str] = Depends(api_key_header)): | |
| if api_key is None or api_key != API_KEY: | |
| raise HTTPException(status_code=401, detail="Unauthorized access") | |
| return api_key | |
| async def ocr( | |
| api_key: str = Depends(get_api_key), | |
| image: UploadFile = File(...), | |
| # languages: list = Body(["eng"]) | |
| ): | |
| try: | |
| content = await image.read() | |
| image = Image.open(BytesIO(content)) | |
| print("[image]",image) | |
| if hasattr(pytesseract, "image_to_string"): | |
| print("Image to string function is available") | |
| # print(pytesseract.image_to_string(image, lang = 'eng')) | |
| text = ocr_tesseract(image, ['eng']) | |
| else: | |
| print("Image to string function is not available") | |
| # text = pytesseract.image_to_string(image, lang="+".join(languages)) | |
| except Exception as e: | |
| return {"error": str(e)}, 500 | |
| return {"ImageText": "text"} | |
| nltk.download('punkt') | |
| OCR_TR_DESCRIPTION = '''# OCR Translate v0.2 | |
| <div id="content_align">OCR translation system based on Tesseract</div>''' | |
| # Image path | |
| img_dir = "./data" | |
| # Get tesseract language list | |
| choices = os.popen('tesseract --list-langs').read().split('\n')[1:-1] | |
| # Translation model selection | |
| def model_choice(src="en", trg="zh"): | |
| # https://huggingface.co/Helsinki-NLP/opus-mt-zh-en | |
| # https://huggingface.co/Helsinki-NLP/opus-mt-en-zh | |
| model_name = f"Helsinki-NLP/opus-mt-{src}-{trg}" # Model name | |
| tokenizer = MarianTokenizer.from_pretrained(model_name) # tokenizer | |
| model = MarianMTModel.from_pretrained(model_name) # Model | |
| return tokenizer, model | |
| # Convert tesseract language list to pytesseract language | |
| 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): | |
| print("[img]", img) | |
| print("[languages]", languages) | |
| ocr_str = pytesseract.image_to_string(img, lang=ocr_lang(languages)) | |
| return ocr_str | |
| # Clear | |
| def clear_content(): | |
| return None | |
| # copy to clipboard | |
| 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) | |
| # clear clipboard | |
| def cp_clear(): | |
| pyclip.clear() | |
| # translate | |
| def translate(input_text, inputs_transStyle): | |
| # reference：https://huggingface.co/docs/transformers/model_doc/marian | |
| if input_text is None or input_text == "": | |
| return "System prompt: There is no content to translate!" | |
| # Select translation model | |
| trans_src, trans_trg = inputs_transStyle.split("-")[0], inputs_transStyle.split("-")[1] | |
| tokenizer, model = model_choice(trans_src, trans_trg) | |
| 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 text extraction -------------- | |
| # with gr.Box(): | |
| # 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", source="upload", type="pil", label="image") | |
| # with gr.Row(): | |
| # inputs_lang = gr.CheckboxGroup(choices=["chi_sim", "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=["zh-en", "en-zh"], | |
| # type="value", | |
| # value="zh-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", ["chi_sim"]]] | |
| # gr.Examples(example_list, [inputs_img, inputs_lang], outputs_text, ocr_tesseract, cache_examples=False) | |
| # # -------------- translate -------------- | |
| # with gr.Box(): | |
| # 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]) | |
| # # ---------------------- translate ---------------------- | |
| # 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]) | |
| # # ---------------------- copy to clipboard ---------------------- | |
| # 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() | |