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