# import os
# 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
# import io
# import cv2
# import numpy as np
# import pytesseract
# from nltk.tokenize import sent_tokenize
# from transformers import MarianMTModel, MarianTokenizer

# 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

# @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:
#         print("[1]",os.popen(f'cat /etc/debian_version').read())
#         print("[2]",os.popen(f'cat /etc/issue').read())
#         print("[3]",os.popen(f'apt search tesseract').read())
#         # content = await image.read()
#         # image = Image.open(BytesIO(content))
#         image_stream = io.BytesIO(image)
#         image_stream.seek(0)
#         file_bytes = np.asarray(bytearray(image_stream.read()), dtype=np.uint8)
#         frame = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
#         # label = read_img(frame)
#         print("[image]",frame)
#         if hasattr(pytesseract, "image_to_string"):
#             print("Image to string function is available")
#         else:
#             print("Image to string function is not available")
#         # text = pytesseract.image_to_string(image, lang="+".join(languages))
#         # text = pytesseract.image_to_string(image, lang = 'eng')
#     except Exception as e:
#         return {"error": str(e)}, 500

#     # return jsonable_encoder({"text": text})
#     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


import numpy as np
import sys, os
from fastapi import FastAPI, UploadFile, File
from starlette.requests import Request
import io
import cv2
import pytesseract
from pydantic import BaseModel
def read_img(img):
    print("[img]", img)
 # text = pytesseract.image_to_string(img)
    text = 'bhooo'
    return(text)
 
app = FastAPI()
class ImageType(BaseModel):
 url: str
@app.post("/api/ocr", response_model=dict)
async def ocr(request: Request,
              file: bytes = File(...)
             ):
# if request.method == "POST":
    try:
        image_stream = io.BytesIO(file)
        image_stream.seek(0)
        file_bytes = np.asarray(bytearray(image_stream.read()), dtype=np.uint8)
        frame = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
        label = read_img(frame)
        print("[label]",label)
    except Exception as e:
        return {"error": str(e)}, 500
    return {"ImageText" : label}