from dotenv import load_dotenv
import io
import boto3
from paddleocr import PaddleOCR
import os
import pytesseract
from PIL import ImageFilter
import numpy as np

def textract_ocr(image, box):
    load_dotenv()
    x1, y1, x2, y2 = box
    cropped_image = image.crop((x1, y1, x2, y2))
    cropped_image = cropped_image.convert("L")
    img_bytes = io.BytesIO()
    cropped_image.save(img_bytes, format='PNG')
    img_bytes = img_bytes.getvalue()
    client = boto3.client('textract', region_name='eu-west-3', aws_access_key_id=os.getenv("aws_access_key_id"),
                          aws_secret_access_key=os.getenv('aws_secret_access_key')
    )

    response = client.detect_document_text(Document={'Bytes': img_bytes})
    blocks = response['Blocks']
    texttract = ""
    line_confidence = {}
    for block in blocks:
        if(block['BlockType'] == 'LINE'):
            line_confidence[block['Text']] = block['Confidence']
            texttract+= block['Text']+"\n"
    
    return texttract 



def paddle_ocr(image,box):
    x1, y1, x2, y2 = box
    cropped_image = image.crop((x1, y1, x2, y2))
    cropped_image = np.array(cropped_image)
    ocr = PaddleOCR(use_angle_cls=False, lang='latin')
    result = ocr.ocr(cropped_image, cls=False)
    text= ""
    if result [0] != None:
        result.sort(key=lambda x: (x[0][0][1], x[0][0][0]))
        text = [x[1][0] for x in result[0]]
    return "\n".join(text)



def tesseract_ocr(image, box):
    target_dpi = 300
    x1, y1, x2, y2 = box
    cropped_image = image.crop((x1, y1, x2, y2))
    cropped_image = cropped_image.convert("L")
   
    current_dpi = cropped_image.info['dpi'][0] if 'dpi' in image.info else None

    if current_dpi:
        scale_factor = target_dpi / current_dpi
    else:
        
        scale_factor = 1.0
    binarized_image = cropped_image.filter(ImageFilter.MedianFilter())
    binarized_image = binarized_image.point(lambda p: p > 180 and 255)
    text = pytesseract.image_to_string(binarized_image, config="--psm 6")
    return text