backend/app/utils/preprocessor.py

import cv2
import numpy as np
from PIL import Image
import io

def preprocess_image(image_bytes: bytes, max_dim: int = 1500) -> Image.Image:
    np_img = np.frombuffer(image_bytes, np.uint8)
    img = cv2.imdecode(np_img, cv2.IMREAD_COLOR)
    h, w = img.shape[:2]
    if max(h, w) > max_dim:
        scale = max_dim / max(h, w)
        img = cv2.resize(img, (int(w*scale), int(h*scale)), interpolation=cv2.INTER_AREA)
    img = cv2.fastNlMeansDenoisingColored(img, None, 10, 10, 7, 21)
    lab = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
    l, a, b = cv2.split(lab)
    clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
    l = clahe.apply(l)
    img = cv2.merge((l, a, b))
    img = cv2.cvtColor(img, cv2.COLOR_LAB2BGR)
    _, encoded = cv2.imencode('.jpg', img)
    return Image.open(io.BytesIO(encoded.tobytes())).convert("RGB")