# -*- coding: utf-8 -*-
#Author: Lart Pang (https://github.com/lartpang) 

import cv2
import numpy as np

from utils.ops import minmax


def read_gray_array(path, div_255=False, to_normalize=False, thr=-1, dtype=np.float32) -> np.ndarray:
    """
    1. read the binary image with the suffix `.jpg` or `.png`
        into a grayscale ndarray
    2. (to_normalize=True) rescale the ndarray to [0, 1]
    3. (thr >= 0) binarize the ndarray with `thr`
    4. return a gray ndarray (np.float32)
    """
    assert path.endswith(".jpg") or path.endswith(".png"), path
    assert not div_255 or not to_normalize, path
    gray_array = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
    assert gray_array is not None, f"Image Not Found: {path}"

    if div_255:
        gray_array = gray_array / 255

    if to_normalize:
        gray_array = minmax(gray_array, up_bound=255)

    if thr >= 0:
        gray_array = gray_array > thr

    return gray_array.astype(dtype)


def read_color_array(path: str):
    assert path.endswith(".jpg") or path.endswith(".png")
    bgr_array = cv2.imread(path, cv2.IMREAD_COLOR)
    assert bgr_array is not None, f"Image Not Found: {path}"
    rgb_array = cv2.cvtColor(bgr_array, cv2.COLOR_BGR2RGB)
    return rgb_array