import numpy as np
import os
from skimage.io import imread
import cv2 as cv
from pathlib import Path

def load_data(input_dir, newSize=(64,64)):
    image_path = Path(input_dir)
    file_names = os.listdir(image_path)
    categories_name = []
    categories_count=[]
    count = 0
    n = file_names[0]
    for name in file_names:
        if name != n:
            categories_count.append(count)
            n = name
            count = 1
        else:
            count += 1
        if not name in categories_name:
            categories_name.append(name)
    categories_count.append(count)
    test_img = []
    labels=[]

    for n in file_names:
        p = image_path / n
        img = imread(p) # zwraca ndarry postaci xSize x ySize x colorDepth
        img = cv.resize(img, newSize, interpolation=cv.INTER_AREA) # zwraca ndarray
        img = img / 255 # type: ignore #normalizacja
        test_img.append(img)
        labels.append(n)

    X={}
    X["values"] = np.array(test_img)
    X["categories_name"] = categories_name
    X["categories_count"] = categories_count
    X["labels"]=labels
    return X

data = load_data('test_set')
print(data['categories_name'])
print(data['categories_count'])
print(data['labels'])
print(list(data["values"]))