# /////////////////////////// Custom Dataset ///////////////////////////#
import numpy as np
import os.path
import cv2
import matplotlib.pyplot as plt

class IdentityMetadata():
    def __init__(self, base, name, file):
        # dataset base directory
        self.base = base
        # identity name
        self.name = name
        # image file name
        self.file = file

    def __repr__(self):
        return self.image_path()

    def image_path(self):
        return os.path.join(self.base, self.name, self.file)


def load_metadata(path):
    metadata = []
    for i in os.listdir(path):
        for f in os.listdir(os.path.join(path, i)):
            metadata.append(IdentityMetadata(path, i, f))
    return np.array(metadata)


metadata = load_metadata('Kaggle Dataset/Train')



def load_image(path):
    img = cv2.imread(path, 1)
    # OpenCV loads images with color channels
    # in BGR order. So we need to reverse them
    return img[...,::-1]

# Load and Plot an image from Dataset
sample_image = load_image(metadata[11].image_path())
plt.imshow(sample_image)

for i in range(metadata.size):
    print(i)
    #current_image = load_image(metadata[11].image_path())
    #plt.imshow(current_image)