Train Validation data split - labels available but no classes

Question

my studies project is to develop a neural network to recognize text on license plates. Therefore, I found the ReId-dataset at https://medusa.fit.vutbr.cz/traffic/research-topics

Answer 1

Question 1 and 2:

For reading the images, imread from matplotlib.pyplot can be used as shown in the example, this does not require any classes to be set.

Question 3:

The labels and images can be brought together by storing the corresponding license plate number in an output array (y in the example) for each image (stored in the xs array in the example) in the data array. You don't necessarily need to merge them.

Hope I helped!

import os
import matplotlib.pyplot as plt
import numpy as np 
import pandas as pd

xs, y = [], []
main_dir = './sample/dataset' # the main directory 
label_data = pd.read_csv('labels.csv')

for folder in os.listdir(main_dir):
    for img in os.listdir(os.path.join(main, folder)):
        arr = plt.imread(os.path.join(main, folder) + img)
        xs.append(arr)
        y.append(label_data[label_data['image_path'] == os.path.join(folder, img)]['lp'])
                #^ this part can be changed depending on the exact format of your label data file.

# then you can convert them into numpy arrays and reshape them as you need.
xs = np.array(xs)
y = np.array(y)