training_data.py

def load_data():
    images, labels = [], []
    
    for dataset in datasets:
        
        for folder in os.listdir(dataset):
            label = class_name_labels[folder]
            
            for file in tqdm(os.listdir(os.path.join(dataset,folder))):
                
                img_path = os.path.join(dataset,folder,file)
                
                img = cv2.imread(img_path)
                img = cv2.resize(img, (96,96))
                
                images.append(img)
                labels.append(label)
                pass
            pass
        
        images = np.array(images,dtype=np.float32)/255.0
        labels = np.array(labels,dtype=np.float32)
        pass
    
    return (images, labels)
    pass

(images, labels) = load_data()
 images.shape, labels.shape