dataloader.py

from keras.utils.data_utils import Sequence
import requests
import io

class BatchSequence(Sequence):
    def __init__(self, x_set, y_set, batch_size=32, image_size=228):
        self.x, self.y = x_set, y_set
        self.batch_size = batch_size
        self.image_size = image_size

    def __len__(self):
        return int(np.ceil(len(self.x) / float(self.batch_size)))

    def __getitem__(self, idx):
        batch_x = self.x[idx * self.batch_size:(idx + 1) * self.batch_size]
        batch_y = self.y[idx * self.batch_size:(idx + 1) * self.batch_size]
        images = [self.url_to_image(file_name) for file_name in batch_x]
        return np.array(images), np.array(batch_y)
    
    def url_to_image(self, url):
        try:
            response = requests.get(url)
            image = Image.open(io.BytesIO(response.content))
            image.thumbnail((self.image_size, self.image_size))
            image = np.array(image)
        except Exception as e:
            output = [1]*(self.image_size*self.image_size*3)
            output = np.array(output).reshape(self.image_size,self.image_size,3).astype('uint8')
            image = Image.fromarray(output).convert('RGB')
        return image