How to use 'keras imagedatagenerator' in Python

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99def get_batches(dirname, gen=image.ImageDataGenerator(), shuffle=True, batch_size=4, class_mode='categorical',
100 target_size=(224,224)):
101 return gen.flow_from_directory(dirname, target_size=target_size,
102 class_mode=class_mode, shuffle=shuffle, batch_size=batch_size)
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336def generator(data, batch_size=cfg.BATCH_SIZE):
337 num_records = len(data)
338
339 while True:
340 #shuffle again for good measure
341 shuffle(data)
342
343 for offset in range(0, num_records, batch_size):
344 batch_data = data[offset:offset+batch_size]
345
346 if len(batch_data) != batch_size:
347 break
348
349 b_inputs_img = []
350 b_inputs_imu = []
351 b_labels = []
352
353 for seq in batch_data:
354 inputs_img = []
355 labels = []
356 for record in seq:
357 #get image data if we don't already have it
358 if record['img_data'] is None:
359 record['img_data'] = np.array(Image.open(record['image_path']))
360
361 inputs_img.append(record['img_data'])
362 labels.append(seq[-1]['target_output'])
363
364 b_inputs_img.append(inputs_img)
365 b_labels.append(labels)
366
367 #X = [np.array(b_inputs_img), np.array(b_inputs_imu)]
368 X = [np.array(b_inputs_img)]
369 y = np.array(b_labels).reshape(batch_size, 2)
370
371 yield X, y

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