How to use 'keras imagedatagenerator' in Python
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99 def 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)
336 def 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