Function data_generator_wrapper

train_bottleneck.py:197–200

(annotation_lines, batch_size, input_shape, anchors, num_classes, random=True, verbose=False)

        yield [image_data, *y_true], np.zeros(batch_size)

def data_generator_wrapper(annotation_lines, batch_size, input_shape, anchors, num_classes, random=True, verbose=False):
    n = len(annotation_lines)
    if n==0 or batch_size<=0: return None
    return data_generator(annotation_lines, batch_size, input_shape, anchors, num_classes, random, verbose)

def bottleneck_generator(annotation_lines, batch_size, input_shape, anchors, num_classes, bottlenecks):
    n = len(annotation_lines)