Python Brightness 예제들

예제 #1

def test_brightness():
    batch_size = 3
    image_size = [256, 512]
    dataset = Pascalvoc2007(
        batch_size=batch_size, pre_processor=ResizeWithGtBoxes(image_size),
        augmentor=Brightness(),
    )
    dataset = DatasetIterator(dataset)

    for _ in range(5):
        images, labels = dataset.feed()
        _show_images_with_boxes(images, labels)

예제 #2

파일: object_detection.py 프로젝트: kainoj/blueoil

NETWORK.CLASS_SCALE = 1.0
NETWORK.COORDINATE_SCALE = 1.0
NETWORK.LOSS_IOU_THRESHOLD = 0.6
NETWORK.WEIGHT_DECAY_RATE = 0.0005
NETWORK.SCORE_THRESHOLD = score_threshold
NETWORK.NMS_IOU_THRESHOLD = nms_iou_threshold
NETWORK.NMS_MAX_OUTPUT_SIZE = nms_max_output_size
NETWORK.LOSS_WARMUP_STEPS = 1280 // BATCH_SIZE

# quantization
NETWORK.ACTIVATION_QUANTIZER = linear_mid_tread_half_quantizer
NETWORK.ACTIVATION_QUANTIZER_KWARGS = {'bit': 2, 'max_value': 2.0}
NETWORK.WEIGHT_QUANTIZER = binary_channel_wise_mean_scaling_quantizer
NETWORK.WEIGHT_QUANTIZER_KWARGS = {}
NETWORK.QUANTIZE_FIRST_CONVOLUTION = True
NETWORK.QUANTIZE_LAST_CONVOLUTION = False

# dataset
DATASET = SmartDict()
DATASET.BATCH_SIZE = BATCH_SIZE
DATASET.DATA_FORMAT = DATA_FORMAT
DATASET.PRE_PROCESSOR = PRE_PROCESSOR
DATASET.AUGMENTOR = Sequence([
    FlipLeftRight(),
    Brightness((0.75, 1.25)),
    Color((0.75, 1.25)),
    Contrast((0.75, 1.25)),
    Hue((-10, 10)),
    SSDRandomCrop(min_crop_ratio=0.7),
])

예제 #3

파일: openimages_face_sample.py 프로젝트: hadusam/bluegrass

NETWORK.WEIGHT_DECAY_RATE = 0.0005
NETWORK.SCORE_THRESHOLD = score_threshold
NETWORK.NMS_IOU_THRESHOLD = nms_iou_threshold
NETWORK.NMS_MAX_OUTPUT_SIZE = nms_max_output_size
NETWORK.LOSS_WARMUP_STEPS = int(8000 / BATCH_SIZE)

# quantize
NETWORK.ACTIVATION_QUANTIZER = linear_mid_tread_half_quantizer
NETWORK.ACTIVATION_QUANTIZER_KWARGS = {
    'bit': 2,
    'max_value': 2.0
}
NETWORK.WEIGHT_QUANTIZER = binary_channel_wise_mean_scaling_quantizer
NETWORK.WEIGHT_QUANTIZER_KWARGS = {}
NETWORK.QUANTIZE_FIRST_CONVOLUTION = False
NETWORK.QUANTIZE_LAST_CONVOLUTION = False

# dataset
DATASET = EasyDict()
DATASET.BATCH_SIZE = BATCH_SIZE
DATASET.DATA_FORMAT = DATA_FORMAT
DATASET.PRE_PROCESSOR = PRE_PROCESSOR
DATASET.AUGMENTOR = Sequence([
    Brightness(value=(0.75, 1.25), ),
    Color(value=(0.75, 1.25), ),
    FlipLeftRight(probability=0.5, ),
    Hue(value=(-10, 10), ),
    SSDRandomCrop(min_crop_ratio=0.3, ),
])
DATASET.ENABLE_PREFETCH = True