def __init__(self): # don't override the super init
self.all_dataset = []
self.num = 0
start_idx = 0
for name in cfg.DATASET.NAMES:
sub_cfg = getattr(cfg.DATASET, name)
sub_dataset = SubDataset(name, sub_cfg.DATA_DIR, sub_cfg.ANNO_FILE,
sub_cfg.FRAME_RANGE, start_idx,
sub_cfg.NUM_USE)
sub_dataset.log()
self.all_dataset.append(sub_dataset)
start_idx += sub_dataset.num
self.num += sub_dataset.num_use
# self.num = cfg.DATASET.VIDEO_PER_EPOCH if cfg.DATASET.VIDEO_PER_EPOCH > 0 else self.num
self.anchor_target = AnchorTarget(cfg.ANCHOR.SCALES, cfg.ANCHOR.RATIOS,
cfg.ANCHOR.STRIDE,
cfg.TRAIN.SEARCH_SIZE // 2,
cfg.TRAIN.OUTPUT_SIZE)
self.template_aug = Augmentation(cfg.DATASET.EXAMPLAR.SHIFT,
cfg.DATASET.EXAMPLAR.SCALE,
cfg.DATASET.EXAMPLAR.BLUR,
cfg.DATASET.EXAMPLAR.FLIP,
cfg.DATASET.EXAMPLAR.COLOR)
self.search_aug = Augmentation(cfg.DATASET.SEARCH.SHIFT,
cfg.DATASET.SEARCH.SCALE,
cfg.DATASET.SEARCH.BLUR,
cfg.DATASET.SEARCH.FLIP,
cfg.DATASET.SEARCH.COLOR)
def __init__(self, model):
super().__init__()
self.model = model
self.model.eval()
self.anchor_generator = AnchorGenerator(cfg.ANCHOR.SCALES,
cfg.ANCHOR.RATIOS,
cfg.ANCHOR.STRIDE)
self.score_size = (cfg.TRACK.INSTANCE_SIZE - cfg.TRACK.EXAMPLAR_SIZE) // \
cfg.ANCHOR.STRIDE + 1 + cfg.TRACK.BASE_SIZE
hanning = np.hanning(self.score_size)
window = np.outer(hanning, hanning)
self.window = np.tile(window.flatten(),
self.anchor_generator.anchor_num)
self.all_anchor = self.anchor_generator.generate_all_anchors(
cfg.TRACK.INSTANCE_SIZE // 2, self.score_size)
self.anchor_target = AnchorTarget(cfg.ANCHOR.SCALES, cfg.ANCHOR.RATIOS,
cfg.ANCHOR.STRIDE,
cfg.TRACK.INSTANCE_SIZE // 2,
self.score_size)
self.search_aug = Augmentation(cfg.DATASET.SEARCH.SHIFT,
cfg.DATASET.SEARCH.SCALE,
cfg.DATASET.SEARCH.BLUR,
cfg.DATASET.SEARCH.FLIP,
cfg.DATASET.SEARCH.COLOR)