def __init__(self, cfg, chip_size): self.valid_ranges = cfg.TRAIN.VALID_RANGES self.scales = cfg.TRAIN.SCALES self.chip_size = chip_size self.use_cpp = cfg.TRAIN.CPP_CHIPS self.chip_stride = np.random.randint(56, 60) self.chip_generator = chip_generator(chip_stride=self.chip_stride, use_cpp=self.use_cpp) self.use_neg_chips = cfg.TRAIN.USE_NEG_CHIPS
def __init__(self, cfg, chip_size): self.valid_ranges = cfg.valid_ranges self.scales = cfg.pyramid_scales self.chip_size = chip_size self.use_cpp = cfg.cpp_chips self.chip_stride = cfg.chip_stride self.chip_generator = chip_generator(chip_stride=self.chip_stride, use_cpp=self.use_cpp) self.use_neg_chips = cfg.use_neg_chips self.chip_gt_overlap = cfg.chip_gt_overlap
def __init__(self, cfg, chip_size): self.valid_ranges = cfg.TRAIN.VALID_RANGES self.scales = cfg.TRAIN.SCALES self.chip_size = chip_size self.use_cpp = cfg.TRAIN.CPP_CHIPS self.chip_stride = np.random.randint(56, 60) self.chip_generator = chip_generator(chip_stride=self.chip_stride, use_cpp=self.use_cpp) self.use_neg_chips = cfg.TRAIN.USE_NEG_CHIPS self.res_based = type(cfg.TRAIN.SCALES[0])==list or type(cfg.TRAIN.SCALES[0])==tuple for s in cfg.TRAIN.SCALES: if self.res_based: assert type(s)==tuple or type(s)==list, 'In resolution-based mode, all scales should be tuples' else: assert type(s)==float, 'In scale-based mode, all scales should be float'
def reset(self): self.chip_stride = np.random.randint(56, 60) self.chip_generator = chip_generator(chip_stride=self.chip_stride, use_cpp=self.use_cpp)
def reset(self): self.chip_generator = chip_generator(chip_stride=self.chip_stride, use_cpp=self.use_cpp)