import os.path
HOME = '/home/ljh/refinedet/data'
COLORS = ((255, 0, 0, 128), (0, 255, 0, 128), (0, 0, 255, 128),
(0, 255, 255, 128), (255, 0, 255, 128), (255, 255, 0, 128))
MEANS = (104, 117, 123)
voc = {
'300': {
'amp':True,
'num_classes': 21,
'lr_steps': (80000, 100000, 120000),
'max_iter': 121000,
'feature_maps': [38, 19, 10, 5, 3, 1],
'min_dim': 300,
'steps': [8, 16, 32, 64, 100, 300],
'min_sizes': [30, 60, 111, 162, 213, 264],
'max_sizes': [60, 111, 162, 213, 264, 315],
'aspect_ratios': [[2], [2, 3], [2, 3], [2, 3], [2], [2]],
'variance': [0.1, 0.2],
'clip': True,
'name': 'VOC_300',
},
'512': {
'amp':True,
'num_classes': 21,
'lr_steps': (80000, 100000, 120000),
'max_iter': 121000,
'feature_maps': [64, 32, 16, 8, 4, 2, 1],
'min_dim': 512,
'steps': [8, 16, 32, 64, 128, 256, 512],
'min_sizes': [20, 51, 133, 215, 296, 378, 460],
'max_sizes': [51, 133, 215, 296, 378, 460, 542],
'aspect_ratios': [[2], [2, 3], [2, 3], [2, 3], [2, 3], [2], [2]],
'variance': [0.1, 0.2],
'clip': True,
'name': 'VOC_512',
}
}
coco = {
'amp':True,
'num_classes': 201,
'lr_steps': (280000, 360000, 400000),
'max_iter': 400000,
'feature_maps': [38, 19, 10, 5, 3, 1],
'min_dim': 300,
'steps': [8, 16, 32, 64, 100, 300],
'min_sizes': [21, 45, 99, 153, 207, 261],
'max_sizes': [45, 99, 153, 207, 261, 315],
'aspect_ratios': [[2], [2, 3], [2, 3], [2, 3], [2], [2]],
'variance': [0.1, 0.2],
'clip': True,
'name': 'COCO',
}
voc_refinedet = {
'320': {
'amp':True,
'num_classes': 21,
'rank':0,
'distributed': True,
'num_epochs': 232,
'lr_steps': (80000, 100000, 120000),
'lr_step_epoch':(154, 193, 232),
'confidence_threshold': 0.01,
'top_k': 5,
'save_folder': 'eval/',
'cuda': False,
'npu': True,
'cleanup': True,
'input_size': 320,
'max_iter': 125000,
'feature_maps': [40, 20, 10, 5],
'min_dim': 320,
'steps': [8, 16, 32, 64],
'min_sizes': [32, 64, 128, 256],
'max_sizes': [],
'aspect_ratios': [[2], [2], [2], [2]],
'variance': [0.1, 0.2],
'clip': True,
'name': 'RefineDet_VOC_320',
},
'512': {
'amp':True,
'num_classes': 21,
'lr_steps': (80000, 100000, 120000),
'epoch_steps': (153, 193, 232),
'max_iter': 121000,
'feature_maps': [64, 32, 16, 8],
'min_dim': 512,
'steps': [8, 16, 32, 64],
'min_sizes': [32, 64, 128, 256],
'max_sizes': [],
'aspect_ratios': [[2], [2], [2], [2]],
'variance': [0.1, 0.2],
'clip': True,
'name': 'RefineDet_VOC_512',
}
}
coco_refinedet = {
'amp':True,
'num_classes': 201,
'lr_steps': (280000, 360000, 400000),
'epoch_steps': (153, 193, 232),
'max_iter': 400000,
'feature_maps': [38, 19, 10, 5, 3, 1],
'min_dim': 300,
'steps': [8, 16, 32, 64, 100, 300],
'min_sizes': [21, 45, 99, 153, 207, 261],
'max_sizes': [45, 99, 153, 207, 261, 315],
'aspect_ratios': [[2], [2, 3], [2, 3], [2, 3], [2], [2]],
'variance': [0.1, 0.2],
'clip': True,
'name': 'COCO',
}