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Retinaface_res50: config specification modification.

This commit is contained in:
zhanghuiyao 2020-11-09 09:53:39 +08:00
parent 603d27ba01
commit f2c6a81f12
3 changed files with 5 additions and 18 deletions
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13
model_zoo/official/cv/retinaface_resnet50/README.md
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@ -126,9 +126,6 @@ Parameters for both training and evaluation can be set in config.py
- config for RetinaFace, WIDERFACE dataset
```python
'name': 'Resnet50', # Backbone name
'min_sizes': [[16, 32], [64, 128], [256, 512]], # Size distribution
'steps': [8, 16, 32], # Each feature map steps
'variance': [0.1, 0.2], # Variance
'clip': False, # Clip
'loc_weight': 2.0, # Bbox regression loss weight
@ -142,14 +139,10 @@ Parameters for both training and evaluation can be set in config.py
'decay1': 70, # Epoch number of the first weight attenuation
'decay2': 90, # Epoch number of the second weight attenuation
'image_size': 840, # Training image size
'return_layers': {'layer2': 1, 'layer3': 2, 'layer4': 3}, # Layer name of input feature pyramid
'in_channel': 256, # Input channel of DetectionHead
'out_channel': 256, # Output channel of DetectionHead
'match_thresh': 0.35, # Threshold for match box
'optim': 'sgd', # Optimizer type
'warmup_epoch': 5, # Warmup size, 0 means no warm-up
'initial_lr': 0.01, # Learning rate
'network': 'resnet50', # Backbone name
'momentum': 0.9, # Momentum for Optimizer
'weight_decay': 5e-4, # Weight decay for Optimizer
'gamma': 0.1, # Attenuation ratio of learning rate
@ -158,10 +151,10 @@ Parameters for both training and evaluation can be set in config.py
'keep_checkpoint_max': 1, # Number of reserved checkpoints
'resume_net': None, # Network for restart, default is None
'training_dataset': '', # Training dataset label path, like 'data/widerface/train/label.txt'
'pretrain': True, # whether training based on the pre-trained backbone
'pretrain': True, # Whether training based on the pre-trained backbone
'pretrain_path': './data/res50_pretrain.ckpt', # Pre-trained backbone checkpoint path
'seed': 1, # setup train seed
'lr_type': 'dynamic_lr',
'seed': 1, # Setup train seed
'lr_type': 'dynamic_lr', # Learning rate decline function type, set dynamic_lr or standard_lr
# val
'val_model': './checkpoint/ckpt_0/RetinaFace-100_536.ckpt', # Validation model path
'val_dataset_folder': './data/widerface/val/', # Validation dataset path

7
model_zoo/official/cv/retinaface_resnet50/src/config.py
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@ -14,9 +14,6 @@
# ============================================================================
"""Config for train and eval."""
cfg_res50 = {
'name': 'Resnet50',
'min_sizes': [[16, 32], [64, 128], [256, 512]],
'steps': [8, 16, 32],
'variance': [0.1, 0.2],
'clip': False,
'loc_weight': 2.0,
@ -27,11 +24,7 @@ cfg_res50 = {
'num_anchor': 29126,
'ngpu': 4,
'image_size': 840,
'return_layers': {'layer2': 1, 'layer3': 2, 'layer4': 3},
'in_channel': 256,
'out_channel': 256,
'match_thresh': 0.35,
'network': 'resnet50',
# opt
'optim': 'sgd',

3
model_zoo/official/cv/retinaface_resnet50/src/utils.py
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@ -130,7 +130,8 @@ class bbox_encode():
self.match_thresh = cfg['match_thresh']
self.variances = cfg['variance']
self.priors = prior_box((cfg['image_size'], cfg['image_size']),
cfg['min_sizes'], cfg['steps'],
[[16, 32], [64, 128], [256, 512]],
[8, 16, 32],
cfg['clip'])
def __call__(self, image, targets):