Delete configs/baseline directory
The 'baseline' series is abandoned since GaitBase can better serve as a baseline model for OpenGait.
This commit is contained in:
Chao Fan
GitHub
@@ -1,99 +0,0 @@
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data_cfg:
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dataset_name: CASIA-B
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dataset_root: your_path
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dataset_partition: ./datasets/CASIA-B/CASIA-B.json
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num_workers: 1
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remove_no_gallery: false # Remove probe if no gallery for it
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test_dataset_name: CASIA-B
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evaluator_cfg:
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enable_float16: true
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restore_ckpt_strict: true
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restore_hint: 60000
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save_name: Baseline
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sampler:
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batch_shuffle: false
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batch_size: 16
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sample_type: all_ordered # all indicates whole sequence used to test, while ordered means input sequence by its natural order; Other options: fixed_unordered
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frames_all_limit: 720 # limit the number of sampled frames to prevent out of memory
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metric: euc # cos
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transform:
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- type: BaseSilCuttingTransform
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img_w: 64
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loss_cfg:
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- loss_term_weight: 1.0
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margin: 0.2
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type: TripletLoss
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log_prefix: triplet
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- loss_term_weight: 0.1
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scale: 16
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type: CrossEntropyLoss
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log_prefix: softmax
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log_accuracy: true
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model_cfg:
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model: Baseline
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backbone_cfg:
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in_channels: 1
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layers_cfg: # Layers configuration for automatically model construction
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- BC-64
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- BC-64
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- M
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- BC-128
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- BC-128
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- M
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- BC-256
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- BC-256
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type: Plain
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SeparateFCs:
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in_channels: 256
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out_channels: 256
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parts_num: 31
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SeparateBNNecks:
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class_num: 74
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in_channels: 256
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parts_num: 31
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bin_num:
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- 16
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- 8
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- 4
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- 2
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- 1
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optimizer_cfg:
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lr: 0.1
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momentum: 0.9
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solver: SGD
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weight_decay: 0.0005
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scheduler_cfg:
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gamma: 0.1
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milestones: # Learning Rate Reduction at each milestones
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- 20000
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- 40000
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scheduler: MultiStepLR
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trainer_cfg:
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enable_float16: true # half_percesion float for memory reduction and speedup
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fix_BN: false
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log_iter: 100
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with_test: true
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restore_ckpt_strict: true
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restore_hint: 0
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save_iter: 10000
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save_name: Baseline
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sync_BN: true
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total_iter: 60000
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sampler:
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batch_shuffle: true
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batch_size:
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- 8 # TripletSampler, batch_size[0] indicates Number of Identity
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- 16 # batch_size[1] indicates Samples sequqnce for each Identity
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frames_num_fixed: 30 # fixed frames number for training
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frames_num_max: 50 # max frames number for unfixed training
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frames_num_min: 25 # min frames number for unfixed traing
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sample_type: fixed_unordered # fixed control input frames number, unordered for controlling order of input tensor; Other options: unfixed_ordered or all_ordered
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type: TripletSampler
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transform:
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- type: BaseSilCuttingTransform
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img_w: 64
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@@ -1,103 +0,0 @@
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data_cfg:
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dataset_name: GREW
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dataset_root: /home/data/grew-pkl-fixed
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dataset_partition: ./datasets/GREW/GREW.json
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num_workers: 16
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remove_no_gallery: false # Remove probe if no gallery for it
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test_dataset_name: GREW
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evaluator_cfg:
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enable_float16: true
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restore_ckpt_strict: true
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restore_hint: 250000
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save_name: Baseline
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eval_func: GREW_submission # identification_real_scene # identification_GREW_submission
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sampler:
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batch_shuffle: false
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batch_size: 64
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sample_type: all_ordered # all indicates whole sequence used to test, while ordered means input sequence by its natural order; Other options: fixed_unordered
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frames_all_limit: 720 # limit the number of sampled frames to prevent out of memory
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metric: euc # cos
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transform:
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- type: BaseSilCuttingTransform
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img_w: 64
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loss_cfg:
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- loss_term_weight: 1.0
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margin: 0.2
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type: TripletLoss
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log_prefix: triplet
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- loss_term_weight: 0.1
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scale: 16
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type: CrossEntropyLoss
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log_prefix: softmax
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log_accuracy: true
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model_cfg:
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model: Baseline
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backbone_cfg:
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in_channels: 1
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layers_cfg: # Layers configuration for automatically model construction
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- BC-32
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- BC-32
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- M
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- BC-64
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- BC-64
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- M
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- BC-128
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- BC-128
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- BC-256
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- BC-256
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# - M
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# - BC-512
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# - BC-512
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type: Plain
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SeparateFCs:
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in_channels: 256
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out_channels: 256
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parts_num: 16
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SeparateBNNecks:
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class_num: 20000
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in_channels: 256
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parts_num: 16
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bin_num:
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- 16
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# - 8
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# - 4
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# - 2
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# - 1
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optimizer_cfg:
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lr: 0.1
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momentum: 0.9
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solver: SGD
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weight_decay: 0.0005
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scheduler_cfg:
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gamma: 0.1
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milestones: # Learning Rate Reduction at each milestones
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- 150000
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scheduler: MultiStepLR
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trainer_cfg:
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enable_float16: true # half_percesion float for memory reduction and speedup
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fix_BN: false
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log_iter: 100
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restore_ckpt_strict: true
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restore_hint: 0
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save_iter: 10000
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save_name: Baseline
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sync_BN: true
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total_iter: 250000
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sampler:
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batch_shuffle: true
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batch_size:
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- 32 # TripletSampler, batch_size[0] indicates Number of Identity
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- 8 # batch_size[1] indicates Samples sequqnce for each Identity
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frames_num_fixed: 30 # fixed frames number for training
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frames_num_max: 50 # max frames number for unfixed training
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frames_num_min: 25 # min frames number for unfixed traing
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sample_type: fixed_unordered # fixed control input frames number, unordered for controlling order of input tensor; Other options: unfixed_ordered or all_ordered
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type: TripletSampler
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transform:
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- type: BaseSilCuttingTransform
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img_w: 64
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@@ -1,104 +0,0 @@
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data_cfg:
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dataset_name: Gait3D
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dataset_root: your_path
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dataset_partition: datasets/Gait3D/Gait3D.json
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data_in_use: [true, false]
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num_workers: 1
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remove_no_gallery: false # Remove probe if no gallery for it
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test_dataset_name: Gait3D
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evaluator_cfg:
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enable_float16: true
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restore_ckpt_strict: true
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restore_hint: 60000
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save_name: Baseline
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eval_func: evaluate_Gait3D
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sampler:
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batch_shuffle: false
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batch_size: 16
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sample_type: all_ordered # all indicates whole sequence used to test, while ordered means input sequence by its natural order; Other options: fixed_unordered
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frames_all_limit: 720 # limit the number of sampled frames to prevent out of memory
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metric: euc # cos euc
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transform:
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- type: BaseSilCuttingTransform
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loss_cfg:
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- loss_term_weight: 1.0
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margin: 0.2
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type: TripletLoss
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log_prefix: triplet
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- loss_term_weight: 0.1
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scale: 16
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type: CrossEntropyLoss
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log_prefix: softmax
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log_accuracy: true
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model_cfg:
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model: Baseline
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backbone_cfg:
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in_channels: 1
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layers_cfg: # Layers configuration for automatically model construction
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- BC-64
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- BC-64
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- M
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- BC-128
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- BC-128
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- M
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- BC-256
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- BC-256
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# - M
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# - BC-512
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# - BC-512
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type: Plain
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SeparateFCs:
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in_channels: 256
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out_channels: 256
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parts_num: 31
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SeparateBNNecks:
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class_num: 3000
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in_channels: 256
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parts_num: 31
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bin_num:
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- 16
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- 8
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- 4
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- 2
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- 1
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optimizer_cfg:
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lr: 0.1
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momentum: 0.9
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solver: SGD
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weight_decay: 0.0005
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scheduler_cfg:
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gamma: 0.1
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milestones: # Learning Rate Reduction at each milestones
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- 20000
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- 40000
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- 50000
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scheduler: MultiStepLR
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trainer_cfg:
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enable_float16: true # half_percesion float for memory reduction and speedup
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fix_BN: false
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log_iter: 100
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with_test: true
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restore_ckpt_strict: true
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restore_hint: 0
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save_iter: 10000
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save_name: Baseline
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sync_BN: true
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total_iter: 60000
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sampler:
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batch_shuffle: true
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batch_size:
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- 32 # TripletSampler, batch_size[0] indicates Number of Identity
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- 4 # batch_size[1] indicates Samples sequqnce for each Identity
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frames_num_fixed: 30 # fixed frames number for training
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frames_num_max: 50 # max frames number for unfixed training
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frames_num_min: 25 # min frames number for unfixed traing
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sample_type: fixed_unordered # fixed control input frames number, unordered for controlling order of input tensor; Other options: unfixed_ordered or all_ordered
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type: TripletSampler
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transform:
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- type: BaseSilCuttingTransform
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@@ -1,101 +0,0 @@
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data_cfg:
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dataset_name: OUMVLP
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dataset_root: your_path
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dataset_partition: ./datasets/OUMVLP/OUMVLP.json
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num_workers: 1
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remove_no_gallery: false # Remove probe if no gallery for it
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test_dataset_name: OUMVLP
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evaluator_cfg:
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enable_float16: true
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restore_ckpt_strict: true
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restore_hint: 150000
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save_name: Baseline
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sampler:
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batch_shuffle: false
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batch_size: 4
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sample_type: all_ordered # all indicates whole sequence used to test, while ordered means input sequence by its natural order; Other options: fixed_unordered
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frames_all_limit: 720 # limit the number of sampled frames to prevent out of memory
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metric: euc # cos
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# transform:
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# - type: BaseSilCuttingTransform
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# img_w: 128
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loss_cfg:
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- loss_term_weight: 1.0
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margin: 0.2
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type: TripletLoss
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log_prefix: triplet
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- loss_term_weight: 0.1
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scale: 16
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type: CrossEntropyLoss
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log_prefix: softmax
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log_accuracy: true
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model_cfg:
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model: Baseline
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backbone_cfg:
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in_channels: 1
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layers_cfg: # Layers configuration for automatically model construction
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- BC-32
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- BC-32
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- M
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- BC-64
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- BC-64
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- M
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- BC-128
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- BC-128
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- BC-256
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- BC-256
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type: Plain
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SeparateFCs:
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in_channels: 256
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out_channels: 256
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parts_num: 31
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SeparateBNNecks:
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class_num: 5153
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in_channels: 256
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parts_num: 31
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bin_num:
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- 16
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- 8
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- 4
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- 2
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- 1
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optimizer_cfg:
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lr: 0.1
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momentum: 0.9
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solver: SGD
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weight_decay: 0.0005
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scheduler_cfg:
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gamma: 0.1
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milestones: # Learning Rate Reduction at each milestones
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- 50000
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- 100000
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scheduler: MultiStepLR
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trainer_cfg:
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enable_float16: true # half_percesion float for memory reduction and speedup
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fix_BN: false
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log_iter: 100
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with_test: true
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restore_ckpt_strict: true
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restore_hint: 0
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save_iter: 10000
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save_name: Baseline
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sync_BN: true
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total_iter: 150000
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sampler:
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batch_shuffle: true
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batch_size:
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- 32 # TripletSampler, batch_size[0] indicates Number of Identity
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- 16 # batch_size[1] indicates Samples sequqnce for each Identity
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frames_num_fixed: 30 # fixed frames number for training
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frames_num_max: 50 # max frames number for unfixed training
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frames_num_min: 25 # min frames number for unfixed traing
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sample_type: fixed_unordered # fixed control input frames number, unordered for controlling order of input tensor; Other options: unfixed_ordered or all_ordered
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type: TripletSampler
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# transform:
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# - type: BaseSilCuttingTransform
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# img_w: 128
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@@ -1,98 +0,0 @@
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data_cfg:
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dataset_name: HID
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dataset_root: your_path
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dataset_partition: ./datasets/HID/HID2023.json
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num_workers: 1
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remove_no_gallery: false # Remove probe if no gallery for it
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evaluator_cfg:
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enable_float16: true
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restore_ckpt_strict: true
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restore_hint: 60000
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save_name: Baseline
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eval_func: HID_submission
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rerank: False
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sampler:
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batch_shuffle: false
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batch_size: 8
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sample_type: all_ordered # all indicates whole sequence used to test, while ordered means input sequence by its natural order; Other options: fixed_unordered
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frames_all_limit: 720 # limit the number of sampled frames to prevent out of memory
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metric: euc # cos
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transform:
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- type: BaseSilCuttingTransform
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img_w: 128
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loss_cfg:
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- loss_term_weight: 1.0
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margin: 0.2
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type: TripletLoss
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log_prefix: triplet
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- loss_term_weight: 0.1
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scale: 16
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type: CrossEntropyLoss
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log_prefix: softmax
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log_accuracy: true
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|
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model_cfg:
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model: Baseline
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backbone_cfg:
|
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in_channels: 1
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layers_cfg: # Layers configuration for automatically model construction
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- BC-64
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- BC-64
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- M
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- BC-128
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- BC-128
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||||
- M
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- BC-256
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- BC-256
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- M
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- BC-512
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- BC-512
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type: Plain
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SeparateFCs:
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in_channels: 512
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out_channels: 256
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parts_num: 31
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SeparateBNNecks:
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class_num: 500
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in_channels: 256
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parts_num: 31
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bin_num:
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- 16
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- 8
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- 4
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- 2
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- 1
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optimizer_cfg:
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lr: 0.1
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momentum: 0.9
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solver: SGD
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weight_decay: 0.0005
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scheduler_cfg:
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gamma: 0.1
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milestones: # Learning Rate Reduction at each milestones
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- 20000
|
||||
- 40000
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scheduler: MultiStepLR
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trainer_cfg:
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enable_float16: true # half_percesion float for memory reduction and speedup
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fix_BN: false
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log_iter: 100
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restore_ckpt_strict: true
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||||
restore_hint: 0
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save_iter: 10000
|
||||
save_name: Baseline
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sync_BN: true
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total_iter: 60000
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||||
sampler:
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batch_shuffle: true
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batch_size:
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- 16 # TripletSampler, batch_size[0] indicates Number of Identity
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||||
- 8 # batch_size[1] indicates Samples sequqnce for each Identity
|
||||
frames_num_fixed: 30 # fixed frames number for training
|
||||
sample_type: fixed_unordered # fixed control input frames number, unordered for controlling order of input tensor; Other options: unfixed_ordered or all_ordered
|
||||
type: TripletSampler
|
||||
transform:
|
||||
- type: BaseSilCuttingTransform
|
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img_w: 128
|
||||
Reference in New Issue
Block a user