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parsinggait_gait3d_parsing.yaml
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data_cfg:
dataset_name: Gait3D-Parsing
dataset_root: your_path
dataset_partition: ./datasets/Gait3D/Gait3D.json # Uses the same Gait3D.json as Gait3D dataset
# data_in_use: [true, false]
num_workers: 1
remove_no_gallery: false # Remove probe if no gallery for it
test_dataset_name: Gait3D-Parsing
evaluator_cfg:
enable_float16: true
restore_ckpt_strict: true
restore_hint: 120000
save_name: ParsingGait
eval_func: evaluate_Gait3D
sampler:
batch_shuffle: false
batch_size: 4
sample_type: all_ordered # all indicates whole sequence used to test, while ordered means input sequence by its natural order; Other options: fixed_unordered
frames_all_limit: 720 # limit the number of sampled frames to prevent out of memory
metric: euc # cos
transform:
- type: BaseParsingCuttingTransform
loss_cfg:
- loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
- loss_term_weight: 1.0
scale: 16
type: CrossEntropyLoss
log_prefix: softmax
log_accuracy: true
model_cfg:
model: ParsingGait
backbone_cfg:
type: ResNet9
block: BasicBlock
channels: # Layers configuration for automatically model construction
- 64
- 128
- 256
- 512
layers:
- 1
- 1
- 1
- 1
strides:
- 1
- 2
- 2
- 1
maxpool: false
SeparateFCs:
in_channels: 512
out_channels: 256
parts_num: 21
SeparateBNNecks:
class_num: 3000
in_channels: 256
parts_num: 21
bin_num:
- 16
gcn_cfg:
fine_parts: 11
coarse_parts: 5
only_fine_graph: false
only_coarse_graph: true
combine_fine_coarse_graph: false
optimizer_cfg:
lr: 0.1
momentum: 0.9
solver: SGD
weight_decay: 0.0005
scheduler_cfg:
gamma: 0.1
milestones: # Learning Rate Reduction at each milestones
- 40000
- 80000
- 100000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true # half_percesion float for memory reduction and speedup
fix_BN: false
with_test: True
log_iter: 100
restore_ckpt_strict: true
restore_hint: 0
save_iter: 40000
save_name: ParsingGait
sync_BN: true
total_iter: 120000
sampler:
batch_shuffle: true
batch_size:
- 32 # TripletSampler, batch_size[0] indicates Number of Identity
- 2 # batch_size[1] indicates Samples sequqnce for each Identity
frames_num_fixed: 30 # fixed frames number for training
frames_num_max: 50 # max frames number for unfixed training
frames_num_min: 10 # min frames number for unfixed traing
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: BaseParsingCuttingTransform