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add gaitedge and reorgnize repo

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This commit is contained in:
darkliang
2022-07-05 21:52:41 +08:00
parent 1b17bac455
commit 4205c5f283
28 changed files with 153 additions and 135 deletions
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configs/baseline/baseline.yaml
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data_cfg:
dataset_name: CASIA-B
dataset_root: your_path
dataset_partition: ./datasets/CASIA-B/CASIA-B_include_005.json
num_workers: 1
remove_no_gallery: false # Remove probe if no gallery for it
test_dataset_name: CASIA-B
evaluator_cfg:
enable_float16: true
restore_ckpt_strict: true
restore_hint: 60000
save_name: Baseline
eval_func: identification
sampler:
batch_shuffle: false
batch_size: 16
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: BaseSilCuttingTransform
img_w: 64
loss_cfg:
- loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
- loss_term_weight: 0.1
scale: 16
type: CrossEntropyLoss
log_prefix: softmax
log_accuracy: true
model_cfg:
model: Baseline
backbone_cfg:
in_channels: 1
layers_cfg: # Layers configuration for automatically model construction
- BC-64
- BC-64
- M
- BC-128
- BC-128
- M
- BC-256
- BC-256
type: Plain
SeparateFCs:
in_channels: 256
out_channels: 256
parts_num: 31
SeparateBNNecks:
class_num: 74
in_channels: 256
parts_num: 31
bin_num:
- 16
- 8
- 4
- 2
- 1
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
- 20000
- 40000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true # half_percesion float for memory reduction and speedup
fix_BN: false
log_iter: 100
with_test: true
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: Baseline
sync_BN: true
total_iter: 60000
sampler:
batch_shuffle: true
batch_size:
- 8 # TripletSampler, batch_size[0] indicates Number of Identity
- 16 # 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: 25 # 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: BaseSilCuttingTransform
img_w: 64
configs/baseline/baseline_GREW.yaml
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data_cfg:
dataset_name: GREW
dataset_root: /home/data/grew-pkl-fixed
dataset_partition: ./datasets/GREW/GREW.json
num_workers: 16
remove_no_gallery: false # Remove probe if no gallery for it
test_dataset_name: GREW
evaluator_cfg:
enable_float16: true
restore_ckpt_strict: true
restore_hint: 250000
save_name: Baseline
eval_func: identification_GREW_submission # identification_real_scene # identification_GREW_submission
sampler:
batch_shuffle: false
batch_size: 64
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: BaseSilCuttingTransform
img_w: 64
loss_cfg:
- loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
- loss_term_weight: 0.1
scale: 16
type: CrossEntropyLoss
log_prefix: softmax
log_accuracy: true
model_cfg:
model: Baseline
backbone_cfg:
in_channels: 1
layers_cfg: # Layers configuration for automatically model construction
- BC-32
- BC-32
- M
- BC-64
- BC-64
- M
- BC-128
- BC-128
- BC-256
- BC-256
# - M
# - BC-512
# - BC-512
type: Plain
SeparateFCs:
in_channels: 256
out_channels: 256
parts_num: 16
SeparateBNNecks:
class_num: 20000
in_channels: 256
parts_num: 16
bin_num:
- 16
# - 8
# - 4
# - 2
# - 1
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
- 150000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true # half_percesion float for memory reduction and speedup
fix_BN: false
log_iter: 100
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: Baseline
sync_BN: true
total_iter: 250000
sampler:
batch_shuffle: true
batch_size:
- 32 # TripletSampler, batch_size[0] indicates Number of Identity
- 8 # 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: 25 # 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: BaseSilCuttingTransform
img_w: 64
configs/baseline/baseline_OUMVLP.yaml
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data_cfg:
dataset_name: OUMVLP
dataset_root: your_path
dataset_partition: ./datasets/OUMVLP/OUMVLP.json
num_workers: 1
remove_no_gallery: false # Remove probe if no gallery for it
test_dataset_name: OUMVLP
evaluator_cfg:
enable_float16: true
restore_ckpt_strict: true
restore_hint: 150000
save_name: Baseline
eval_func: identification
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: BaseSilCuttingTransform
# img_w: 128
loss_cfg:
- loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
- loss_term_weight: 0.1
scale: 16
type: CrossEntropyLoss
log_prefix: softmax
log_accuracy: true
model_cfg:
model: Baseline
backbone_cfg:
in_channels: 1
layers_cfg: # Layers configuration for automatically model construction
- BC-32
- BC-32
- M
- BC-64
- BC-64
- M
- BC-128
- BC-128
- BC-256
- BC-256
type: Plain
SeparateFCs:
in_channels: 256
out_channels: 256
parts_num: 31
SeparateBNNecks:
class_num: 5153
in_channels: 256
parts_num: 31
bin_num:
- 16
- 8
- 4
- 2
- 1
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
- 50000
- 100000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true # half_percesion float for memory reduction and speedup
fix_BN: false
log_iter: 100
with_test: true
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: Baseline
sync_BN: true
total_iter: 150000
sampler:
batch_shuffle: true
batch_size:
- 32 # TripletSampler, batch_size[0] indicates Number of Identity
- 16 # 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: 25 # 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: BaseSilCuttingTransform
# img_w: 128
configs/baseline/baseline_hid.yaml
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data_cfg:
dataset_name: HID
dataset_root: your_path
dataset_partition: ./datasets/HID/HID.json
num_workers: 1
remove_no_gallery: false # Remove probe if no gallery for it
evaluator_cfg:
enable_float16: true
restore_ckpt_strict: true
restore_hint: 60000
save_name: Baseline
eval_func: evaluate_HID
sampler:
batch_shuffle: false
batch_size: 8
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: BaseSilCuttingTransform
img_w: 128
loss_cfg:
- loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
- loss_term_weight: 0.1
scale: 16
type: CrossEntropyLoss
log_prefix: softmax
log_accuracy: true
model_cfg:
model: Baseline
backbone_cfg:
in_channels: 1
layers_cfg: # Layers configuration for automatically model construction
- BC-64
- BC-64
- M
- BC-128
- BC-128
- M
- BC-256
- BC-256
- M
- BC-512
- BC-512
type: Plain
SeparateFCs:
in_channels: 512
out_channels: 256
parts_num: 31
SeparateBNNecks:
class_num: 500
in_channels: 256
parts_num: 31
bin_num:
- 16
- 8
- 4
- 2
- 1
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
- 20000
- 40000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true # half_percesion float for memory reduction and speedup
fix_BN: false
log_iter: 100
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: Baseline
sync_BN: true
total_iter: 60000
sampler:
batch_shuffle: true
batch_size:
- 16 # TripletSampler, batch_size[0] indicates Number of Identity
- 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
img_w: 128
configs/default.yaml
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data_cfg:
dataset_name: CASIA-B
dataset_root: your_path
num_workers: 1
dataset_partition: ./datasets/CASIA-B/CASIA-B.json
remove_no_gallery: false
cache: false
test_dataset_name: CASIA-B
evaluator_cfg:
enable_float16: false
restore_ckpt_strict: true
restore_hint: 80000
save_name: tmp
eval_func: identification
sampler:
batch_size: 4
sample_type: all_ordered
type: InferenceSampler
transform:
- img_w: 64
type: BaseSilCuttingTransform
metric: euc # cos
loss_cfg:
loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
model_cfg:
model: Baseline
optimizer_cfg:
lr: 0.1
momentum: 0.9
solver: SGD
weight_decay: 0.0005
scheduler_cfg:
gamma: 0.1
milestones:
- 20000
- 40000
- 60000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true
with_test: false
fix_BN: false
log_iter: 100
restore_ckpt_strict: true
optimizer_reset: false
scheduler_reset: false
restore_hint: 0
save_iter: 2000
save_name: tmp
sync_BN: false
total_iter: 80000
sampler:
batch_shuffle: false
batch_size:
- 8
- 16
frames_num_fixed: 30
frames_num_max: 50
frames_num_min: 25
sample_type: fixed_unordered
type: TripletSampler
transform:
- img_w: 64
type: BaseSilCuttingTransform
configs/gaitedge/README.md
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# GaitEdge: Beyond Plain End-to-end Gait Recognition for Better Practicality
This [paper](https://arxiv.org/abs/2203.03972) has been accepted by ECCV 2022, the source code and CASIA-B* dataset mentioned in the paper will be released within two weeks.
## Abstract
Gait is one of the most promising biometrics to identify individuals at a long distance. Although most previous methods have focused on recognizing the silhouettes, several end-to-end methods that extract gait features directly from RGB images perform better. However, we argue that these end-to-end methods inevitably suffer from the gait-unrelated noises, i.e., low-level texture and colorful information. Experimentally, we design both the cross-domain evaluation and visualization to stand for this view. In this work, we propose a novel end-to-end framework named GaitEdge which can effectively block gait-unrelated information and release end-to-end training potential. Specifically, GaitEdge synthesizes the output of the pedestrian segmentation network and then feeds it to the subsequent recognition network, where the synthetic silhouettes consist of trainable edges of bodies and fixed interiors to limit the information that the recognition network receives. Besides, GaitAlign for aligning silhouettes is embedded into the GaitEdge without loss of differentiability. Experimental results on CASIA-B and our newly built TTG-200 indicate that GaitEdge significantly outperforms the previous methods and provides a more practical end-to-end paradigm for blocking RGB noises effectively.
![img](../../assets/gaitedge.png)
configs/gaitgl/gaitgl.yaml
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# Note : *** the batch_size should be equal to the gpus number at the test phase!!! ***
data_cfg:
dataset_name: CASIA-B
dataset_root: your_path
dataset_partition: ./datasets/CASIA-B/CASIA-B_include_005.json
num_workers: 1
remove_no_gallery: false
test_dataset_name: CASIA-B
evaluator_cfg:
enable_distributed: true
enable_float16: false
restore_ckpt_strict: true
restore_hint: 80000
save_name: GaitGL
sampler:
batch_size: 4
sample_type: all_ordered
type: InferenceSampler
loss_cfg:
- loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
- loss_term_weight: 1.0
scale: 1
type: CrossEntropyLoss
log_accuracy: true
label_smooth: false
log_prefix: softmax
model_cfg:
model: GaitGL
channels: [32, 64, 128]
class_num: 74
optimizer_cfg:
lr: 1.0e-4
solver: Adam
weight_decay: 5.0e-4
scheduler_cfg:
gamma: 0.1
milestones:
- 70000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true
with_test: true
log_iter: 100
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: GaitGL
sync_BN: true
total_iter: 80000
sampler:
batch_shuffle: true
batch_size:
- 8
- 8
frames_num_fixed: 30
frames_skip_num: 0
sample_type: fixed_ordered
type: TripletSampler
configs/gaitgl/gaitgl_GREW.yaml
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# Note : *** the batch_size should be equal to the gpus number at the test phase!!! ***
data_cfg:
dataset_name: GREW
dataset_root: your_path
dataset_partition: ./datasets/GREW/GREW.json
num_workers: 16
remove_no_gallery: false # Remove probe if no gallery for it
test_dataset_name: GREW
evaluator_cfg:
enable_distributed: true
enable_float16: false
restore_ckpt_strict: true
restore_hint: 250000
save_name: GaitGL
eval_func: identification_GREW_submission # identification_real_scene # identification_GREW_submission
sampler:
batch_size: 4
sample_type: all_ordered
type: InferenceSampler
loss_cfg:
- loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
- loss_term_weight: 1.0
scale: 1
type: CrossEntropyLoss
log_accuracy: true
label_smooth: true
log_prefix: softmax
model_cfg:
model: GaitGL
channels: [32, 64, 128, 256]
class_num: 20000
optimizer_cfg:
lr: 1.0e-4
solver: Adam
weight_decay: 0
scheduler_cfg:
gamma: 0.1
milestones:
- 150000
- 200000
scheduler: MultiStepLR
trainer_cfg:
enable_distributed: true
enable_float16: true
with_test: false
log_iter: 100
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: GaitGL
sync_BN: true
total_iter: 250000
sampler:
batch_shuffle: true
batch_size:
- 32
- 4
frames_num_fixed: 30
frames_skip_num: 0
sample_type: fixed_ordered
type: TripletSampler
configs/gaitgl/gaitgl_GREW_BNNeck.yaml
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# Note : *** the batch_size should be equal to the gpus number at the test phase!!! ***
data_cfg:
dataset_name: GREW
dataset_root: your_path
dataset_partition: ./datasets/GREW/GREW.json
num_workers: 16
remove_no_gallery: false # Remove probe if no gallery for it
test_dataset_name: GREW
evaluator_cfg:
enable_distributed: true
enable_float16: false
restore_ckpt_strict: true
restore_hint: 250000
save_name: GaitGL_BNNeck
eval_func: identification_GREW_submission # identification_real_scene # identification_GREW_submission
sampler:
batch_size: 4
sample_type: all_ordered
type: InferenceSampler
loss_cfg:
- loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
- loss_term_weight: 1.0
scale: 1
type: CrossEntropyLoss
log_accuracy: true
label_smooth: true
log_prefix: softmax
model_cfg:
model: GaitGL
channels: [32, 64, 128, 256]
class_num: 20000
SeparateBNNecks:
class_num: 20000
in_channels: 256
parts_num: 64
optimizer_cfg:
lr: 1.0e-4
solver: Adam
weight_decay: 0
scheduler_cfg:
gamma: 0.1
milestones:
- 150000
- 200000
scheduler: MultiStepLR
trainer_cfg:
enable_distributed: true
enable_float16: true
with_test: false
log_iter: 100
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: GaitGL_BNNeck
sync_BN: true
total_iter: 250000
sampler:
batch_shuffle: true
batch_size:
- 32
- 4
frames_num_fixed: 30
frames_skip_num: 0
sample_type: fixed_ordered
type: TripletSampler
configs/gaitgl/gaitgl_OUMVLP.yaml
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# Note : *** the batch_size should be equal to the gpus number at the test phase!!! ***
data_cfg:
dataset_name: OUMVLP
dataset_root: your_path
dataset_partition: ./datasets/OUMVLP/OUMVLP.json
num_workers: 1
remove_no_gallery: false
test_dataset_name: OUMVLP
evaluator_cfg:
enable_distributed: true
enable_float16: false
restore_ckpt_strict: true
restore_hint: 210000
save_name: GaitGL
sampler:
batch_size: 2
sample_type: all_ordered
type: InferenceSampler
loss_cfg:
- loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
- loss_term_weight: 1.0
scale: 1
type: CrossEntropyLoss
log_accuracy: true
label_smooth: true
log_prefix: softmax
model_cfg:
model: GaitGL
channels: [32, 64, 128, 256]
class_num: 5153
optimizer_cfg:
lr: 1.0e-4
solver: Adam
weight_decay: 0
scheduler_cfg:
gamma: 0.1
milestones:
- 150000
- 200000
scheduler: MultiStepLR
trainer_cfg:
enable_distributed: true
enable_float16: true
with_test: false
log_iter: 100
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: GaitGL
sync_BN: true
total_iter: 210000
sampler:
batch_shuffle: true
batch_size:
- 32
- 8
frames_num_fixed: 30
frames_skip_num: 0
sample_type: fixed_ordered
type: TripletSampler
configs/gaitpart/gaitpart.yaml
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data_cfg:
dataset_name: CASIA-B
dataset_root: your_path
num_workers: 1
remove_no_gallery: false
test_dataset_name: CASIA-B
evaluator_cfg:
enable_float16: false
restore_ckpt_strict: true
restore_hint: 120000
save_name: GaitPart
sampler:
batch_size: 16
sample_type: all_ordered
type: InferenceSampler
metric: euc # cos
loss_cfg:
loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
model_cfg:
model: GaitPart
backbone_cfg:
in_channels: 1
layers_cfg:
- BC-32
- BC-32
- M
- FC-64-2
- FC-64-2
- M
- FC-128-3
- FC-128-3
type: Plain
SeparateFCs:
in_channels: 128
out_channels: 128
parts_num: 16
bin_num:
- 16
optimizer_cfg:
lr: 0.0001
momentum: 0.9
solver: Adam
weight_decay: 0.0
scheduler_cfg:
gamma: 0.1
milestones:
- 100000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true
log_iter: 100
with_test: true
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: GaitPart
sync_BN: false
total_iter: 120000
sampler:
batch_shuffle: false
batch_size:
- 8
- 16
frames_num_fixed: 30
frames_num_max: 50
frames_num_min: 25
frames_skip_num: 10
sample_type: fixed_ordered
type: TripletSampler
configs/gaitpart/gaitpart_GREW.yaml
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data_cfg:
dataset_name: GREW
dataset_root: your_path
dataset_partition: ./datasets/GREW/GREW.json
num_workers: 4
remove_no_gallery: false # Remove probe if no gallery for it
test_dataset_name: GREW
evaluator_cfg:
enable_float16: false
restore_ckpt_strict: true
restore_hint: 250000
save_name: GaitPart
eval_func: identification_GREW_submission # identification_real_scene # identification_GREW_submission
sampler:
batch_size: 4
sample_type: all_ordered
type: InferenceSampler
metric: euc # cos
loss_cfg:
loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
model_cfg:
model: GaitPart
backbone_cfg:
in_channels: 1
layers_cfg:
- BC-32
- BC-32
- M
- BC-64
- BC-64
- M
- FC-128-3
- FC-128-3
- FC-256-3
- FC-256-3
type: Plain
SeparateFCs:
in_channels: 256
out_channels: 256
parts_num: 16
bin_num:
- 16
optimizer_cfg:
lr: 0.0001
momentum: 0.9
solver: Adam
weight_decay: 0.0
scheduler_cfg:
gamma: 0.1
milestones:
- 150000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true
fix_BN: false
log_iter: 100
with_test: false
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: GaitPart
sync_BN: false
total_iter: 250000
sampler:
batch_shuffle: false
batch_size:
- 32
- 4
frames_num_fixed: 30
frames_num_max: 50
frames_num_min: 25
frames_skip_num: 10
sample_type: fixed_ordered
type: TripletSampler
configs/gaitpart/gaitpart_OUMVLP.yaml
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data_cfg:
dataset_name: OUMVLP
dataset_root: your_path
dataset_partition: ./datasets/OUMVLP/OUMVLP.json
num_workers: 4
remove_no_gallery: false
test_dataset_name: OUMVLP
evaluator_cfg:
enable_float16: false
restore_ckpt_strict: true
restore_hint: 250000
save_name: GaitPart
sampler:
batch_size: 4
sample_type: all_ordered
type: InferenceSampler
metric: euc # cos
loss_cfg:
loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
model_cfg:
model: GaitPart
backbone_cfg:
in_channels: 1
layers_cfg:
- BC-32
- BC-32
- M
- BC-64
- BC-64
- M
- FC-128-3
- FC-128-3
- FC-256-3
- FC-256-3
type: Plain
SeparateFCs:
in_channels: 256
out_channels: 256
parts_num: 16
bin_num:
- 16
optimizer_cfg:
lr: 0.0001
momentum: 0.9
solver: Adam
weight_decay: 0.0
scheduler_cfg:
gamma: 0.1
milestones:
- 150000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true
fix_BN: false
log_iter: 100
with_test: true
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: GaitPart
sync_BN: false
total_iter: 250000
sampler:
batch_shuffle: false
batch_size:
- 32
- 16
frames_num_fixed: 30
frames_num_max: 50
frames_num_min: 25
frames_skip_num: 10
sample_type: fixed_ordered
type: TripletSampler
configs/gaitset/gaitset.yaml
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data_cfg:
dataset_name: CASIA-B
dataset_root: your_path
num_workers: 1
remove_no_gallery: false
test_dataset_name: CASIA-B
evaluator_cfg:
enable_float16: false
restore_ckpt_strict: true
restore_hint: 40000
save_name: GaitSet
sampler:
batch_size: 16
sample_type: all_ordered
type: InferenceSampler
metric: euc # cos
loss_cfg:
loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
model_cfg:
model: GaitSet
in_channels:
- 1
- 32
- 64
- 128
SeparateFCs:
in_channels: 128
out_channels: 256
parts_num: 62
bin_num:
- 16
- 8
- 4
- 2
- 1
optimizer_cfg:
lr: 0.1
momentum: 0.9
solver: SGD
weight_decay: 0.0005
scheduler_cfg:
gamma: 0.1
milestones:
- 10000
- 20000
- 30000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true
log_iter: 100
with_test: true
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: GaitSet
sync_BN: false
total_iter: 40000
sampler:
batch_shuffle: false
batch_size:
- 8
- 16
frames_num_fixed: 30
frames_num_max: 50
frames_num_min: 25
sample_type: fixed_unordered
type: TripletSampler
configs/gaitset/gaitset_GREW.yaml
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data_cfg:
dataset_name: GREW
dataset_root: your_path
dataset_partition: ./datasets/GREW/GREW.json
num_workers: 4
remove_no_gallery: false # Remove probe if no gallery for it
test_dataset_name: GREW
evaluator_cfg:
enable_float16: true
restore_ckpt_strict: true
restore_hint: 250000
save_name: GaitSet
eval_func: identification_GREW_submission # identification_real_scene # identification_GREW_submission
sampler:
batch_size: 4
sample_type: all_ordered
type: InferenceSampler
metric: euc # cos
loss_cfg:
loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
model_cfg:
model: GaitSet
in_channels:
- 1
- 64
- 128
- 256
SeparateFCs:
in_channels: 256
out_channels: 256
parts_num: 62
bin_num:
- 16
- 8
- 4
- 2
- 1
optimizer_cfg:
lr: 0.0001
momentum: 0.9
solver: Adam
weight_decay: 0
scheduler_cfg:
gamma: 0.1
milestones:
- 150000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true
fix_BN: false
with_test: false
log_iter: 100
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: GaitSet
sync_BN: false
total_iter: 250000
sampler:
batch_shuffle: false
batch_size:
- 32
- 4
frames_num_fixed: 30
frames_num_max: 50
frames_num_min: 25
sample_type: fixed_unordered
type: TripletSampler
configs/gaitset/gaitset_OUMVLP.yaml
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data_cfg:
dataset_name: OUMVLP
dataset_root: your_path
dataset_partition: ./datasets/OUMVLP/OUMVLP.json
num_workers: 4
remove_no_gallery: false
test_dataset_name: OUMVLP
evaluator_cfg:
enable_float16: true
restore_ckpt_strict: true
restore_hint: 250000
save_name: GaitSet
sampler:
batch_size: 4
sample_type: all_ordered
type: InferenceSampler
metric: euc # cos
loss_cfg:
loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
model_cfg:
model: GaitSet
in_channels:
- 1
- 64
- 128
- 256
SeparateFCs:
in_channels: 256
out_channels: 256
parts_num: 62
bin_num:
- 16
- 8
- 4
- 2
- 1
optimizer_cfg:
lr: 0.0001
momentum: 0.9
solver: Adam
weight_decay: 0
scheduler_cfg:
gamma: 0.1
milestones:
- 150000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true
fix_BN: false
with_test: true
log_iter: 100
restore_ckpt_strict: true
restore_hint: 0
save_iter: 10000
save_name: GaitSet
sync_BN: false
total_iter: 250000
sampler:
batch_shuffle: false
batch_size:
- 32
- 16
frames_num_fixed: 30
frames_num_max: 50
frames_num_min: 25
sample_type: fixed_unordered
type: TripletSampler
configs/gln/gln_phase1.yaml
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data_cfg:
dataset_name: CASIA-B
dataset_root: your_path
dataset_partition: ./datasets/CASIA-B/CASIA-B_include_005.json
num_workers: 1
cache: false
remove_no_gallery: false
test_dataset_name: CASIA-B
evaluator_cfg:
enable_distributed: true
enable_float16: false
restore_ckpt_strict: true
restore_hint: 40000
save_name: GLN_P1
sampler:
batch_size: 8
sample_type: all_ordered
type: InferenceSampler
metric: euc # euc
transform:
- img_w: 128
type: BaseSilCuttingTransform
loss_cfg:
- loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
# - loss_term_weight: 0.1
# scale: 1
# type: CrossEntropyLoss
# log_prefix: softmax
model_cfg:
model: GLN
class_num: 74
lateral_dim : 256
hidden_dim : 256
dropout : 0.9
in_channels:
- 1
- 32
- 64
- 128
SeparateFCs:
in_channels: 256
out_channels: 256
parts_num: 93
bin_num:
- 16
- 8
- 4
- 2
- 1
Lateral_pretraining: true
optimizer_cfg:
lr: 0.1
momentum: 0.9
solver: SGD
weight_decay: 0.0005
# lr: 0.0001
# momentum: 0.9
# solver: Adam
# weight_decay: 0.0005
scheduler_cfg:
gamma: 0.1
milestones:
- 10000
- 20000
- 30000
scheduler: MultiStepLR
trainer_cfg:
enable_float16: true
fix_layers: false
with_test: true
log_iter: 100
optimizer_reset: false
restore_ckpt_strict: true
restore_hint: 0
save_iter: 2000
save_name: GLN_P1
sync_BN: true
total_iter: 40000
sampler:
batch_shuffle: false
batch_size:
- 8
- 16
frames_num_fixed: 30
frames_skip_num: 0
sample_type: fixed_ordered
type: TripletSampler
transform:
- img_w: 128
type: BaseSilCuttingTransform
configs/gln/gln_phase2.yaml
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data_cfg:
dataset_name: CASIA-B
dataset_root: your_path
dataset_partition: ./datasets/CASIA-B/CASIA-B_include_005.json
num_workers: 1
remove_no_gallery: false
test_dataset_name: CASIA-B
evaluator_cfg:
enable_distributed: true
enable_float16: false
restore_ckpt_strict: true
restore_hint: 40000
save_name: GLN_P2
sampler:
batch_size: 2
sample_type: all_ordered
type: InferenceSampler
metric: euc # euc
transform:
- img_w: 128
type: BaseSilCuttingTransform
loss_cfg:
- loss_term_weight: 1.0
margin: 0.2
type: TripletLoss
log_prefix: triplet
- loss_term_weight: 0.1
scale: 16
type: CrossEntropyLoss
log_prefix: softmax
model_cfg:
model: GLN
class_num: 74
lateral_dim : 256
hidden_dim : 256
dropout : 0.9
in_channels:
- 1
- 32
- 64
- 128
SeparateFCs:
in_channels: 256
out_channels: 256
parts_num: 93
bin_num:
- 16
- 8
- 4
- 2
- 1
Lateral_pretraining: false
optimizer_cfg:
lr: 0.01
momentum: 0.9
solver: SGD
weight_decay: 0.0005
scheduler_cfg:
gamma: 0.1
milestones:
- 10000
- 20000
- 30000
scheduler: MultiStepLR
trainer_cfg:
enable_distributed: true
enable_float16: true
fix_layers: false
log_iter: 100
optimizer_reset: true
scheduler_reset: true
restore_ckpt_strict: false
restore_hint: output/CASIA-B/GLN/GLN_P1/checkpoints/GLN_P1-40000.pt
save_iter: 2000
save_name: GLN_P2
sync_BN: true
total_iter: 40000
sampler:
batch_shuffle: false
batch_size:
- 8
- 16
frames_num_fixed: 30
frames_skip_num: 0
sample_type: fixed_ordered
type: TripletSampler
transform:
- img_w: 128
type: BaseSilCuttingTransform