PaddleClas/ppcls/configs/Pedestrian/strong_baseline_m1.yaml

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3.9 KiB
YAML

# global configs
Global:
checkpoints: null
pretrained_model: null
output_dir: "./output/"
device: "gpu"
save_interval: 40
eval_during_train: True
eval_interval: 10
epochs: 120
print_batch_step: 20
use_visualdl: False
eval_mode: "retrieval"
retrieval_feature_from: "features" # 'backbone' or 'features'
re_ranking: False
# used for static mode and model export
image_shape: [3, 256, 128]
save_inference_dir: "./inference"
# model architecture
Arch:
name: "RecModel"
infer_output_key: "features"
infer_add_softmax: False
Backbone:
name: "ResNet50_last_stage_stride1"
pretrained: True
stem_act: null
BackboneStopLayer:
name: "flatten"
Neck:
name: BNNeck
num_features: &feat_dim 2048
weight_attr:
initializer:
name: Constant
value: 1.0
bias_attr:
initializer:
name: Constant
value: 0.0
learning_rate: 1.0e-20 # NOTE: Temporarily set lr small enough to freeze the bias to zero
Head:
name: "FC"
embedding_size: *feat_dim
class_num: 751
weight_attr:
initializer:
name: Normal
std: 0.001
bias_attr: False
# loss function config for traing/eval process
Loss:
Train:
- CELoss:
weight: 1.0
epsilon: 0.1
- TripletLossV2:
weight: 1.0
margin: 0.3
normalize_feature: False
feature_from: "backbone"
Eval:
- CELoss:
weight: 1.0
Optimizer:
name: Adam
lr:
name: Piecewise
decay_epochs: [30, 60]
values: [0.00035, 0.000035, 0.0000035]
warmup_epoch: 10
warmup_start_lr: 0.0000035
by_epoch: True
last_epoch: 0
regularizer:
name: 'L2'
coeff: 0.0005
# data loader for train and eval
DataLoader:
Train:
dataset:
name: "Market1501"
image_root: "./dataset/"
cls_label_path: "bounding_box_train"
backend: "pil"
transform_ops:
- ResizeImage:
size: [128, 256]
return_numpy: False
backend: "pil"
- RandFlipImage:
flip_code: 1
- Pad:
padding: 10
- RandCropImageV2:
size: [128, 256]
- ToTensor:
- Normalize:
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
- RandomErasing:
EPSILON: 0.5
sl: 0.02
sh: 0.4
r1: 0.3
mean: [0.485, 0.456, 0.406]
sampler:
name: DistributedRandomIdentitySampler
batch_size: 64
num_instances: 4
drop_last: False
shuffle: True
loader:
num_workers: 4
use_shared_memory: True
Eval:
Query:
dataset:
name: "Market1501"
image_root: "./dataset/"
cls_label_path: "query"
backend: "pil"
transform_ops:
- ResizeImage:
size: [128, 256]
return_numpy: False
backend: "pil"
- ToTensor:
- Normalize:
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
sampler:
name: DistributedBatchSampler
batch_size: 128
drop_last: False
shuffle: False
loader:
num_workers: 4
use_shared_memory: True
Gallery:
dataset:
name: "Market1501"
image_root: "./dataset/"
cls_label_path: "bounding_box_test"
backend: "pil"
transform_ops:
- ResizeImage:
size: [128, 256]
return_numpy: False
backend: "pil"
- ToTensor:
- Normalize:
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
sampler:
name: DistributedBatchSampler
batch_size: 128
drop_last: False
shuffle: False
loader:
num_workers: 4
use_shared_memory: True
Metric:
Eval:
- Recallk:
topk: [1, 5]
- mAP: {}