更换文档检测模型

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2024-08-27 14:42:45 +08:00
parent aea6f19951
commit 1514e09c40
2072 changed files with 254336 additions and 4967 deletions

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use_gpu: true
log_iter: 50
save_dir: output
snapshot_epoch: 10
weights: output/vitpose_base_simple_coco_256x192/model_final
epoch: 210
num_joints: &num_joints 17
pixel_std: &pixel_std 200
metric: KeyPointTopDownCOCOEval
num_classes: 1
train_height: &train_height 256
train_width: &train_width 192
trainsize: &trainsize [*train_width, *train_height]
hmsize: &hmsize [48, 64]
flip_perm: &flip_perm [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10], [11, 12], [13, 14], [15, 16]]
#####model
architecture: VitPose_TopDown
pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/keypoint/mae_pretrain_vit_base.pdparams
VitPose_TopDown:
backbone: ViT
head: TopdownHeatmapSimpleHead
post_process: VitPosePostProcess
loss: KeyPointMSELoss
flip_test: True
ViT:
img_size: [256, 192]
patch_size: 16
embed_dim: 768
depth: 12
num_heads: 12
ratio: 1
mlp_ratio: 4
qkv_bias: True
drop_path_rate: 0.3
epsilon: 0.000001
TopdownHeatmapSimpleHead:
in_channels: 768
num_deconv_layers: 2
num_deconv_filters: [256,256]
num_deconv_kernels: [4,4]
out_channels: 17
shift_heatmap: False
flip_pairs: *flip_perm
extra: {final_conv_kernel: 1}
VitPosePostProcess:
use_dark: True
KeyPointMSELoss:
use_target_weight: true
loss_scale: 1.0
####optimizer
LearningRate:
base_lr: 0.0005
schedulers:
- !PiecewiseDecay
gamma: 0.1
milestones: [170, 200]
- !LinearWarmup
start_factor: 0.001
steps: 500
OptimizerBuilder:
clip_grad_by_norm: 1.0
optimizer:
type: AdamWDL
betas: [0.9, 0.999]
weight_decay: 0.1
num_layers: 12
layer_decay: 0.75
filter_bias_and_bn: True
skip_decay_names: ['pos_embed','norm']
set_param_lr_func: 'layerwise_lr_decay'
#####data
TrainDataset:
!KeypointTopDownCocoDataset
image_dir: train2017
anno_path: annotations/person_keypoints_train2017.json
dataset_dir: dataset/coco
num_joints: *num_joints
trainsize: *trainsize
pixel_std: *pixel_std
center_scale: 0.4
EvalDataset:
!KeypointTopDownCocoDataset
image_dir: val2017
anno_path: annotations/person_keypoints_val2017.json
dataset_dir: dataset/coco
num_joints: *num_joints
trainsize: *trainsize
pixel_std: *pixel_std
image_thre: 0.0
use_gt_bbox: True
TestDataset:
!ImageFolder
anno_path: dataset/coco/keypoint_imagelist.txt
worker_num: 4
global_mean: &global_mean [0.485, 0.456, 0.406]
global_std: &global_std [0.229, 0.224, 0.225]
TrainReader:
sample_transforms:
- RandomFlipHalfBodyTransform:
scale: 0.5
rot: 40
num_joints_half_body: 8
prob_half_body: 0.3
pixel_std: *pixel_std
trainsize: *trainsize
upper_body_ids: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
flip_pairs: *flip_perm
- TopDownAffine:
trainsize: *trainsize
use_udp: true
- ToHeatmapsTopDown_UDP:
hmsize: *hmsize
sigma: 2
batch_transforms:
- NormalizeImage:
mean: *global_mean
std: *global_std
is_scale: true
- Permute: {}
batch_size: 64
shuffle: True
drop_last: True
EvalReader:
sample_transforms:
- TopDownAffine:
trainsize: *trainsize
use_udp: true
batch_transforms:
- NormalizeImage:
mean: *global_mean
std: *global_std
is_scale: true
- Permute: {}
batch_size: 64
TestReader:
inputs_def:
image_shape: [3, *train_height, *train_width]
sample_transforms:
- Decode: {}
- TopDownEvalAffine:
trainsize: *trainsize
- NormalizeImage:
mean: *global_mean
std: *global_std
is_scale: true
- Permute: {}
batch_size: 1
fuse_normalize: false

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use_gpu: true
log_iter: 50
save_dir: output
snapshot_epoch: 10
weights: output/vitpose_base_simple_coco_256x192/model_final
epoch: 210
num_joints: &num_joints 17
pixel_std: &pixel_std 200
metric: KeyPointTopDownCOCOEval
num_classes: 1
train_height: &train_height 256
train_width: &train_width 192
trainsize: &trainsize [*train_width, *train_height]
hmsize: &hmsize [48, 64]
flip_perm: &flip_perm [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10], [11, 12], [13, 14], [15, 16]]
#####model
architecture: VitPose_TopDown
pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/keypoint/mae_pretrain_vit_base.pdparams
VitPose_TopDown:
backbone: ViT
head: TopdownHeatmapSimpleHead
post_process: VitPosePostProcess
loss: KeyPointMSELoss
flip_test: True
ViT:
img_size: [256, 192]
qkv_bias: True
drop_path_rate: 0.3
epsilon: 0.000001
TopdownHeatmapSimpleHead:
in_channels: 768
num_deconv_layers: 0
num_deconv_filters: []
num_deconv_kernels: []
upsample: 4
shift_heatmap: False
flip_pairs: *flip_perm
extra: {final_conv_kernel: 3}
VitPosePostProcess:
use_dark: True
KeyPointMSELoss:
use_target_weight: true
loss_scale: 1.0
####optimizer
LearningRate:
base_lr: 0.0005
schedulers:
- !PiecewiseDecay
gamma: 0.1
milestones: [170, 200]
- !LinearWarmup
start_factor: 0.001
steps: 500
OptimizerBuilder:
clip_grad_by_norm: 1.0
optimizer:
type: AdamWDL
betas: [0.9, 0.999]
weight_decay: 0.1
num_layers: 12
layer_decay: 0.75
filter_bias_and_bn: True
skip_decay_names: ['pos_embed','norm']
set_param_lr_func: 'layerwise_lr_decay'
#####data
TrainDataset:
!KeypointTopDownCocoDataset
image_dir: train2017
anno_path: annotations/person_keypoints_train2017.json
dataset_dir: dataset/coco
num_joints: *num_joints
trainsize: *trainsize
pixel_std: *pixel_std
center_scale: 0.4
EvalDataset:
!KeypointTopDownCocoDataset
image_dir: val2017
anno_path: annotations/person_keypoints_val2017.json
dataset_dir: dataset/coco
num_joints: *num_joints
trainsize: *trainsize
pixel_std: *pixel_std
image_thre: 0.0
use_gt_bbox: True
TestDataset:
!ImageFolder
anno_path: dataset/coco/keypoint_imagelist.txt
worker_num: 4
global_mean: &global_mean [0.485, 0.456, 0.406]
global_std: &global_std [0.229, 0.224, 0.225]
TrainReader:
sample_transforms:
- RandomFlipHalfBodyTransform:
scale: 0.5
rot: 40
num_joints_half_body: 8
prob_half_body: 0.3
pixel_std: *pixel_std
trainsize: *trainsize
upper_body_ids: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
flip_pairs: *flip_perm
- TopDownAffine:
trainsize: *trainsize
use_udp: true
- ToHeatmapsTopDown_UDP:
hmsize: *hmsize
sigma: 2
batch_transforms:
- NormalizeImage:
mean: *global_mean
std: *global_std
is_scale: true
- Permute: {}
batch_size: 64
shuffle: True
drop_last: True
EvalReader:
sample_transforms:
- TopDownAffine:
trainsize: *trainsize
use_udp: true
batch_transforms:
- NormalizeImage:
mean: *global_mean
std: *global_std
is_scale: true
- Permute: {}
batch_size: 64
TestReader:
inputs_def:
image_shape: [3, *train_height, *train_width]
sample_transforms:
- Decode: {}
- TopDownEvalAffine:
trainsize: *trainsize
- NormalizeImage:
mean: *global_mean
std: *global_std
is_scale: true
- Permute: {}
batch_size: 1
fuse_normalize: false