更换文档检测模型

This commit is contained in:
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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metric: COCO
num_classes: 80
# Datset configuration
TrainDataset:
!COCODataSet
image_dir: train2017
anno_path: annotations/instances_train2017.json
dataset_dir: dataset/coco/
EvalDataset:
!COCODataSet
image_dir: val2017
anno_path: annotations/instances_val2017.json
dataset_dir: dataset/coco/
worker_num: 6
eval_height: &eval_height 416
eval_width: &eval_width 416
eval_size: &eval_size [*eval_height, *eval_width]
EvalReader:
sample_transforms:
- Decode: {}
- Resize: {interp: 2, target_size: *eval_size, keep_ratio: False}
- NormalizeImage: {mean: [0, 0, 0], std: [1, 1, 1], is_scale: True}
- Permute: {}
batch_transforms:
- PadBatch: {pad_to_stride: 32}
batch_size: 8
shuffle: false

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Global:
reader_config: ./configs/picodet_reader.yml
include_nms: True
Evaluation: True
model_dir: ./picodet_s_416_coco_npu/
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: l2
QuantAware:
use_pact: true
activation_quantize_type: 'moving_average_abs_max'
weight_bits: 8
activation_bits: 8
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 8000
eval_iter: 1000
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00001
T_max: 8000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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Global:
reader_config: configs/ppyoloe_crn_l_80e_sliced_visdrone_640_025_reader.yml
input_list: ['image', 'scale_factor']
arch: YOLO
include_nms: True
Evaluation: True
model_dir: ../../output_inference/ppyoloe_crn_l_80e_sliced_visdrone_640_025
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
onnx_format: True
use_pact: False
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 8000
eval_iter: 500
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 6000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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metric: COCO
num_classes: 10
# Datset configuration
TrainDataset:
!COCODataSet
image_dir: train_images_640_025
anno_path: train_640_025.json
dataset_dir: dataset/visdrone_sliced
EvalDataset:
!COCODataSet
image_dir: val_images_640_025
anno_path: val_640_025.json
dataset_dir: dataset/visdrone_sliced
worker_num: 0
# preprocess reader in test
EvalReader:
sample_transforms:
- Decode: {}
- Resize: {target_size: [640, 640], keep_ratio: False, interp: 2}
#- NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
- Permute: {}
batch_size: 16

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Global:
reader_config: configs/ppyoloe_reader.yml
include_nms: True
Evaluation: True
model_dir: ./ppyoloe_crn_l_300e_coco
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
use_pact: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 5000
eval_iter: 1000
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 6000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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Global:
reader_config: configs/ppyoloe_plus_reader.yml
include_nms: True
Evaluation: True
model_dir: ../../output_inference/ppyoloe_plus_crn_t_auxhead_300e_coco/
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
onnx_format: True
use_pact: False
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 8000
eval_iter: 1000
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 6000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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Global:
reader_config: configs/ppyoloe_plus_reader.yml
include_nms: True
Evaluation: True
model_dir: ./ppyoloe_plus_crn_l_80e_coco
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
use_pact: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 5000
eval_iter: 1000
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 6000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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Global:
reader_config: configs/ppyoloe_plus_reader.yml
include_nms: True
Evaluation: True
model_dir: ./ppyoloe_plus_crn_m_80e_coco
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
use_pact: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 5000
eval_iter: 1000
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 6000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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metric: COCO
num_classes: 80
# Datset configuration
TrainDataset:
!COCODataSet
image_dir: train2017
anno_path: annotations/instances_train2017.json
dataset_dir: dataset/coco/
EvalDataset:
!COCODataSet
image_dir: val2017
anno_path: annotations/instances_val2017.json
dataset_dir: dataset/coco/
worker_num: 0
# preprocess reader in test
EvalReader:
sample_transforms:
- Decode: {}
- Resize: {target_size: [640, 640], keep_ratio: False, interp: 2}
- NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
- Permute: {}
batch_size: 4

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Global:
reader_config: configs/ppyoloe_plus_reader.yml
include_nms: True
Evaluation: True
model_dir: ./ppyoloe_plus_crn_s_80e_coco
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
use_pact: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 5000
eval_iter: 1000
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 6000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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Global:
reader_config: configs/ppyoloe_plus_reader.yml
include_nms: True
Evaluation: True
model_dir: ../../output_inference/ppyoloe_plus_sod_crn_l_80e_coco
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
onnx_format: True
use_pact: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 1
eval_iter: 1
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 6000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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Global:
reader_config: configs/ppyoloe_plus_reader.yml
include_nms: True
Evaluation: True
model_dir: ./ppyoloe_plus_crn_x_80e_coco
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
use_pact: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 5000
eval_iter: 1000
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 6000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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metric: COCO
num_classes: 80
# Datset configuration
TrainDataset:
!COCODataSet
image_dir: train2017
anno_path: annotations/instances_train2017.json
dataset_dir: dataset/coco/
EvalDataset:
!COCODataSet
image_dir: val2017
anno_path: annotations/instances_val2017.json
dataset_dir: dataset/coco/
worker_num: 0
# preprocess reader in test
EvalReader:
sample_transforms:
- Decode: {}
- Resize: {target_size: [640, 640], keep_ratio: False, interp: 2}
- NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
- Permute: {}
batch_size: 4

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Global:
reader_config: configs/rtdetr_reader.yml
include_nms: True
Evaluation: True
model_dir: ./rtdetr_hgnetv2_l_6x_coco/
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
onnx_format: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
- matmul_v2
TrainConfig:
train_iter: 200
eval_iter: 50
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 10000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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Global:
reader_config: configs/rtdetr_reader.yml
include_nms: True
Evaluation: True
model_dir: ./rtdetr_hgnetv2_x_6x_coco/
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
onnx_format: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
- matmul_v2
TrainConfig:
train_iter: 500
eval_iter: 100
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 10000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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Global:
reader_config: configs/rtdetr_reader.yml
include_nms: True
Evaluation: True
model_dir: ./rtdetr_r101vd_6x_coco/
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
onnx_format: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
- matmul_v2
TrainConfig:
train_iter: 200
eval_iter: 50
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 10000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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Global:
reader_config: configs/rtdetr_reader.yml
include_nms: True
Evaluation: True
model_dir: ./rtdetr_r50vd_6x_coco/
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
onnx_format: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
- matmul_v2
TrainConfig:
train_iter: 500
eval_iter: 100
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 10000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05

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metric: COCO
num_classes: 80
# Datset configuration
TrainDataset:
!COCODataSet
image_dir: train2017
anno_path: annotations/instances_train2017.json
dataset_dir: dataset/coco/
!COCODataSet
image_dir: val2017
anno_path: annotations/instances_val2017.json
dataset_dir: dataset/coco/
EvalDataset:
!COCODataSet
image_dir: val2017
anno_path: annotations/instances_val2017.json
dataset_dir: dataset/coco/
TestDataset:
!COCODataSet
image_dir: val2017
anno_path: annotations/instances_val2017.json
dataset_dir: dataset/coco/
worker_num: 0
# preprocess reader in test
EvalReader:
sample_transforms:
- Decode: {}
- Resize: {target_size: [640, 640], keep_ratio: False, interp: 2}
- NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
- Permute: {}
batch_size: 1
shuffle: false
drop_last: false

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metric: COCO
num_classes: 80
# Datset configuration
TrainDataset:
!COCODataSet
image_dir: train2017
anno_path: annotations/instances_train2017.json
dataset_dir: dataset/coco/
EvalDataset:
!COCODataSet
image_dir: val2017
anno_path: annotations/instances_val2017.json
dataset_dir: dataset/coco/
worker_num: 0
# preprocess reader in test
TestReader:
sample_transforms:
- Decode: {}
- Resize: {target_size: [640, 640], keep_ratio: True, interp: 1}
- Pad: {size: [640, 640], fill_value: [114., 114., 114.]}
- Permute: {}
batch_size: 1

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Global:
reader_config: configs/yolov5_reader.yml
include_nms: True
Evaluation: True
model_dir: ./yolov5_s_300e_coco
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
use_pact: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 3000
eval_iter: 1000
learning_rate: 0.00001
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05
target_metric: 0.365

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Global:
reader_config: configs/yolov5_reader.yml
include_nms: True
Evaluation: True
model_dir: ./yolov6mt_s_400e_coco
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 8000
eval_iter: 1000
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 8000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 0.00004

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Global:
reader_config: configs/yolov5_reader.yml
include_nms: True
Evaluation: True
model_dir: ./yolov7_l_300e_coco
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 8000
eval_iter: 1000
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 8000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 0.00004

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metric: COCO
num_classes: 80
# Dataset configuration
TrainDataset:
!COCODataSet
image_dir: train2017
anno_path: annotations/instances_train2017.json
dataset_dir: dataset/coco/
EvalDataset:
!COCODataSet
image_dir: val2017
anno_path: annotations/instances_val2017.json
dataset_dir: dataset/coco/
worker_num: 0
# preprocess reader in test
EvalReader:
sample_transforms:
- Decode: {}
- Resize: {target_size: [640, 640], keep_ratio: True, interp: 1}
- Pad: {size: [640, 640], fill_value: [114., 114., 114.]}
- NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
- Permute: {}
batch_size: 4

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Global:
reader_config: configs/yolov8_reader.yml
include_nms: True
Evaluation: True
model_dir: ./yolov8_s_500e_coco_trt_nms/
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: soft_label
QuantAware:
onnx_format: true
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
TrainConfig:
train_iter: 8000
eval_iter: 1000
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 10000
optimizer_builder:
optimizer:
type: SGD
weight_decay: 4.0e-05