未验证 提交 c5b17022 编写于 作者: C Chang Xu 提交者: GitHub

Add PicoDet Demo/Config (#1299)

上级 5a1f3073
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/
eval_height: &eval_height 416
eval_width: &eval_width 416
eval_size: &eval_size [*eval_height, *eval_width]
worker_num: 0
EvalReader:
inputs_def:
image_shape: [1, 3, *eval_height, *eval_width]
sample_transforms:
- Decode: {}
- Resize: {interp: 2, target_size: *eval_size, keep_ratio: False}
- NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
- Permute: {}
batch_size: 32
Global:
reader_config: ./configs/picodet_reader.yml
input_list: ['image', 'scale_factor']
Evaluation: True
model_dir: ./picodet_s_416_coco_lcnet/
model_filename: model.pdmodel
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: l2
node:
- conv2d_138.tmp_1
- tmp_2
- conv2d_146.tmp_1
- tmp_5
- conv2d_162.tmp_1
- tmp_11
- conv2d_154.tmp_1
- tmp_8
Quantization:
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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