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ppyoloe_crn_l_36e_coco_xpu.yml
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ppyoloe_crn_l_36e_coco_xpu.yml
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_BASE_: [
'../datasets/coco_detection.yml',
'../runtime.yml',
'./_base_/optimizer_36e_xpu.yml',
'./_base_/ppyoloe_reader.yml',
]
# note: these are default values (use_gpu = true and use_xpu = false) for CI.
# set use_gpu = false and use_xpu = true for training.
use_gpu: true
use_xpu: false
log_iter: 100
snapshot_epoch: 1
weights: output/ppyoloe_crn_l_36e_coco/model_final
find_unused_parameters: True
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/CSPResNetb_l_pretrained.pdparams
depth_mult: 1.0
width_mult: 1.0
TrainReader:
batch_size: 8
architecture: YOLOv3
norm_type: sync_bn
use_ema: true
ema_decay: 0.9998
YOLOv3:
backbone: CSPResNet
neck: CustomCSPPAN
yolo_head: PPYOLOEHead
post_process: ~
CSPResNet:
layers: [3, 6, 6, 3]
channels: [64, 128, 256, 512, 1024]
return_idx: [1, 2, 3]
use_large_stem: True
CustomCSPPAN:
out_channels: [768, 384, 192]
stage_num: 1
block_num: 3
act: 'swish'
spp: true
PPYOLOEHead:
fpn_strides: [32, 16, 8]
grid_cell_scale: 5.0
grid_cell_offset: 0.5
static_assigner_epoch: 4
use_varifocal_loss: True
loss_weight: {class: 1.0, iou: 2.5, dfl: 0.5}
static_assigner:
name: ATSSAssigner
topk: 9
assigner:
name: TaskAlignedAssigner
topk: 13
alpha: 1.0
beta: 6.0
nms:
name: MultiClassNMS
nms_top_k: 1000
keep_top_k: 300
score_threshold: 0.01
nms_threshold: 0.7