未验证 提交 8f79fd39 编写于 作者: W wangxinxin08 提交者: GitHub

refine yolov3 configs (#2756)

* refine yolov3 configs

* fix dataset problem
上级 a9255173
metric: VOC
map_type: 11point
map_type: integral
num_classes: 4
TrainDataset:
......
......@@ -9,37 +9,6 @@ _BASE_: [
snapshot_epoch: 5
weights: output/yolov3_mobilenet_v1_270e_voc/model_final
TrainReader:
inputs_def:
num_max_boxes: 50
sample_transforms:
- Decode: {}
- Mixup: {alpha: 1.5, beta: 1.5}
- RandomDistort: {}
- RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
- RandomCrop: {}
- RandomFlip: {}
batch_transforms:
- BatchRandomResize:
target_size: [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
random_size: True
random_interp: True
keep_ratio: False
- NormalizeBox: {}
- PadBox: {num_max_boxes: 50}
- BboxXYXY2XYWH: {}
- NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
- Permute: {}
- Gt2YoloTarget:
anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
anchors: [[10, 13], [16, 30], [33, 23], [30, 61], [62, 45], [59, 119], [116, 90], [156, 198], [373, 326]]
downsample_ratios: [32, 16, 8]
num_classes: 20
batch_size: 8
shuffle: true
drop_last: true
mixup_epoch: 250
LearningRate:
base_lr: 0.001
schedulers:
......
......@@ -5,45 +5,12 @@ _BASE_: [
'_base_/yolov3_reader.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams
norm_type: sync_bn
weights: output/yolov3_mobilenet_v1_roadsign/model_final
metric: VOC
map_type: integral
YOLOv3Loss:
ignore_thresh: 0.7
label_smooth: true
TrainReader:
inputs_def:
num_max_boxes: 50
sample_transforms:
- Decode: {}
- Mixup: {alpha: 1.5, beta: 1.5}
- RandomDistort: {}
- RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
- RandomCrop: {}
- RandomFlip: {}
batch_transforms:
- BatchRandomResize:
target_size: [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
random_size: True
random_interp: True
keep_ratio: False
- NormalizeBox: {}
- PadBox: {num_max_boxes: 50}
- BboxXYXY2XYWH: {}
- NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
- Permute: {}
- Gt2YoloTarget:
anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
anchors: [[10, 13], [16, 30], [33, 23], [30, 61], [62, 45], [59, 119], [116, 90], [156, 198], [373, 326]]
downsample_ratios: [32, 16, 8]
num_classes: 4
batch_size: 8
shuffle: true
drop_last: true
snapshot_epoch: 2
epoch: 40
......
_BASE_: [
'../datasets/coco_detection.yml',
'../datasets/voc.yml',
'../runtime.yml',
'_base_/optimizer_270e.yml',
'_base_/yolov3_mobilenet_v1.yml',
......@@ -10,37 +10,6 @@ snapshot_epoch: 5
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV1_ssld_pretrained.pdparams
weights: output/yolov3_mobilenet_v1_ssld_270e_voc/model_final
TrainReader:
inputs_def:
num_max_boxes: 50
sample_transforms:
- Decode: {}
- Mixup: {alpha: 1.5, beta: 1.5}
- RandomDistort: {}
- RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
- RandomCrop: {}
- RandomFlip: {}
batch_transforms:
- BatchRandomResize:
target_size: [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
random_size: True
random_interp: True
keep_ratio: False
- NormalizeBox: {}
- PadBox: {num_max_boxes: 50}
- BboxXYXY2XYWH: {}
- NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
- Permute: {}
- Gt2YoloTarget:
anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
anchors: [[10, 13], [16, 30], [33, 23], [30, 61], [62, 45], [59, 119], [116, 90], [156, 198], [373, 326]]
downsample_ratios: [32, 16, 8]
num_classes: 20
batch_size: 8
shuffle: true
drop_last: true
mixup_epoch: 250
LearningRate:
base_lr: 0.001
schedulers:
......
......@@ -9,37 +9,6 @@ _BASE_: [
snapshot_epoch: 5
weights: output/yolov3_mobilenet_v3_large_270e_voc/model_final
TrainReader:
inputs_def:
num_max_boxes: 50
sample_transforms:
- Decode: {}
- Mixup: {alpha: 1.5, beta: 1.5}
- RandomDistort: {}
- RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
- RandomCrop: {}
- RandomFlip: {}
batch_transforms:
- BatchRandomResize:
target_size: [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
random_size: True
random_interp: True
keep_ratio: False
- NormalizeBox: {}
- PadBox: {num_max_boxes: 50}
- BboxXYXY2XYWH: {}
- NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
- Permute: {}
- Gt2YoloTarget:
anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
anchors: [[10, 13], [16, 30], [33, 23], [30, 61], [62, 45], [59, 119], [116, 90], [156, 198], [373, 326]]
downsample_ratios: [32, 16, 8]
num_classes: 20
batch_size: 8
shuffle: true
drop_last: true
mixup_epoch: 250
LearningRate:
base_lr: 0.001
schedulers:
......
_BASE_: [
'../datasets/coco_detection.yml',
'../datasets/voc.yml',
'../runtime.yml',
'_base_/optimizer_270e.yml',
'_base_/yolov3_mobilenet_v3_large.yml',
......@@ -10,37 +10,6 @@ snapshot_epoch: 5
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x1_0_ssld_pretrained.pdparams
weights: output/yolov3_mobilenet_v3_large_ssld_270e_voc/model_final
TrainReader:
inputs_def:
num_max_boxes: 50
sample_transforms:
- Decode: {}
- Mixup: {alpha: 1.5, beta: 1.5}
- RandomDistort: {}
- RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
- RandomCrop: {}
- RandomFlip: {}
batch_transforms:
- BatchRandomResize:
target_size: [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
random_size: True
random_interp: True
keep_ratio: False
- NormalizeBox: {}
- PadBox: {num_max_boxes: 50}
- BboxXYXY2XYWH: {}
- NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
- Permute: {}
- Gt2YoloTarget:
anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
anchors: [[10, 13], [16, 30], [33, 23], [30, 61], [62, 45], [59, 119], [116, 90], [156, 198], [373, 326]]
downsample_ratios: [32, 16, 8]
num_classes: 20
batch_size: 8
shuffle: true
drop_last: true
mixup_epoch: 250
LearningRate:
base_lr: 0.001
schedulers:
......
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