AP未达到论文中报告的结果 about ai-tod

[Chasel-Tsui]

能否提供完整的config呢？训练集使用的是train set还是trainval set？

[Cathy1900]

能否提供完整的config呢？训练集使用的是train set还是trainval set？

这是data和优化器的设置，除了改samples_per_gpu，其余没动过了。
data = dict(
samples_per_gpu=4,
workers_per_gpu=2,
train=dict(
type='AITODDataset',
ann_file='data/AI-TOD/annotations/aitod_training_v1.0.json',
img_prefix='data/AI-TOD/trainval/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='Resize', img_scale=(800, 800), keep_ratio=True),
dict(type='RandomFlip', flip_ratio=0.5),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
]),
val=dict(
type='AITODDataset',
ann_file='data/AI-TOD/annotations/aitod_validation_v1.0.json',
img_prefix='data/AI-TOD/trainval/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(800, 800),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]),
test=dict(
type='AITODDataset',
ann_file='data/AI-TOD/annotations/aitod_test_v1_1.0.json',
img_prefix='data/AI-TOD/test/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(800, 800),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]))
evaluation = dict(interval=12, metric='bbox')
optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None)
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=2000,
warmup_ratio=0.001,
step=[8, 11])
runner = dict(type='EpochBasedRunner', max_epochs=12)

[Chasel-Tsui]

似乎是因为训练只用了train set的标签，论文里的结果是用trainval set训练得到的，config中虽然图片路径是trainval，但是标签文件可能只是train set，onedrive公开的标签中包含了trainval set的json文件

[Cathy1900]

似乎是因为训练只用了train set的标签，论文里的结果是用trainval set训练得到的，config中虽然图片路径是trainval，但是标签文件可能只是train set，onedrive公开的标签中包含了trainval set的json文件

好的，谢谢您的回复，我再调整下