_base_ = './yolox_tiny_8x8_300e_coco.py'

# model settings
model = dict(
    bbox_head=dict(num_classes=6))

# dataset settings
dataset_type = 'HWCarDataset'
data_root = 'data/huawei_car_full/'
data = dict(
    samples_per_gpu=8,
    workers_per_gpu=8,
    train=dict(
        dataset=dict(
            type=dataset_type,
            ann_file=data_root + 'voc07_trainval.json',
            img_prefix=data_root,
            pipeline=[
                dict(type='LoadImageFromFile', to_float32=True),
                dict(type='LoadAnnotations', with_bbox=True)
            ],
            filter_empty_gt=False,
        )),
    val=dict(
        type=dataset_type,
        ann_file=data_root + 'voc07_test.json',
        img_prefix=data_root),
    test=dict(
        type=dataset_type,
        ann_file=data_root + 'voc07_test.json',
        img_prefix=data_root)
)

# use 1 gpu
optimizer = dict(lr=0.01/8,)

_base_ = './yolox_tiny_8x8_300e_coco.py'

# model settings
model = dict(
    bbox_head=dict(num_classes=6))

# dataset settings
dataset_type = 'HWCarDataset'
data_root = 'data/huawei_car_full/'
data = dict(
    samples_per_gpu=8,
    workers_per_gpu=8,
    train=dict(
        dataset=dict(
            type=dataset_type,
            ann_file=data_root + 'voc07_trainval.json',
            img_prefix=data_root,
            pipeline=[
                dict(type='LoadImageFromFile', to_float32=True),
                dict(type='LoadAnnotations', with_bbox=True)
            ],
            filter_empty_gt=False,
        )),
    val=dict(
        type=dataset_type,
        ann_file=data_root + 'voc07_test.json',
        img_prefix=data_root),
    test=dict(
        type=dataset_type,
        ann_file=data_root + 'voc07_test.json',
        img_prefix=data_root)
)

# use 1 gpu
optimizer = dict(lr=0.01/8,)

# model settings # dataset settings # use 1 gpu