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fcos_r50_torch_1x_mot20_crowdhuman.py
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_base_ = './fcos_r50_torch_1x_coco.py'
data_root0 = 'data/tracking/crowdhuman/'
data_root1 = 'data/tracking/MOT20/'
CLASSES = ('pedestrian', )
train_dataset = dict(
data_source=dict(
ann_file=[
data_root1 + 'annotations/train_cocoformat.json', data_root0 +
'/annotations/crowdhuman_train.json', data_root0 +
'/annotations/crowdhuman_val.json'
],
img_prefix=[
data_root1 + 'train', data_root0 + 'train', data_root0 + 'val'
],
classes=CLASSES))
val_dataset = dict(
data_source=dict(
ann_file=data_root0 + '/annotations/crowdhuman_val.json',
img_prefix=data_root0 + 'val',
classes=CLASSES))
data = dict(
imgs_per_gpu=2, workers_per_gpu=2, train=train_dataset, val=val_dataset)
model = dict(head=dict(num_classes=1))
optimizer = dict(lr=0.001)
eval_pipelines = [
dict(
mode='test',
evaluators=[
dict(type='CocoDetectionEvaluator', classes=CLASSES),
],
)
]
checkpoint_config = dict(interval=1)
checkpoint_sync_export = True
export = dict(export_neck=True)
load_from = 'https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/EasyCV/modelzoo/detection/fcos/fcos_epoch_12.pth'