Image Segmentation
Transformers
PyTorch
upernet
Inference Endpoints
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_base_ = [
    '../_base_/models/fpn_r50.py', '../_base_/datasets/FoodSeg103.py',
    '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
]

model = dict(decode_head=dict(num_classes=104))

optimizer_config = dict()

runner = dict(type='IterBasedRunner', max_iters=80000)
checkpoint_config = dict(by_epoch=False, interval=4000)
evaluation = dict(interval=4000, metric='mIoU')