segmentation/configs/_base_/datasets/pascal_context.py

# ---------------------------------------------------------------------------------------------------
# CLIP-DINOiser
# authors: Monika Wysoczanska, Warsaw University of Technology
# ----------------------------------------------------------------------------------------------------
# Modified from TCL
# Copyright (c) 2023 Kakao Brain. All Rights Reserved.
# ------------------------------------------------------------------------------
_base_ = ["../custom_import.py"]
# dataset settings
dataset_type = "PascalContextDataset"
data_root = "./data/VOCdevkit/VOC2010"
test_pipeline = [
    dict(type="LoadImageFromFile"),
    dict(type='ToRGB'),
    dict(
        type="MultiScaleFlipAug",
        img_scale=(2048, 448),
        flip=False,
        transforms=[
            dict(type="Resize", keep_ratio=True),
            dict(type="RandomFlip"),
            dict(type="ImageToTensorV2", keys=["img"]),
            dict(type="Collect", keys=["img"], meta_keys=['ori_shape', 'img_shape', 'pad_shape', 'flip', 'img_info']),
        ],
    ),
]
data = dict(
    test=dict(
        type=dataset_type,
        data_root=data_root,
        img_dir="JPEGImages",
        ann_dir="SegmentationClassContext",
        split="ImageSets/SegmentationContext/val.txt",
        pipeline=test_pipeline,
    )
)

test_cfg = dict(mode="slide", stride=(224, 224), crop_size=(448, 448))