Image Segmentation
Transformers
PyTorch
upernet
Inference Endpoints
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import os.path as osp

import mmcv
import pytest
from mmcv.utils import build_from_cfg

from mmseg.datasets.builder import PIPELINES


def test_multi_scale_flip_aug():
    # test assertion if img_scale=None, img_ratios=1 (not float).
    with pytest.raises(AssertionError):
        tta_transform = dict(
            type='MultiScaleFlipAug',
            img_scale=None,
            img_ratios=1,
            transforms=[dict(type='Resize', keep_ratio=False)],
        )
        build_from_cfg(tta_transform, PIPELINES)

    # test assertion if img_scale=None, img_ratios=None.
    with pytest.raises(AssertionError):
        tta_transform = dict(
            type='MultiScaleFlipAug',
            img_scale=None,
            img_ratios=None,
            transforms=[dict(type='Resize', keep_ratio=False)],
        )
        build_from_cfg(tta_transform, PIPELINES)

    # test assertion if img_scale=(512, 512), img_ratios=1 (not float).
    with pytest.raises(AssertionError):
        tta_transform = dict(
            type='MultiScaleFlipAug',
            img_scale=(512, 512),
            img_ratios=1,
            transforms=[dict(type='Resize', keep_ratio=False)],
        )
        build_from_cfg(tta_transform, PIPELINES)

    tta_transform = dict(
        type='MultiScaleFlipAug',
        img_scale=(512, 512),
        img_ratios=[0.5, 1.0, 2.0],
        flip=False,
        transforms=[dict(type='Resize', keep_ratio=False)],
    )
    tta_module = build_from_cfg(tta_transform, PIPELINES)

    results = dict()
    # (288, 512, 3)
    img = mmcv.imread(
        osp.join(osp.dirname(__file__), '../data/color.jpg'), 'color')
    results['img'] = img
    results['img_shape'] = img.shape
    results['ori_shape'] = img.shape
    # Set initial values for default meta_keys
    results['pad_shape'] = img.shape
    results['scale_factor'] = 1.0

    tta_results = tta_module(results.copy())
    assert tta_results['scale'] == [(256, 256), (512, 512), (1024, 1024)]
    assert tta_results['flip'] == [False, False, False]

    tta_transform = dict(
        type='MultiScaleFlipAug',
        img_scale=(512, 512),
        img_ratios=[0.5, 1.0, 2.0],
        flip=True,
        transforms=[dict(type='Resize', keep_ratio=False)],
    )
    tta_module = build_from_cfg(tta_transform, PIPELINES)
    tta_results = tta_module(results.copy())
    assert tta_results['scale'] == [(256, 256), (256, 256), (512, 512),
                                    (512, 512), (1024, 1024), (1024, 1024)]
    assert tta_results['flip'] == [False, True, False, True, False, True]

    tta_transform = dict(
        type='MultiScaleFlipAug',
        img_scale=(512, 512),
        img_ratios=1.0,
        flip=False,
        transforms=[dict(type='Resize', keep_ratio=False)],
    )
    tta_module = build_from_cfg(tta_transform, PIPELINES)
    tta_results = tta_module(results.copy())
    assert tta_results['scale'] == [(512, 512)]
    assert tta_results['flip'] == [False]

    tta_transform = dict(
        type='MultiScaleFlipAug',
        img_scale=(512, 512),
        img_ratios=1.0,
        flip=True,
        transforms=[dict(type='Resize', keep_ratio=False)],
    )
    tta_module = build_from_cfg(tta_transform, PIPELINES)
    tta_results = tta_module(results.copy())
    assert tta_results['scale'] == [(512, 512), (512, 512)]
    assert tta_results['flip'] == [False, True]

    tta_transform = dict(
        type='MultiScaleFlipAug',
        img_scale=None,
        img_ratios=[0.5, 1.0, 2.0],
        flip=False,
        transforms=[dict(type='Resize', keep_ratio=False)],
    )
    tta_module = build_from_cfg(tta_transform, PIPELINES)
    tta_results = tta_module(results.copy())
    assert tta_results['scale'] == [(256, 144), (512, 288), (1024, 576)]
    assert tta_results['flip'] == [False, False, False]

    tta_transform = dict(
        type='MultiScaleFlipAug',
        img_scale=None,
        img_ratios=[0.5, 1.0, 2.0],
        flip=True,
        transforms=[dict(type='Resize', keep_ratio=False)],
    )
    tta_module = build_from_cfg(tta_transform, PIPELINES)
    tta_results = tta_module(results.copy())
    assert tta_results['scale'] == [(256, 144), (256, 144), (512, 288),
                                    (512, 288), (1024, 576), (1024, 576)]
    assert tta_results['flip'] == [False, True, False, True, False, True]

    tta_transform = dict(
        type='MultiScaleFlipAug',
        img_scale=[(256, 256), (512, 512), (1024, 1024)],
        img_ratios=None,
        flip=False,
        transforms=[dict(type='Resize', keep_ratio=False)],
    )
    tta_module = build_from_cfg(tta_transform, PIPELINES)
    tta_results = tta_module(results.copy())
    assert tta_results['scale'] == [(256, 256), (512, 512), (1024, 1024)]
    assert tta_results['flip'] == [False, False, False]

    tta_transform = dict(
        type='MultiScaleFlipAug',
        img_scale=[(256, 256), (512, 512), (1024, 1024)],
        img_ratios=None,
        flip=True,
        transforms=[dict(type='Resize', keep_ratio=False)],
    )
    tta_module = build_from_cfg(tta_transform, PIPELINES)
    tta_results = tta_module(results.copy())
    assert tta_results['scale'] == [(256, 256), (256, 256), (512, 512),
                                    (512, 512), (1024, 1024), (1024, 1024)]
    assert tta_results['flip'] == [False, True, False, True, False, True]