mmdetection/tests/test_datasets/test_tta.py

# Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from unittest import TestCase

import mmcv
import pytest

from mmdet.datasets.transforms import *  # noqa
from mmdet.registry import TRANSFORMS


class TestMuitiScaleFlipAug(TestCase):

    def test_exception(self):
        with pytest.raises(TypeError):
            tta_transform = dict(
                type='TestTimeAug',
                transforms=[dict(type='Resize', keep_ratio=False)],
            )
            TRANSFORMS.build(tta_transform)

    def test_multi_scale_flip_aug(self):
        tta_transform = dict(
            type='TestTimeAug',
            transforms=[[
                dict(type='Resize', scale=scale, keep_ratio=False)
                for scale in [(256, 256), (512, 512), (1024, 1024)]
            ],
                        [
                            dict(
                                type='mmdet.PackDetInputs',
                                meta_keys=('img_id', 'img_path', 'ori_shape',
                                           'img_shape', 'scale_factor'))
                        ]])
        tta_module = TRANSFORMS.build(tta_transform)

        results = dict()
        img = mmcv.imread(
            osp.join(osp.dirname(__file__), '../data/color.jpg'), 'color')
        results['img_id'] = '1'
        results['img_path'] = 'data/color.jpg'
        results['img'] = img
        results['ori_shape'] = img.shape
        results['ori_height'] = img.shape[0]
        results['ori_width'] = img.shape[1]
        # Set initial values for default meta_keys
        results['pad_shape'] = img.shape
        results['scale_factor'] = 1.0

        tta_results = tta_module(results.copy())
        assert [img.shape
                for img in tta_results['inputs']] == [(3, 256, 256),
                                                      (3, 512, 512),
                                                      (3, 1024, 1024)]

        tta_transform = dict(
            type='TestTimeAug',
            transforms=[
                [
                    dict(type='Resize', scale=scale, keep_ratio=False)
                    for scale in [(256, 256), (512, 512), (1024, 1024)]
                ],
                [
                    dict(type='RandomFlip', prob=0., direction='horizontal'),
                    dict(type='RandomFlip', prob=1., direction='horizontal')
                ],
                [
                    dict(
                        type='mmdet.PackDetInputs',
                        meta_keys=('img_id', 'img_path', 'ori_shape',
                                   'img_shape', 'scale_factor', 'flip',
                                   'flip_direction'))
                ]
            ])
        tta_module = TRANSFORMS.build(tta_transform)
        tta_results: dict = tta_module(results.copy())
        assert [img.shape
                for img in tta_results['inputs']] == [(3, 256, 256),
                                                      (3, 256, 256),
                                                      (3, 512, 512),
                                                      (3, 512, 512),
                                                      (3, 1024, 1024),
                                                      (3, 1024, 1024)]
        assert [
            data_sample.metainfo['flip']
            for data_sample in tta_results['data_samples']
        ] == [False, True, False, True, False, True]

        tta_transform = dict(
            type='TestTimeAug',
            transforms=[[
                dict(type='Resize', scale=(512, 512), keep_ratio=False)
            ],
                        [
                            dict(
                                type='mmdet.PackDetInputs',
                                meta_keys=('img_id', 'img_path', 'ori_shape',
                                           'img_shape', 'scale_factor'))
                        ]])
        tta_module = TRANSFORMS.build(tta_transform)
        tta_results = tta_module(results.copy())
        assert [tta_results['inputs'][0].shape] == [(3, 512, 512)]

        tta_transform = dict(
            type='TestTimeAug',
            transforms=[
                [dict(type='Resize', scale=(512, 512), keep_ratio=False)],
                [
                    dict(type='RandomFlip', prob=0., direction='horizontal'),
                    dict(type='RandomFlip', prob=1., direction='horizontal')
                ],
                [
                    dict(
                        type='mmdet.PackDetInputs',
                        meta_keys=('img_id', 'img_path', 'ori_shape',
                                   'img_shape', 'scale_factor', 'flip',
                                   'flip_direction'))
                ]
            ])
        tta_module = TRANSFORMS.build(tta_transform)
        tta_results = tta_module(results.copy())
        assert [img.shape for img in tta_results['inputs']] == [(3, 512, 512),
                                                                (3, 512, 512)]
        assert [
            data_sample.metainfo['flip']
            for data_sample in tta_results['data_samples']
        ] == [False, True]

        tta_transform = dict(
            type='TestTimeAug',
            transforms=[[
                dict(type='Resize', scale_factor=r, keep_ratio=False)
                for r in [0.5, 1.0, 2.0]
            ],
                        [
                            dict(
                                type='mmdet.PackDetInputs',
                                meta_keys=('img_id', 'img_path', 'ori_shape',
                                           'img_shape', 'scale_factor'))
                        ]])
        tta_module = TRANSFORMS.build(tta_transform)
        tta_results = tta_module(results.copy())
        assert [img.shape for img in tta_results['inputs']] == [(3, 144, 256),
                                                                (3, 288, 512),
                                                                (3, 576, 1024)]

        tta_transform = dict(
            type='TestTimeAug',
            transforms=[
                [
                    dict(type='Resize', scale_factor=r, keep_ratio=True)
                    for r in [0.5, 1.0, 2.0]
                ],
                [
                    dict(type='RandomFlip', prob=0., direction='horizontal'),
                    dict(type='RandomFlip', prob=1., direction='horizontal')
                ],
                [
                    dict(
                        type='mmdet.PackDetInputs',
                        meta_keys=('img_id', 'img_path', 'ori_shape',
                                   'img_shape', 'scale_factor', 'flip',
                                   'flip_direction'))
                ]
            ])
        tta_module = TRANSFORMS.build(tta_transform)
        tta_results = tta_module(results.copy())
        assert [img.shape for img in tta_results['inputs']] == [(3, 144, 256),
                                                                (3, 144, 256),
                                                                (3, 288, 512),
                                                                (3, 288, 512),
                                                                (3, 576, 1024),
                                                                (3, 576, 1024)]
        assert [
            data_sample.metainfo['flip']
            for data_sample in tta_results['data_samples']
        ] == [False, True, False, True, False, True]