File size: 2,754 Bytes
09a3fa9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 | # Copyright (c) OpenMMLab. All rights reserved.
import random
from unittest import TestCase
import numpy as np
import pytest
import torch
from mmengine.structures import PixelData
class TestPixelData(TestCase):
def setup_data(self):
metainfo = dict(
img_id=random.randint(0, 100),
img_shape=(random.randint(400, 600), random.randint(400, 600)))
image = np.random.randint(0, 255, (4, 20, 40))
featmap = torch.randint(0, 255, (10, 20, 40))
pixel_data = PixelData(metainfo=metainfo, image=image, featmap=featmap)
return pixel_data
def test_set_data(self):
pixel_data = self.setup_data()
# test set '_metainfo_fields' or '_data_fields'
with self.assertRaises(AttributeError):
pixel_data._metainfo_fields = 1
with self.assertRaises(AttributeError):
pixel_data._data_fields = 1
# value only supports (torch.Tensor, np.ndarray)
with self.assertRaises(AssertionError):
pixel_data.v = 'value'
# The width and height must be the same
with self.assertRaises(AssertionError):
pixel_data.map2 = torch.randint(0, 255, (3, 21, 41))
# The dimension must be 3 or 2
with self.assertRaises(AssertionError):
pixel_data.map2 = torch.randint(0, 255, (1, 3, 20, 40))
pixel_data.map2 = torch.randint(0, 255, (3, 20, 40))
assert 'map2' in pixel_data
pixel_data.map3 = torch.randint(0, 255, (20, 40))
assert tuple(pixel_data.map3.shape) == (1, 20, 40)
def test_getitem(self):
pixel_data = PixelData()
pixel_data = self.setup_data()
slice_pixel_data = pixel_data[10:15, 20:30]
assert slice_pixel_data.shape == (5, 10)
pixel_data = self.setup_data()
slice_pixel_data = pixel_data[10, 20:30]
assert slice_pixel_data.shape == (1, 10)
# must be tuple
item = torch.Tensor([1, 2, 3, 4])
with pytest.raises(
TypeError,
match=f'Unsupported type {type(item)} for slicing PixelData'):
pixel_data[item]
item = 1
with pytest.raises(
TypeError,
match=f'Unsupported type {type(item)} for slicing PixelData'):
pixel_data[item]
item = (5.5, 5)
with pytest.raises(
TypeError,
match=('The type of element in input must be int or slice, '
f'but got {type(item[0])}')):
pixel_data[item]
def test_shape(self):
pixel_data = self.setup_data()
assert pixel_data.shape == (20, 40)
pixel_data = PixelData()
assert pixel_data.shape is None
|