def testSmallRandomDistort(self):
"""Tests random_distort with small-change arguments.
We pass parameters to random_distort that make it so that it should
change the image relatively little, and then check that in fact it
changed relatively little.
"""
total_boxes = 3
im_shape = (600, 900, 3)
config = EasyDict({
'brightness': {
'max_delta': 0.00001,
},
'hue': {
'max_delta': 0.00001,
},
'saturation': {
'lower': 0.99999,
'upper': 1.00001,
},
'contrast': {
'lower': 0.99999,
'upper': 1.00001
}
})
label = 3
image, bboxes = self._get_image_with_boxes(im_shape, total_boxes)
# Add a label to each bbox.
bboxes_w_label = tf.concat(
[
bboxes,
tf.fill((bboxes.shape[0], 1), label)
],
axis=1
)
ret_image, ret_bboxes = self._random_distort(
image, config, bboxes_w_label
)
# Assertions
large_number = 0.1
self.assertAllClose(image, ret_image, rtol=0.05, atol=large_number)
评论列表
文章目录