def testAnchorGenerationDict(self, min_level, max_level, aspect_ratios,
expected_boxes):
image_size = [64, 64]
levels = range(min_level, max_level + 1)
anchor_sizes = dict((str(level), 2**(level + 1)) for level in levels)
strides = dict((str(level), 2**level) for level in levels)
anchor_gen = anchor_generator.AnchorGenerator(
anchor_sizes=anchor_sizes,
scales=[1.],
aspect_ratios=aspect_ratios,
strides=strides,
clip_boxes=False)
anchors = anchor_gen(image_size)
for k in expected_boxes.keys():
self.assertAllClose(expected_boxes[k], anchors[k].numpy())
def testAnchorGeneration(self, min_level, max_level, aspect_ratios,
expected_boxes):
image_size = [64, 64]
levels = range(min_level, max_level + 1)
anchor_sizes = [2**(level + 1) for level in levels]
strides = [2**level for level in levels]
anchor_gen = anchor_generator.AnchorGenerator(
anchor_sizes=anchor_sizes,
scales=[1.],
aspect_ratios=aspect_ratios,
strides=strides)
anchors = anchor_gen(image_size)
anchors = [tf.reshape(anchor, [-1, 4]) for anchor in anchors]
anchors = tf.concat(anchors, axis=0).numpy()
self.assertAllClose(expected_boxes, anchors)
def build_anchor_generator(min_level, max_level, num_scales, aspect_ratios,
anchor_size):
"""Build anchor generator from levels."""
anchor_sizes = collections.OrderedDict()
strides = collections.OrderedDict()
scales = []
for scale in range(num_scales):
scales.append(2**(scale / float(num_scales)))
for level in range(min_level, max_level + 1):
stride = 2**level
strides[str(level)] = stride
anchor_sizes[str(level)] = anchor_size * stride
anchor_gen = anchor_generator.AnchorGenerator(anchor_sizes=anchor_sizes,
scales=scales,
aspect_ratios=aspect_ratios,
strides=strides)
return anchor_gen