def make_anchors(self):
'''
:return: [-1,4] ,all level's anchors
'''
with tf.variable_scope('make_anchors'):
anchor_list = []
with tf.name_scope('make_anchors_all_level'):
for level, base_anchor_size, stride in zip(
self.level, self.base_anchor_size_list, self.stride):
feature_map_shape = tf.shape(self.feature_pyramid[level])
feature_h, feature_w = feature_map_shape[
1], feature_map_shape[2]
temp_anchors = make_anchor.make_anchors(
base_anchor_size,
self.anchor_scales,
self.anchor_ratios,
feature_h,
feature_w,
stride,
name='make_anchor_{}'.format(level))
temp_anchors = tf.reshape(temp_anchors, [-1, 4])
anchor_list.append(temp_anchors)
all_level_anchors = tf.concat(anchor_list, axis=0)
return all_level_anchors
def make_anchors(self):
with tf.variable_scope('make_anchors'):
anchor_list = []
level_list = self.level
with tf.name_scope('make_anchors_all_level'):
for level, base_anchor_size, stride in zip(level_list, self.base_anchor_size_list, self.stride):
'''
(level, base_anchor_size) tuple:
(P2, 32), (P3, 64), (P4, 128), (P5, 256), (P6, 512)
'''
featuremap_height, featuremap_width = tf.shape(self.feature_pyramid[level])[1], \
tf.shape(self.feature_pyramid[level])[2]
# stride = base_anchor_size / 8.
# tmp_anchors = tf.py_func(
# anchor_utils_pyfunc.make_anchors,
# inp=[base_anchor_size, self.anchor_scales, self.anchor_ratios,
# featuremap_height, featuremap_width, stride],
# Tout=tf.float32
# )
tmp_anchors = make_anchor.make_anchors(base_anchor_size, self.anchor_scales, self.anchor_ratios,
featuremap_height, featuremap_width, stride,
name='make_anchors_{}'.format(level))
tmp_anchors = tf.reshape(tmp_anchors, [-1, 4])
anchor_list.append(tmp_anchors)
all_level_anchors = tf.concat(anchor_list, axis=0)
return all_level_anchors
def make_anchors(self):
with tf.variable_scope('make_anchors'):
anchor_list = []
level_list = self.level
with tf.name_scope('make_anchors_all_level'):
for level, base_anchor_size, stride in zip(
level_list, self.base_anchor_size_list, self.stride):
'''
(level, base_anchor_size) tuple:
(P2, 32), (P3, 64), (P4, 128), (P5, 256), (P6, 512)
base_anchor_size [15, 25, 40, 60, 80],,LEVEL = ['P2', 'P3', 'P4', 'P5', "P6"],,STRIDE = [4, 8, 16, 32, 64]
in small feature map, anchors one by one,dense; in higher feature map, anchors gap by stride ---bob
'''
featuremap_height, featuremap_width = tf.shape(self.feature_pyramid[level])[1], \
tf.shape(self.feature_pyramid[level])[2]
# stride = base_anchor_size / 8.
# tmp_anchors = tf.py_func(
# anchor_utils_pyfunc.make_anchors,
# inp=[base_anchor_size, self.anchor_scales, self.anchor_ratios,
# featuremap_height, featuremap_width, stride],
# Tout=tf.float32
# )
tmp_anchors = make_anchor.make_anchors(
base_anchor_size,
self.anchor_scales,
self.anchor_ratios,
featuremap_height,
featuremap_width,
stride,
name='make_anchors_{}'.format(level))
tmp_anchors = tf.reshape(tmp_anchors, [-1, 4])
anchor_list.append(tmp_anchors)
all_level_anchors = tf.concat(anchor_list, axis=0)
return all_level_anchors