def _anchor_component(self, height, width):
anchors, anchor_length = generate_anchors_pre(height, width,
self._feat_stride,
self._anchor_scales,
self._anchor_ratios)
self._anchors = Variable(torch.from_numpy(anchors).cuda())
self._anchor_length = anchor_length
def generate_anchors(self, im_info):
height = int(math.ceil(im_info[0, 0] / np.float32(self._feat_stride[0])))
width = int(math.ceil(im_info[0, 1] / np.float32(self._feat_stride[0])))
anchors, anchor_length = generate_anchors_pre(height, width, self._feat_stride, self._anchor_scales, self._anchor_ratios)
anchors = np.reshape(anchors, [-1, 4])
anchor_length = np.reshape(anchor_length, [-1])
return anchors, anchor_length
def _anchor_component(self, height, width):
# just to get the shape right
#height = int(math.ceil(self._im_info.data[0, 0] / self._feat_stride[0]))
#width = int(math.ceil(self._im_info.data[0, 1] / self._feat_stride[0]))
anchors, anchor_length = generate_anchors_pre(\
height, width,
self._feat_stride, self._anchor_scales, self._anchor_ratios)
self._anchors = Variable(torch.from_numpy(anchors).cuda())
self._anchor_length = anchor_length
def _anchor_component(self, height, width):
# just to get the shape right
#height = int(math.ceil(self._im_info.data[0, 0] / self._feat_stride[0]))
#width = int(math.ceil(self._im_info.data[0, 1] / self._feat_stride[0]))
anchors, anchor_length = generate_anchors_pre(\
height, width,
self._feat_stride, self._anchor_scales, self._anchor_ratios)
self._anchors = Variable(torch.from_numpy(anchors).cuda())
self._anchor_length = anchor_length
def _anchor_component(self, height, width):
# just to get the shape right
# 找出anchorbox,是合成的读取的图片的height和width
#height = int(math.ceil(self._im_info.data[0, 0] / self._feat_stride[0]))
#width = int(math.ceil(self._im_info.data[0, 1] / self._feat_stride[0]))
#转到snippets。py
anchors, anchor_length = generate_anchors_pre(\
height, width,
self._feat_stride, self._anchor_scales, self._anchor_ratios)
#得到9×k个anchor,送到GPU
self._anchors = torch.from_numpy(anchors).to(self._device)
self._anchor_length = anchor_length
def _anchor_component(self):
with tf.variable_scope('ANCHOR_' + self._tag) as scope:
# just to get the shape right
height = tf.to_int32(
tf.ceil(self._im_info[0] / np.float32(self._feat_stride[0])))
width = tf.to_int32(
tf.ceil(self._im_info[1] / np.float32(self._feat_stride[0])))
anchors, anchor_length = generate_anchors_pre(
height, width, self._feat_stride, self._anchor_scales,
self._anchor_ratios)
anchors.set_shape([None, 4])
anchor_length.set_shape([])
self._anchors = anchors
self._anchor_length = anchor_length
def _anchor_component(self):
with tf.variable_scope('ANCHOR_' + self._tag) as scope:
# just to get the shape right
height = tf.to_int32(tf.ceil(self._im_info[0] / np.float32(self._feat_stride[0])))
width = tf.to_int32(tf.ceil(self._im_info[1] / np.float32(self._feat_stride[0])))
anchors, anchor_length = generate_anchors_pre(
height,
width,
self._feat_stride,
self._anchor_scales,
self._anchor_ratios
)
anchors.set_shape([None, 4])
anchor_length.set_shape([])
self._anchors = anchors
self._anchor_length = anchor_length
def _anchor_component_fpn(self, net_conv):
# just to get the shape right
#height = int(math.ceil(self._im_info.data[0, 0] / self._feat_stride[0]))
#width = int(math.ceil(self._im_info.data[0, 1] / self._feat_stride[0]))
anchors_total = []
anchor_length_total = []
for idx, p in enumerate(net_conv):
height = p.size(2)
width = p.size(3)
anchors, anchor_length = generate_anchors_pre(\
height, width,
[self._feat_stride[idx]], [self._anchor_scales[idx]], self._anchor_ratios)
anchors_total.append(Variable(torch.from_numpy(anchors).cuda()))
anchor_length_total.append(anchor_length)
self._anchors = anchors_total
self._anchor_length = anchor_length_total
import tensorflow as tf
import numpy as np
from layer_utils import snippets
if __name__ == '__main__':
anchors, length = snippets.generate_anchors_pre(40, 60, 16)
print(anchors[:32, :])
print(length)
import tensorflow as tf
import numpy as np
from layer_utils import snippets
if __name__ == '__main__':
anchors, length = snippets.generate_anchors_pre(40, 60, 16)
print(anchors[:32, :])
print(length)
