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- # --------------------------------------------------------
- # Tensorflow Faster R-CNN
- # Licensed under The MIT License [see LICENSE for details]
- # Written by Xinlei Chen
- # --------------------------------------------------------
- from __future__ import absolute_import
- from __future__ import division
- from __future__ import print_function
- import tensorflow as tf
- import numpy as np
- from segment.sheet_resolve.lib.layer_utils.generate_anchors import generate_anchors
- def generate_anchors_pre(height, width, feat_stride=16, anchor_scales=(8, 16, 32), anchor_ratios=(0.5, 1, 2)):
- shift_x = tf.range(width) * feat_stride # width
- shift_y = tf.range(height) * feat_stride # height
- shift_x, shift_y = tf.meshgrid(shift_x, shift_y)
- sx = tf.reshape(shift_x, shape=(-1,))
- sy = tf.reshape(shift_y, shape=(-1,))
- shifts = tf.transpose(tf.stack([sx, sy, sx, sy]))
- K = tf.multiply(width, height)
- shifts = tf.transpose(tf.reshape(shifts, shape=[1, K, 4]), perm=(1, 0, 2))
- anchors = generate_anchors(ratios=np.array(anchor_ratios), scales=np.array(anchor_scales))
- A = anchors.shape[0]
- anchor_constant = tf.constant(anchors.reshape((1, A, 4)), dtype=tf.int32)
- length = K * A
- anchors_tf = tf.reshape(tf.add(anchor_constant, shifts), shape=(length, 4))
-
- return tf.cast(anchors_tf, dtype=tf.float32), length
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