Faster RCNN 源码解析(3.2) -- Anchor 生成(generate_anchors.py)

基于源码的实现

generate_anchors.py

生成多尺度和多比例的锚点。这里由generate_anthors函数主要完成，可以看到，使用了 3 个尺度( 128, 256, and 512)以及 3 个比例(1:1,1:2,2:1)。一个锚点由w, h, x_ctr, y_ctr固定，也就是宽、高、x center和y center固定。

#功能描述：生成多尺度、多宽高比的anchors。  #          尺度为：128,256,512; 宽高比为：1:2,1:1,2:1  import numpy as np  #提供矩阵运算功能的库  #生成anchors总函数：ratios为一个列表，表示宽高比为：1:2,1:1,2:1  #2**x表示:2^x，scales:[2^3 2^4 2^5],即:[8 16 32]  def generate_anchors(base_size=16, ratios=[0.5, 1, 2],                       scales=2**np.arange(3, 6)):      """     Generate anchor (reference) windows by enumerating aspect ratios X     scales wrt a reference (0, 0, 15, 15) window.     """      base_anchor = np.array([1, 1, base_size, base_size]) - 1  #新建一个数组：base_anchor:[0 0 15 15]      ratio_anchors = _ratio_enum(base_anchor, ratios)  #枚举各种宽高比      anchors = np.vstack([_scale_enum(ratio_anchors[i, :], scales)  #枚举各种尺度，vstack:竖向合并数组                           for i in xrange(ratio_anchors.shape[0])]) #shape[0]:读取矩阵第一维长度，其值为3      return anchors  #用于返回width,height,(x,y)中心坐标(对于一个anchor窗口)  def _whctrs(anchor):      """     Return width, height, x center, and y center for an anchor (window).     """      #anchor:存储了窗口左上角，右下角的坐标      w = anchor[2] - anchor[0] + 1      h = anchor[3] - anchor[1] + 1      x_ctr = anchor[0] + 0.5 * (w - 1)  #anchor中心点坐标      y_ctr = anchor[1] + 0.5 * (h - 1)      return w, h, x_ctr, y_ctr  #给定一组宽高向量，输出各个anchor，即预测窗口，**输出anchor的面积相等，只是宽高比不同**  def _mkanchors(ws, hs, x_ctr, y_ctr):      #ws:[23 16 11]，hs:[12 16 22],ws和hs一一对应。      """     Given a vector of widths (ws) and heights (hs) around a center     (x_ctr, y_ctr), output a set of anchors (windows).     """      ws = ws[:, np.newaxis]  #newaxis:将数组转置      hs = hs[:, np.newaxis]      anchors = np.hstack((x_ctr - 0.5 * (ws - 1),    #hstack、vstack:合并数组                           y_ctr - 0.5 * (hs - 1),    #anchor：[[-3.5 2 18.5 13]                           x_ctr + 0.5 * (ws - 1),     #        [0  0  15  15]                           y_ctr + 0.5 * (hs - 1)))     #       [2.5 -3 12.5 18]]      return anchors  #枚举一个anchor的各种宽高比，anchor[0 0 15 15],ratios[0.5,1,2]  def _ratio_enum(anchor, ratios):      """   列举关于一个anchor的三种宽高比 1:2,1:1,2:1     Enumerate a set of anchors for each aspect ratio wrt an anchor.     """      w, h, x_ctr, y_ctr = _whctrs(anchor)  #返回宽高和中心坐标，w:16,h:16,x_ctr:7.5,y_ctr:7.5      size = w * h   #size:16*16=256      size_ratios = size / ratios  #256/ratios[0.5,1,2]=[512,256,128]      #round()方法返回x的四舍五入的数字，sqrt()方法返回数字x的平方根      ws = np.round(np.sqrt(size_ratios)) #ws:[23 16 11]      hs = np.round(ws * ratios)    #hs:[12 16 22],ws和hs一一对应。as:23&12      anchors = _mkanchors(ws, hs, x_ctr, y_ctr)  #给定一组宽高向量，输出各个预测窗口      return anchors  #枚举一个anchor的各种尺度，以anchor[0 0 15 15]为例,scales[8 16 32]  def _scale_enum(anchor, scales):      """   列举关于一个anchor的三种尺度 128*128,256*256,512*512     Enumerate a set of anchors for each scale wrt an anchor.     """      w, h, x_ctr, y_ctr = _whctrs(anchor) #返回宽高和中心坐标，w:16,h:16,x_ctr:7.5,y_ctr:7.5      ws = w * scales   #[128 256 512]      hs = h * scales   #[128 256 512]      anchors = _mkanchors(ws, hs, x_ctr, y_ctr) #[[-56 -56 71 71] [-120 -120 135 135] [-248 -248 263 263]]      return anchors  if __name__ == '__main__':  #主函数      import time      t = time.time()      a = generate_anchors()  #生成anchor（窗口）      print time.time() - t   #显示时间      print a      from IPython import embed; embed()  

参考资料

generate_anchors.py from fastr-rcnn
generate_anchors.py analyze