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目标识别网络Faster RCNN:Pytorch源码分析(二)
锚框(anchors)产生:感觉论文这块内容说的不太细致,只能深挖源码了~from __future__ import print_function# --------------------------------------------------------# Faster R-CNN# Copyright (c) 2015 Microsoft# Licensed under The MIT License [see LICENSE for details]# Written by Ro原创 2020-11-21 21:50:00 · 202 阅读 · 0 评论 -
目标识别网络Faster-RCNN:Pytorch源码分析(一)
Faster-RCNN base & Faster-RCNN top (除去RPN部分) :Github源码如下(vgg16.py):# --------------------------------------------------------# Tensorflow Faster R-CNN# Licensed under The MIT License [see LICENSE for details]# Written by Xinlei Chen# ------------原创 2020-11-21 11:20:28 · 472 阅读 · 0 评论 -
目标识别网络SSD:Pytorch源码分析(二)
1.先验框生成Github源码:from __future__ import divisionfrom math import sqrt as sqrtfrom itertools import product as productimport torchclass PriorBox(object): """Compute priorbox coordinates in center-offset form for each source feature map. ""原创 2020-11-20 10:25:44 · 334 阅读 · 0 评论 -
目标识别网络SSD:Pytorch源码分析(一)
1.IOU计算:先验框表示方式变换:(cx, cy, w, h) to (xmin, ymin, xmax, ymax):def point_form(boxes): """ Convert prior_boxes to (xmin, ymin, xmax, ymax) representation for comparison to point form ground truth data. Args: boxes: (tensor) center-size原创 2020-11-18 13:38:10 · 300 阅读 · 0 评论