maskrcnn_benchmark 代码详解之 anchor_generator.py

前言：

　　在RPN中需要生成拥有不同步长(stride)不同大小(size)以及不同长环比(ratio)的anchor,　在maskrcnn_benchmark中，这一工作由anchor_generator.py完成。anchor_generator.py生成所需的不同特征图上的anchor，需要注意的是，如果在backbone中采用了FPN的话，需要保证，stride个数，size个数以及FPN的层数相同。其详细代码为：

# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import math

import numpy as np
import torch
from torch import nn

from maskrcnn_benchmark.structures.bounding_box import BoxList


# todo 把anchors转换成buffer的list
class BufferList(nn.Module):
    """
    Similar to nn.ParameterList, but for buffers
    """

    def __init__(self, buffers=None):
        super(BufferList, self).__init__()
        # 如果存在anchor，则把他保存为buffer格式
        if buffers is not None:
            self.extend(buffers)

    def extend(self, buffers):
        offset = len(self)
        # 循环的把各个大小尺度下不同窗宽比anchor，保存为buffer
        for i, buffer in enumerate(buffers):
            self.register_buffer(str(offset + i), buffer)
        return self

    def __len__(self):
        return len(self._buffers)

    def __iter__(self):
        return iter(self._buffers.values())


class AnchorGenerator(nn.Module):
    """
    For a set of image sizes and feature maps, computes a set
    of anchors
    """

    def __init__(
        self,
        sizes=(128, 256, 512),
        aspect_ratios=(0.5, 1.0, 2.0),
        anchor_strides=(8, 16, 32),
        straddle_thresh=0,
    ):
        super(AnchorGenerator, self).__init__()
        # 如果只从一个特征图上提取特征，即不使用rpn
        if len(anchor_strides) == 1:
            # 获得anchor滑动步长
            anchor_stride = anchor_strides[0]
            cell_anchors = [
                generate_anchors(anchor_stride, sizes, aspect_ratios).float()
            ]
        else:
            # 如果anchor滑动步长列表与anchor大小的列表长度不同则报错
            if len(anchor_strides) != len(sizes):
                raise RuntimeError("FPN should have #anchor_strides == #sizes")
            # 循环的得到不同大小尺度不同步长情况下不同长宽比的anchor
            cell_anchors = [
                generate_anchors(
                    anchor_stride,
                    size if isinstance(size, (tuple, list)) else (size,),
                    aspect_ratios
                ).float()
                for anchor_stride, size in zip(anchor_strides, sizes)
            ]
        self.strides = anchor_strides