Weakly Supervised Instance Segmentation using Class Peak Response论文复现以及遇到的问题

github链接

摘要：使用图像级别标签的弱监督实例分割，而不是昂贵的像素级掩码，仍然未被探索。在本文中，我们通过利用类峰值响应来启用分类网络（例如掩码提取）来解决这一具有挑战性的问题。仅使用图像标签监控，完全卷积方式的CNN分类器可以生成类响应图，其指定每个图像位置处的分类置信度。我们观察到类响应图中的局部最大值（即峰值）通常对应于驻留在每个实例内的强视觉提示。受此启发，我们首先设计一个过程，以激发从类响应图中出现的峰值。然后，出现的峰值被反向传播并有效地映射到每个对象实例的高信息区域，例如实例边界。我们将从类峰值响应生成的上述映射称为峰值响应映射（PRM）。 PRM提供了精细的详细实例级表示，即使使用一些现成的方法也可以提取实例掩码。据我们所知，我们首次报告了具有挑战性的图像级监督实例分割任务的结果。大量实验表明，我们的方法还可以提高弱监督的逐点定位以及语义分割性能，并在流行的基准测试中报告最先进的结果，包括PASCAL VOC 2012和MS COCO。

复现的时候就按照官网上说的那样：

win10或者≥ubantu14.04

GPU版本：

NVIDIA GPU + CUDA CuDNN

或者CPU可以

还有就是

Python>=3.5

PyTorch>=0.4

Jupyter Notebook and ipywidgets

我是在win10上实现的，没有GPU加速。

安装：

1.Install Nest

pip install git+https://github.com/ZhouYanzhao/Nest.git

2.Install PRM via Nest's CLI tool:

nest module install github@ZhouYanzhao/PRM:pytorch prm

测试是否成功：

nest module list --filter prm

输出：

# 3 Nest modules found.
# [0] prm.fc_resnet50 (1.0.0)
# [1] prm.peak_response_mapping (1.0.0)
# [2] prm.prm_visualize (1.0.0)

接下来就是运行了。

1.Install Nest's build-in Pytorch modules

nest module install github@ZhouYanzhao/Nest:pytorch pytorch

2.Download the PASCAL-VOC2012 dataset:在浏览器输入就行解压到demo里

http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar

3.Run the demo experiment via demo/main.ipynb

用jupyter notebook打开

得到像这样的：

这里就是训练用的，训练生成的是.pt权重文件，这是pytorch框架的权重，还有.pkl类型的，其实都一样。

这里的config.yml是设定参数用的。

_name: network_trainer
data_loaders:
  _name: fetch_data
  dataset: 
    _name: pascal_voc_classification
    data_dir: ./datasets/VOCdevkit
    year: 2012
  batch_size: 16
  num_workers: 4
  transform:
    _name: image_transform
    image_size: [448, 448]
    mean: [0.485, 0.456, 0.406]
    std: [0.229, 0.224, 0.225]
  train_augmentation:
    horizontal_flip: 0.5
  train_splits:
    - trainval
model:
  _name: peak_response_mapping
  backbone:
    _name: fc_resnet50
  win_size: 3
  sub_pixel_locating_factor: 8
  enable_peak_stimulation: true
criterion:
  _name: multilabel_soft_margin_loss
  difficult_samples: yes
optimizer:
  _name: sgd_optimizer
  lr: 0.01
  momentum: 0.9
  weight_decay: 1.0e-4
parameter:
  _name: finetune
  base_lr: 0.01
  groups:
    'features': 0.01
meters:
  loss:
    _name: loss_meter
max_epoch: 20
device: cuda
hooks:
  on_start:
    -
      _name: print_state
      formats:
        - '@CONFIG'
        - 'Model: {model}'
      join_str: '\n'
  on_end_epoch: 
    - 
      _name: print_state
      formats:
        - 'epoch: {epoch_idx}'
        - 'classification_loss: {metrics[trainval_loss]:.4f}'
    -
      _name: checkpoint
      save_dir: './snapshots'
      save_latest: yes

因为用的是CPU，所以batch_size设置成的是4，设置成16，发现卡的不行。然后就开始训练了。

训练了三天多，要不是因为无故断电了，还能训练，最后的loss下降到0.03

[2018-07-29 15:41:05,699] epoch: 0 | classification_loss: 0.1172
[2018-07-29 15:41:05,918] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt
[2018-07-29 20:29:30,672] epoch: 1 | classification_loss: 0.0758
[2018-07-29 20:29:30,812] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt
[2018-07-30 01:17:34,042] epoch: 2 | classification_loss: 0.0645
[2018-07-30 01:17:34,214] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt
[2018-07-30 06:04:50,313] epoch: 3 | classification_loss: 0.0566
[2018-07-30 06:04:50,485] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt
[2018-07-30 11:03:36,152] epoch: 4 | classification_loss: 0.0498
[2018-07-30 11:03:36,293] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt
[2018-07-30 16:09:31,468] epoch: 5 | classification_loss: 0.0444
[2018-07-30 16:09:31,683] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt
[2018-07-30 21:07:03,611] epoch: 6 | classification_loss: 0.0409
[2018-07-30 21:07:03,751] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt
[2018-07-31 01:55:32,188] epoch: 7 | classification_loss: 0.0414
[2018-07-31 01:55:32,422] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt
[2018-07-31 06:43:39,614] epoch: 8 | classification_loss: 0.0388
[2018-07-31 06:43:39,761] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt
[2018-07-31 11:32:24,822] epoch: 9 | classification_loss: 0.0351
[2018-07-31 11:32:25,025] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt
[2018-07-31 16:20:31,651] epoch: 10 | classification_loss: 0.0351
[2018-07-31 16:20:31,858] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt
[2018-07-31 21:08:55,310] epoch: 11 | classification_loss: 0.0330
[2018-07-31 21:08:55,508] checkpoint created at C:\Users\Mars\PRM-pytorch\demo\snapshots\model_latest.pt

然后是导入模型：

这回问题很大了！因为保存的是模型的参数，需要再建立一个网络，再把参数赋值进去，但导入的时候发现，有问题，新建的模型需要的是‘module.0.features.0.weight’类似命名的，而生成的权重文件都是'0.features.0.weight'这样的命名的，所以我得到的权重文件缺少了‘module.’这几个字符，先想着用notepad++直接改，但是读取的时候根本识别不了。

KeyError: ‘unexpected key “module.encoder.embedding.weight”搜到了一个类似的问题，这个问题说的正是我遇到的反例，生成的模型没有‘module.’，而生成的模型里多了‘module.’这几个字符，所以大家把权重文件中的前面那几个字符去掉了。

# 导入已经保存了的权重文件
state_dict = torch.load('myfile.pth.tar')
# 建立一个没有`module.`的权重
from collections import OrderedDict
new_state_dict = OrderedDict()
for k, v in state_dict.items():
    name = k[7:] # remove `module.`
    new_state_dict[name] = v
# load
model.load_state_dict(new_state_dict)

而我的情况恰好相反，所以我需要加上这几个字符：

先把字符串变成list，然后在前面添加`module.`

n_state = state['model']
new_state_dict = OrderedDict()
for k, v in n_state.items():
    temp_list = list(k)
    temp_list.insert(0,'module.')
    name = ''.join(temp_list)
    new_state_dict[name] = v
# load params
# print(new_state_dict)
model.load_state_dict(new_state_dict)

问题解决！

然后就都是一些小问题了。这是全部的代码：

%matplotlib inline
from matplotlib import pyplot as plt
import torch
import torch.nn as nn
from nest import modules
import numpy as np
import os
import PIL.Image
import json
import scipy.misc
import torch.nn.functional as F
import PIL.Image
from collections import OrderedDict
import warnings
warnings.filterwarnings("ignore")
class_names = modules.pascal_voc_object_categories()
image_size = 448
# image pre-processor
transformer = modules.image_transform(
    image_size = [image_size, image_size],
    augmentation = dict(),
    mean = [0.485, 0.456, 0.406],
    std = [0.229, 0.224, 0.225])
backbone = modules.fc_resnet50(num_classes=20, pretrained=False)
model = modules.peak_response_mapping(backbone)
model = nn.DataParallel(model)
state = torch.load('11.pt')
# model.load_state_dict(state['model'])
# model = model.module.cuda()
# a = state['model']
# b = np.array(a)
# print(state.items())
n_state = state['model']
new_state_dict = OrderedDict()
for k, v in n_state.items():
    temp_list = list(k)
    temp_list.insert(0,'module.')
    name = ''.join(temp_list)
    new_state_dict[name] = v
# load params
# print(new_state_dict)
model.load_state_dict(new_state_dict)
model = model.module.cpu()
idx = 4
raw_img = PIL.Image.open('F://python//PRM-pytorch//demo//data//sample%d.jpg' % idx).convert('RGB')
input_var = transformer(raw_img).unsqueeze(0).cpu().requires_grad_()
with open('F://python//PRM-pytorch//demo//data//sample%d.json' % idx, 'r') as f:
    proposals = list(map(modules.rle_decode, json.load(f)))
# plot raw image
# plt.figure(figsize=(5,5))
# plt.imshow(raw_img)

model = model.eval()
print('Object categories in the image:')
confidence = model(input_var)
for idx in range(len(class_names)):
    if confidence.data[0, idx] > 0:
        print('    [class_idx: %d] %s (%.2f)' % (idx, class_names[idx], confidence[0, idx]))
        
        
        
model = model.inference()
visual_cues = model(input_var)
if visual_cues is None:
    print('No class peak response detected')
else:
    confidence, class_response_maps, class_peak_responses, peak_response_maps = visual_cues
    _, class_idx = torch.max(confidence, dim=1)
    class_idx = class_idx.item()
    num_plots = 2 + len(peak_response_maps)
    f, axarr = plt.subplots(1, num_plots, figsize=(num_plots * 4, 4))
    axarr[0].imshow(scipy.misc.imresize(raw_img, (image_size, image_size), interp='bicubic'))
    axarr[0].set_title('Image')
    axarr[0].axis('off')
    axarr[1].imshow(class_response_maps[0, class_idx].cpu(), interpolation='bicubic')
    axarr[1].set_title('Class Response Map ("%s")' % class_names[class_idx])
    axarr[1].axis('off')
    for idx, (prm, peak) in enumerate(sorted(zip(peak_response_maps, class_peak_responses), key=lambda v: v[-1][-1])):
        axarr[idx + 2].imshow(prm.cpu(), cmap=plt.cm.jet)
        axarr[idx + 2].set_title('Peak Response Map ("%s")' % (class_names[peak[1].item()]))
        axarr[idx + 2].axis('off')        
# predict instance masks via proposal retrieval
instance_list = model(input_var, retrieval_cfg=dict(proposals=proposals, param=(0.95, 1e-5, 0.8)))

# visualization
if instance_list is None:
    print('No object detected')
else:
    # peak response maps are merged if they select similar proposals
    vis = modules.prm_visualize(instance_list, class_names=class_names)
    f, axarr = plt.subplots(1, 3, figsize=(12, 5))
    axarr[0].imshow(scipy.misc.imresize(raw_img, (image_size, image_size), interp='bicubic'))
    axarr[0].set_title('Image')
    axarr[0].axis('off')
    axarr[1].imshow(vis[0])
    axarr[1].set_title('Prediction')
    axarr[1].axis('off')
    axarr[2].imshow(vis[1])
    axarr[2].set_title('Peak Response Maps')
    axarr[2].axis('off')
    plt.show()

结果：

其他图片的测试：

其实我在这里就有了问题，就是作者在进行画mask的时候用到了提前计算好的proposals，保存成了.json文件，

.json文件我遇到过，就是用labelme进行标注的时候生成的标签，但是我比较这两个文件不一样。

标签文件是这样的：

{
  "flags": {},
  "shapes": [
    {
      "label": "car",
      "line_color": null,
      "fill_color": null,
      "points": [
        [
          64,
          77
        ],
        [
          50,
          91
        ],
        [
          41,
          102
        ],
        [
          37,
          115
        ],
        [
          36,
          130
        ],
        [
          36,
          138
        ],
        [
          37,
          153
        ],
        [
          40,
          163
        ],
        [
          47,
          167
        ],
        [
          55,
          167
        ],
        [
          60,
          165
        ],
        [
          63,
          157
        ],
        [
          64,
          154
        ],
        [
          110,
          160
        ],
        [
          113,
          167
        ],
        [
          120,
          174
        ],
        [
          127,
          178
        ],
        [
          146,
          178
        ],
        [
          155,
          174
        ],
        [
          159,
          167
        ],
        [
          160,
          165
        ],
        [
          218,
          164
        ],
        [
          220,
          170
        ],
        [
          232,
          175
        ],
        [
          247,
          174
        ],
        [
          255,
          169
        ],
        [
          258,
          163
        ],
        [
          258,
          161
        ],
        [
          267,
          160
        ],
        [
          268,
          155
        ],
        [
          267,
          154
        ],
        [
          269,
          141
        ],
        [
          268,
          131
        ],
        [
          264,
          121
        ],
        [
          260,
          113
        ],
        [
          252,
          109
        ],
        [
          238,
          103
        ],
        [
          224,
          99
        ],
        [
          217,
          98
        ],
        [
          219,
          96
        ],
        [
          213,
          93
        ],
        [
          208,
          91
        ],
        [
          194,
          80
        ],
        [
          185,
          74
        ],
        [
          175,
          71
        ],
        [
          162,
          69
        ],
        [
          140,
          68
        ],
        [
          122,
          67
        ],
        [
          106,
          67
        ],
        [
          93,
          67
        ],
        [
          80,
          70
        ]
      ]
    }
  ],
  "lineColor": [
    0,
    255,
    0,
    128
  ],
  "fillColor": [
    255,
    0,
    0,
    128
  ],
  "imagePath": "..\\..\\..\\get_img\\China_Vehicle_Raw\\0001_6.jpg",
  "imageData": 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"
}

而proposal文件是：

[{"data": "sYACAAIAAAClggIAAgAAAJmEAgACAAAAioYCAAUAAAB+iAIABQAAAHGKAgAGAAAAY4wCAAgAAABXjgIACAAAAEGQAgASAAAANZICABIAAAAplAIAEgAAAB2WAgAKAAAA", "shape": [375, 500]}, {"data": "VA8CAAUAAABIEQIABQAAADwTAgAFAAAAIRUCABQAAAAVFwIAFAAAAAkZAgAUAAAA/RoCABQAAADxHAIAFAAAAOUeAgAUAAAA2SACABQAAADNIgIAFAAAAMEkAgAUAAAAtSYCABQAAACpKAIAFAAAAJ0qAgAUAAAAkSwCABQAAACFLgIAFAAAAHowAgATAAAAcTICABAAAABnNAIADgAAAA==", "shape": [375, 500]}, {"data": "NRsBABEAAAApHQEAEQAAAB0fAQARAAAAESEBABEAAAAFIwEAEQAAAPkkAQARAAAA7SYBABEAAADpKAEACQAAAOEqAQAFAAAA1SwBAAQAAADJLgEABAAAAL0wAQAEAAAAsTIBAAQAAAClNAEABAAAAJk2AQACAAAA", "shape": [375, 500]}, {"data": 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"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", 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标签文件通过“imageData”可以将图像复原：

import argparse
import json
import matplotlib.pyplot as plt
from labelme import utils

data = json.load(open('F://python//PRM-pytorch//demo//0001_6.json')) # 加载json文件
img = utils.img_b64_to_arr(data['imageData']) # 解析原图片数据
print(img.shape)
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape, data['shapes']) # 解析'shapes'中的字段信息，解析出每个对象的mask与对应的label   lbl存储 mask，lbl_names 存储对应的label
    # lal 像素取值 0、1、2 其中0对应背景，1对应第一个对象，2对应第二个对象
    # 使用该方法取出每个对象的mask mask=[] mask.append((lbl==1).astype(np.uint8)) # 解析出像素值为1的对象，对应第一个对象 mask 为0、1组成的（0为背景，1为对象）
    # lbl_names  ['background','cat_1','cat_2']
captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
lbl_viz = utils.draw_label(lbl, img, captions)
plt.subplot(121)
plt.imshow(img)
plt.subplot(122)
plt.imshow(lbl_viz)
plt.show()

所以这里还需研究一下！

权重文件链接：嘻嘻这个链接的loss是最大的，将就用吧~

Weakly Supervised Instance Segmentation using Class Peak Response论文复现以及遇到的问题

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