酸洗cv2.KeyPoint导致酸洗错误 [英] Pickling cv2.KeyPoint causes PicklingError

问题描述

我想搜索给定目录中所有图像中的冲浪，并保存它们的关键点和描述符以供将来使用.我决定使用泡菜，如下所示:

I want to search surfs in all images in a given directory and save their keypoints and descriptors for future use. I decided to use pickle as shown below:

#!/usr/bin/env python
import os
import pickle
import cv2

class Frame:
  def __init__(self, filename):
    surf = cv2.SURF(500, 4, 2, True)
    self.filename = filename
    self.keypoints, self.descriptors = surf.detect(cv2.imread(filename, cv2.CV_LOAD_IMAGE_GRAYSCALE), None, False)

if __name__ == '__main__':

  Fdb = open('db.dat', 'wb')
  base_path = "img/"
  frame_base = []

  for filename in os.listdir(base_path):
    frame_base.append(Frame(base_path+filename))
    print filename

  pickle.dump(frame_base,Fdb,-1)

  Fdb.close()

当我尝试执行时，出现以下错误:

When I try to execute, I get a following error:

File "src/pickle_test.py", line 23, in <module>
    pickle.dump(frame_base,Fdb,-1)
...
pickle.PicklingError: Can't pickle <type 'cv2.KeyPoint'>: it's not the same object as cv2.KeyPoint

有人知道吗，这是什么意思，以及如何解决?我正在使用Python 2.6和Opencv 2.3.1

Does anybody know, what does it mean and how to fix it? I am using Python 2.6 and Opencv 2.3.1

非常感谢

推荐答案

问题是您无法将cv2.KeyPoint转储到pickle文件中.我遇到了同样的问题，并设法通过在自己将关键点序列化和反序列化之前，先将其序列化和反序列化，然后再将其与Pickle一起转储，来解决.

The problem is that you cannot dump cv2.KeyPoint to a pickle file. I had the same issue, and managed to work around it by essentially serializing and deserializing the keypoints myself before dumping them with Pickle.

因此用元组表示每个关键点及其描述符:

So represent every keypoint and its descriptor with a tuple:

temp = (point.pt, point.size, point.angle, point.response, point.octave, 
        point.class_id, desc)       

将所有这些点附加到一些列表中，然后与Pickle一起转储.

Append all these points to some list that you then dump with Pickle.

然后，当您想再次检索数据时，用Pickle加载所有数据:

Then when you want to retrieve the data again, load all the data with Pickle:

temp_feature = cv2.KeyPoint(x=point[0][0],y=point[0][1],_size=point[1], _angle=point[2], 
                            _response=point[3], _octave=point[4], _class_id=point[5]) 
temp_descriptor = point[6]

使用上面的代码从此数据创建一个cv2.KeyPoint，然后您可以使用这些点来构建功能列表.

Create a cv2.KeyPoint from this data using the above code, and you can then use these points to construct a list of features.

我怀疑有一个更整洁的方法可以执行此操作，但是以上方法对我来说很好(并且很快).您可能需要稍微处理一下数据格式，因为我的功能存储在特定于格式的列表中.我试图以自己的想法为基础介绍以上内容.希望对您有所帮助.

I suspect there is a neater way to do this, but the above works fine (and fast) for me. You might have to play around with your data format a bit, as my features are stored in format-specific lists. I tried to present the above using my idea at its generic base. I hope that this may help you.

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