質問編集履歴
3
UbuntuCleanerでは解決せず
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@@ -69,4 +69,4 @@
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キャッシュから読み込まれているのかと思い、仮想環境のすべてのpycファイルを削除しましたが、やはり上書き保存前の情報のままでした。
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###補足情報(言語/FW/ツール等のバージョンなど)
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UbuntuCleanerでシステムワイドにcacheを消しましたが古い内容を読み込むままでした。
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2
作成コードを追加しました。
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@@ -55,51 +55,12 @@
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def _to_one_hot(self,name):
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one_hot_vector = [0] * self.num_classes
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if name == 'nerve':
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one_hot_vector[0] = 1
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one_hot_vector[0] = 1
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#elif name == 'bicycle':
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# one_hot_vector[1] = 1
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#elif name == 'bird':
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# one_hot_vector[2] = 1
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#elif name == 'boat':
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# one_hot_vector[3] = 1
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#elif name == 'bottle':
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# one_hot_vector[4] = 1
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#elif name == 'bus':
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# one_hot_vector[5] = 1
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#elif name == 'car':
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# one_hot_vector[6] = 1
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#elif name == 'cat':
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# one_hot_vector[7] = 1
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#elif name == 'chair':
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# one_hot_vector[8] = 1
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#elif name == 'cow':
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# one_hot_vector[9] = 1
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#elif name == 'diningtable':
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# one_hot_vector[10] = 1
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#elif name == 'dog':
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# one_hot_vector[11] = 1
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#elif name == 'horse':
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# one_hot_vector[12] = 1
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#elif name == 'motorbike':
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# one_hot_vector[13] = 1
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#elif name == 'person':
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# one_hot_vector[14] = 1
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#elif name == 'pottedplant':
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# one_hot_vector[15] = 1
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#elif name == 'sheep':
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# one_hot_vector[16] = 1
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#elif name == 'sofa':
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# one_hot_vector[17] = 1
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#elif name == 'train':
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# one_hot_vector[18] = 1
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#elif name == 'tvmonitor':
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# one_hot_vector[19] = 1
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else:
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print('unknown label: %s' %name)
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return one_hot_vector
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## example on how to use it
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import pickle
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data = XML_preprocessor('/home/owner/data/VOCdevkit/VOC2019/Annotations/').data
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pickle.dump(data,open('/home/owner/data/VOCdevkit/VOC2019/VOC2019.pkl','wb'))
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1
修正コード全体を貼り付けます。
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@@ -10,8 +10,100 @@
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ファイル名、物体の位置とクラス名が記載されているxmlファイルに間違いがあったためgeditで訂正・上書き保存しました。pklファイルを確認すると上書き保存する前の間違った情報が反映されていました。
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###該当のソースコード
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Python3.5, Ubuntu14.04, Anaconda3による仮想環境
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Python3.5, Ubuntu14.04, Anaconda3による仮想環境。
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１クラス判別のため、それ以外のクラスをコメントアウトし、一番下の3行から＃を外しました。
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import numpy as np
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import os
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from xml.etree import ElementTree
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class XML_preprocessor(object):
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def __init__(self, data_path):
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self.path_prefix = data_path
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self.num_classes = 1
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self.data = dict()
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self._preprocess_XML()
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def _preprocess_XML(self):
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filenames = os.listdir(self.path_prefix)
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for filename in filenames:
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tree = ElementTree.parse(self.path_prefix + filename)
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root = tree.getroot()
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bounding_boxes = []
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one_hot_classes = []
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size_tree = root.find('size')
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width = float(size_tree.find('width').text)
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height = float(size_tree.find('height').text)
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for object_tree in root.findall('object'):
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for bounding_box in object_tree.iter('bndbox'):
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xmin = float(bounding_box.find('xmin').text)/width
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ymin = float(bounding_box.find('ymin').text)/height
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xmax = float(bounding_box.find('xmax').text)/width
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ymax = float(bounding_box.find('ymax').text)/height
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bounding_box = [xmin,ymin,xmax,ymax]
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bounding_boxes.append(bounding_box)
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class_name = object_tree.find('name').text
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one_hot_class = self._to_one_hot(class_name)
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one_hot_classes.append(one_hot_class)
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image_name = root.find('filename').text
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bounding_boxes = np.asarray(bounding_boxes)
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one_hot_classes = np.asarray(one_hot_classes)
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image_data = np.hstack((bounding_boxes, one_hot_classes))
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self.data[image_name] = image_data
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def _to_one_hot(self,name):
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one_hot_vector = [0] * self.num_classes
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if name == 'nerve':
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one_hot_vector[0] = 1
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#elif name == 'bicycle':
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# one_hot_vector[1] = 1
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#elif name == 'bird':
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# one_hot_vector[2] = 1
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#elif name == 'boat':
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# one_hot_vector[3] = 1
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#elif name == 'bottle':
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# one_hot_vector[4] = 1
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#elif name == 'bus':
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# one_hot_vector[5] = 1
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#elif name == 'car':
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# one_hot_vector[6] = 1
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#elif name == 'cat':
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# one_hot_vector[7] = 1
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#elif name == 'chair':
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# one_hot_vector[8] = 1
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#elif name == 'cow':
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# one_hot_vector[9] = 1
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#elif name == 'diningtable':
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# one_hot_vector[10] = 1
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#elif name == 'dog':
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# one_hot_vector[11] = 1
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#elif name == 'horse':
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# one_hot_vector[12] = 1
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#elif name == 'motorbike':
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# one_hot_vector[13] = 1
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#elif name == 'person':
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# one_hot_vector[14] = 1
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#elif name == 'pottedplant':
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# one_hot_vector[15] = 1
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#elif name == 'sheep':
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# one_hot_vector[16] = 1
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#elif name == 'sofa':
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# one_hot_vector[17] = 1
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#elif name == 'train':
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# one_hot_vector[18] = 1
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#elif name == 'tvmonitor':
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# one_hot_vector[19] = 1
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else:
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print('unknown label: %s' %name)
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return one_hot_vector
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## example on how to use it
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import pickle
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data = XML_preprocessor('/home/owner/data/VOCdevkit/VOC2019/Annotations/').data
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pickle.dump(data,open('/home/owner/data/VOCdevkit/VOC2019/VOC2019.pkl','wb'))
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15
107
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###試したこと
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16
108
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キャッシュから読み込まれているのかと思い、仮想環境のすべてのpycファイルを削除しましたが、やはり上書き保存前の情報のままでした。
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17
109
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