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我正在練習使用特徵面和支持向量機的人臉識別示例在官方scikit-learn網站上。ValueError:min_faces_per_person = 70太嚴格了
但是當我運行此:
from __future__ import print_function
from time import time
import logging
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.model_selection import GridSearchCV
from sklearn.datasets import fetch_lfw_people
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.decomposition import PCA
from sklearn.svm import SVC
print(__doc__)
# Display progress logs on stdout
logging.basicConfig(level=logging.INFO, format='%(asctime)s %(message)s')
# #############################################################################
# Download the data, if not already on disk and load it as numpy arrays
lfw_people = fetch_lfw_people(min_faces_per_person=70, resize=0.4)
但我得到告訴我一個錯誤:
Traceback (most recent call last):
File "D:\神經網絡與深度學習\麥子學院-深度學習\(Part One)深度學習基礎\代碼與素材
\代碼與素材(1)\03SVM\plot_face_recognition.py", line 54, in <module>
lfw_people = fetch_lfw_people(min_faces_per_person=70, resize=0.4)
File "D:\Program Files\Python36\lib\site-packages\sklearn\datasets\lfw.py", line 335, in fetch_lfw_people
min_faces_per_person=min_faces_per_person, color=color, slice_=slice_)
File "D:\Program Files\Python36\lib\site-packages\sklearn\externals\joblib\memory.py", line 562, in __call__
return self._cached_call(args, kwargs)[0]
File "D:\Program Files\Python36\lib\site-packages\sklearn\externals\joblib\memory.py", line 510, in _cached_call
out, metadata = self.call(*args, **kwargs)
File "D:\Program Files\Python36\lib\site-packages\sklearn\externals\joblib\memory.py", line 744, in call
output = self.func(*args, **kwargs)
File "D:\Program Files\Python36\lib\site-packages\sklearn\datasets\lfw.py", line 231, in _fetch_lfw_people
min_faces_per_person)
ValueError: min_faces_per_person=70 is too restrictive
我不明白爲什麼我的Python版本是什麼? 3.6.2,scikit-learn版本是v0.19.0
閱讀[代碼](https://github.com/scikit-learn/scikit-learn/blob/c1eee276fa501965e7b4e23e6349031092e33131/sklearn/datasets/lfw.py#L208)它似乎有一些麻煩路徑的東西效果在empy文件集中。 – sascha
我在Ubuntu 14和Python 2並沒有得到任何錯誤。也許[這個問題](https://github.com/scikit-learn/scikit-learn/issues/6484)是相關的。你可以在那裏發佈一個新的問題。 –