【发布时间】：2015-07-09 02:46:14
【问题描述】：
这几周我一直在从事一个性别识别项目（在 python 中），起初使用的是：Fisherfaces as Feature Extraction method 和 1-NN classifier with Euclidean Distance 但现在我虽然还不够可靠（以我的拙见) 所以我即将使用 SVM，但是当我必须创建和训练模型以在我的图像数据集中使用它时我迷路了，但我在 http://scikit-learn.org 中找不到我需要的命令的解决方案。 我试过这个代码，但它不起作用，不知道为什么 执行时出现此错误：
File "prueba.py", line 46, in main
clf.fit(R, r)
File "/Users/Raul/anaconda/lib/python2.7/site-packages/sklearn/svm/base.py", line 139, in fit
X = check_array(X, accept_sparse='csr', dtype=np.float64, order='C')
File "/Users/Raul/anaconda/lib/python2.7/site-packages/sklearn/utils/validation.py", line 350, in check_array
array.ndim)
ValueError: Found array with dim 3. Expected <= 2
这是我的代码：
import os, sys
import numpy as np
import PIL.Image as Image
import cv2
from sklearn import svm
def read_images(path, id, sz=None):
c = id
X,y = [], []
for dirname, dirnames, filenames in os.walk(path):
for subdirname in dirnames:
subject_path = os.path.join(dirname, subdirname)
for filename in os.listdir(subject_path):
try:
im = Image.open(os.path.join(subject_path, filename))
im = im.convert("L")
# resize to given size (if given)
if (sz is not None):
im = im.resize(sz, Image.ANTIALIAS)
X.append(np.asarray(im, dtype=np.uint8))
y.append(c)
except IOError as e:
print "I/O error({0}): {1}".format(e.errno, e.strerror)
except:
print "Unexpected error:", sys.exc_info()[0]
raise
#c = c+1
return [X,y]
def main():
# check arguments
if len(sys.argv) != 3:
print "USAGE: example.py </path/to/images/males> </path/to/images/females>"
sys.exit()
# read images and put them into Vectors and id's
[X,x] = read_images(sys.argv[1], 1)
[Y, y] = read_images(sys.argv[2], 0)
# R all images and r all id's
[R, r] = [X+Y, x+y]
clf = svm.SVC()
clf.fit(R, r)
if __name__ == '__main__':
main()
对于如何使用 SVM 进行性别识别，我将不胜感激 感谢阅读
【问题讨论】：
标签： python machine-learning svm libsvm