Advertisement
Not a member of Pastebin yet?
Sign Up,
it unlocks many cool features!
- from sklearn import datasets
- from sklearn.svm import SVC
- from scipy import misc
- import os
- os.system('sudo pip install scikit-learn')
- digits = datasets.load_digits()
- features = digits.data
- labels = digits.target
- clf = SVC(gamma = 0.001)
- clf.fit(features, labels)
- img = misc.imread("8.jpg")
- img = misc.imresize(img, (8,8))
- img = img.astype(digits.images.dtype)
- img = misc.bytescale(img, high=16, low=0)
- x_test = []
- for eachRow in img:
- for eachPixel in eachRow:
- x_test.append(sum(eachPixel)/3.0)
- print(clf.predict([x_test]))
Advertisement
Add Comment
Please, Sign In to add comment
Advertisement