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HoG and Hellinger-metric preprocess for digit recognition

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line breaks in fitline.py description
This commit is contained in:
Alexander Mordvintsev
2012-07-02 13:49:36 +00:00
parent efe139667b
commit 1543b46383
4 changed files with 69 additions and 24 deletions
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10
samples/python2/digits_adjust.py
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@@ -76,7 +76,7 @@ class App(object):
shuffle = np.random.permutation(len(digits))
digits, labels = digits[shuffle], labels[shuffle]
digits2 = map(deskew, digits)
samples = np.float32(digits2).reshape(-1, SZ*SZ) / 255.0
samples = preprocess_hog(digits2)
return samples, labels
def get_dataset(self):
@@ -95,8 +95,8 @@ class App(object):
return ires
def adjust_SVM(self):
Cs = np.logspace(0, 5, 10, base=2)
gammas = np.logspace(-7, -2, 10, base=2)
Cs = np.logspace(0, 10, 15, base=2)
gammas = np.logspace(-7, 4, 15, base=2)
scores = np.zeros((len(Cs), len(gammas)))
scores[:] = np.nan
@@ -114,6 +114,9 @@ class App(object):
print '%d / %d (best error: %.2f %%, last: %.2f %%)' % (count+1, scores.size, np.nanmin(scores)*100, score*100)
print scores
print 'writing score table to "svm_scores.npz"'
np.savez('svm_scores.npz', scores=scores, Cs=Cs, gammas=gammas)
i, j = np.unravel_index(scores.argmin(), scores.shape)
best_params = dict(C = Cs[i], gamma=gammas[j])
print 'best params:', best_params
@@ -142,7 +145,6 @@ if __name__ == '__main__':
print __doc__
args, _ = getopt.getopt(sys.argv[1:], '', ['model=', 'cloud', 'env='])
args = dict(args)
args.setdefault('--model', 'svm')