def compute_recognition_data(self, dim=48, resample=True):
# Assign labels to actual template data structure.
for i, temp in enumerate(self.templates):
temp.name = self.labels[i]
self.join_graph = groups_to_join_graph(self.groups)
self.image_templates = group_image_templates(self.templates,
self.groups, dim=dim,
resample=resample)
self.raw_features = compute_features_equation(self.templates)
(self.group_features, self.group_labels) = features_to_classifier_input(
self.raw_features, self.join_graph)
def group_classify(page, clf):
features = page.group_features
y = clf.predict(features)
real = page.group_labels
accuracy = sum([1.0 if r == p else 0.0
for r,p in zip(real, y)])/len(y)
groups = clf_results_to_join_graph(page.raw_features,
y,
page.num_temps)
return (accuracy, group_image_templates(page.templates,
groups))
