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))