Esempio n. 1
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 def row_to_features(self, img, row):
     labels = list()
     features = list()
     for roof in row.roofs:
         labels.append(type_dict[roof['type']])
         roof_patch = utils.crop_from_center(img, roof['x'], roof['y'])
         features.append(utils.color_feat(roof_patch))
     return labels, features
Esempio n. 2
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    def image_to_features(self, img):
        c_feat = utils.color_feat(img)

        #Iron
        thres_iron = np.linspace(0.3, 1.0, 14, endpoint=False)
        iron_feat = np.array([self.get_threshold_features(img, self.iron_temp, thres)
                              for thres in thres_iron])

        #Grass
        thres_grass = np.linspace(0.8, 1.0, 14, endpoint=False)
        grass_feat = np.array([self.get_threshold_features(img, self.grass_temp, thres)
                              for thres in thres_grass])

        #Total features
        features = np.concatenate([iron_feat, grass_feat, c_feat]).tolist()
        return features
Esempio n. 3
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    def image_to_features(self, img):
        if self.roof_model is None:
            return np.zeros((80,))
        c_feat = utils.color_feat(img)

        #Iron
        thres_iron = np.linspace(0.3, 1.0, 14, endpoint=False)
        iron_feat = np.array([self.get_threshold_features(img, self.iron_temp, thres, self.roof_model)
                              for thres in thres_iron])
        iron_feat = np.concatenate(np.transpose(iron_feat))

        #Grass
        thres_grass = np.linspace(0.8, 1.0, 14, endpoint=False)
        grass_feat = np.array([self.get_threshold_features(img, self.grass_temp, thres, self.roof_model)
                              for thres in thres_grass])
        grass_feat = np.concatenate(np.transpose(grass_feat))

        #Total features
        features = np.concatenate([iron_feat, grass_feat, c_feat]).tolist()
        return features
Esempio n. 4
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 def image_to_features(self, img):
     features = utils.color_feat(img)
     return self.clf.predict_proba(features)