traffic_light_classifier.py

def get_classification(self, img):
    # Bounding Box Detection.
    with self.detection_graph.as_default():
        # Expand dimension since the model expects image to have shape [1, None, None, 3].
        img_expanded = np.expand_dims(img, axis=0)  
        (boxes, scores, classes, num) = self.sess.run(
            [self.d_boxes, self.d_scores, self.d_classes, self.num_d],
            feed_dict={self.image_tensor: img_expanded})
    return boxes, scores, classes, num

Thank you very much for your Medium post, which is where I found this Gist. Could you please clarify which license applies to your Gist(s)? MIT?

Thank you!