65094fc108c9db13fde4cbd5ab99491413842007,keras_retinanet/preprocessing/csv_generator.py,CSVGenerator,load_annotations,#CSVGenerator#Any#,199

Before Change

        
        path   = self.image_names[image_index]
        annots = self.image_data[path]
        boxes  = np.zeros((len(annots), 5))

        for idx, annot in enumerate(annots):
            class_name = annot["class"]
            boxes[idx, 0] = float(annot["x1"])
            boxes[idx, 1] = float(annot["y1"])
            boxes[idx, 2] = float(annot["x2"])
            boxes[idx, 3] = float(annot["y2"])
            boxes[idx, 4] = self.name_to_label(class_name)

        return boxes

After Change

        annotations = {"labels": np.empty((0,)), "bboxes": np.empty((0, 4))}

        for idx, annot in enumerate(self.image_data[path]):
            annotations["labels"] = np.concatenate((annotations["labels"], [self.name_to_label(annot["class"])]))
            annotations["bboxes"] = np.concatenate((annotations["bboxes"], [[
                float(annot["x1"]),
                float(annot["y1"]),
                float(annot["x2"]),
                float(annot["y2"]),
            ]]))

        return annotations

Instances