def get_video()

in training/dataset/vos_raw_dataset.py [0:0]

• 32 lines of code
• 9 McCabe index (conditional complexity)

    def get_video(self, video_idx):
        """
        Given a VOSVideo object, return the mask tensors.
        """
        video_name = self.video_names[video_idx]
        video_json_path = os.path.join(self.gt_folder, video_name + "_manual.json")
        segment_loader = JSONSegmentLoader(
            video_json_path=video_json_path,
            ann_every=self.ann_every,
            frames_fps=self.frames_fps,
        )

        frame_ids = [
            int(os.path.splitext(frame_name)[0])
            for frame_name in sorted(
                os.listdir(os.path.join(self.img_folder, video_name))
            )
        ]

        frames = [
            VOSFrame(
                frame_id,
                image_path=os.path.join(
                    self.img_folder, f"{video_name}/%05d.jpg" % (frame_id)
                ),
            )
            for frame_id in frame_ids[:: self.sample_rate]
        ]

        if self.rm_unannotated:
            # Eliminate the frames that have not been annotated
            valid_frame_ids = [
                i * segment_loader.ann_every
                for i, annot in enumerate(segment_loader.frame_annots)
                if annot is not None and None not in annot
            ]
            frames = [f for f in frames if f.frame_idx in valid_frame_ids]

        video = VOSVideo(video_name, video_idx, frames)
        return video, segment_loader