if session.view is not None:
    classification_views = []

    for sample in session.view:
        first_frame = sample.frames.first()

        if first_frame.classifications and first_frame.classifications.classifications:
            skip_full_frame_catalog = False
            for classification in first_frame.classifications.classifications:
                start, stop, step = 0, sample.metadata.total_frame_count, 1

                if classification.label == "video_split":
                    start, stop = classification.start, classification.stop
                elif classification.label == "single_frames":
                    start, stop, step = classification.start, classification.stop, classification.step
                else:
                    continue
                frame_ids_for_classification = [
                    frame.id for frame in sample.frames.values()
                    if start <= frame.frame_number <= stop and (frame.frame_number - start) % step == 0
                ]

                if frame_ids_for_classification:
                    classification_view = session.view.select_frames(frame_ids_for_classification)
                    classification_views.append(classification_view)
                    skip_full_frame_catalog = True

            if skip_full_frame_catalog:
                continue

        start, stop, step = 0, sample.metadata.total_frame_count, 1
        frame_ids_for_default = [
            frame.id for frame in sample.frames.values()
            if start <= frame.frame_number <= stop and (frame.frame_number - start) % step == 0
        ]

        if frame_ids_for_default:
            default_view = session.view.select_frames(frame_ids_for_default)
            classification_views.append(default_view)

    for view in classification_views:
        first_frame = view.first()
        parts = first_frame.filepath.split('/')
        og_data_loc = os.path.join(minio_endpoint, *parts[3:])

        frames_view = view.to_frames(sample_frames=True, sparse=True)
        first_frame = frames_view.first()
        parts = first_frame.filepath.split('/')
        bucket_name = parts[3]
        rest_of_path = '/'.join(parts[4:-1])
        now = datetime.datetime.now()
        date_time_folder = now.strftime("%Y%m%d_%H%M%S")
        folder_path = f"fiftyone_processed_data/{rest_of_path}/{date_time_folder}"

        local_video_directory = os.path.join("/".join(parts[:4]), os.path.dirname(rest_of_path))
        video_file_name = f"stitched_{date_time_folder}.mp4"
        local_video_path = os.path.join(local_video_directory, video_file_name)

        # Determine the video format from the first frame
        extension = os.path.splitext(og_data_loc)[-1].upper()
        data_type = extension[1:]  # Remove the dot from the extension

        # Initialize video writer
        frame = cv2.imread(first_frame.filepath)
        height, width, layers = frame.shape
        codec = cv2.VideoWriter_fourcc(*'mp4v')
        video = cv2.VideoWriter(local_video_path, codec, view.first().metadata.frame_rate, (width, height))

        for frame in frames_view:
            frame_path = frame.filepath
            frame = cv2.imread(frame_path)
            video.write(frame)

        video.release()
        
        s3_upload_path = os.path.join(folder_path, video_file_name)
        try:
            with open(local_video_path, "rb") as f:
                s3_client.upload_fileobj(f, bucket_name, s3_upload_path)
        except Exception as e:
            print(f"Failed to upload stitched video due to {e}")
        
        task_name = video_file_name
        with ApiClient(configuration) as api_client:
            try:
                twr = TaskWriteRequest(task_name, project_id=target_project)
                data, response = api_client.tasks_api.create(twr, org=organization)

                server_files = [f"{bucket_name}/{s3_upload_path}"]
                data_request = DataRequest(image_quality=95, server_files=server_files, use_cache=True, use_zip_chunks=False)
                api_client.tasks_api.create_data(data.id, upload_finish=True, upload_multiple=False, upload_start=True, data_request=data_request)
                print("Uploaded task to CVAT")
            except exceptions.ApiException as e:
                print(f"Exception when calling CVAT API: {e}")

The goal of this code is, given a project A, cataloging project, upload to project B with a downselect of the data. This works as expected. I have realized if the user isn't splitting the data, and going to:  if skip_full_frame_catalog: area, it will essentially be the unmodified file. Which means we can use the original source and do not need to                 s3_client.upload_fileobj(f, bucket_name, s3_upload_path). Do you understand? If so, go ahead an fix that so we prevent data duplication where possible. Give me the entire code back,  no omissions.