def _convert_render_batch_response()

in orrb/remote_renderer.py [0:0]

• 35 lines of code
• 13 McCabe index (conditional complexity)

def _convert_render_batch_response(response, config, batch_size):
    h, w = config.image_height, config.image_width
    batch_dataset = dict()
    for stream in response.streams:
        stream_rgb_dataset = []
        stream_depth_dataset = []
        stream_normals_dataset = []
        stream_segmentation_dataset = []
        for entry in stream.entries:
            if entry.image_data:
                image = read_rgba_image(entry.image_data, w, h)
                stream_rgb_dataset.append(image)
            if entry.depth_data:
                image = read_depth_image(entry.depth_data, w, h)
                stream_depth_dataset.append(image)
            if entry.normals_data:
                image = read_normals_image(entry.normals_data, w, h)
                stream_normals_dataset.append(image)
            if entry.segmentation_data:
                image = read_segmentation_image(entry.segmentation_data, w, h)
                stream_segmentation_dataset.append(image)

        batch_dataset[stream.name] = np.array(stream_rgb_dataset)
        if stream_depth_dataset:
            batch_dataset['%s_depth' % stream.name] = np.array(stream_depth_dataset)
        if stream_normals_dataset:
            batch_dataset['%s_normals' % stream.name] = np.array(stream_normals_dataset)
        if stream_segmentation_dataset:
            batch_dataset['%s_segmentation' % stream.name] = np.array(stream_segmentation_dataset)

    for float_stream in response.auxiliary_float_streams:
        _add_auxiliary_stream(batch_dataset, batch_size, float_stream, float)

    for int_stream in response.auxiliary_int_streams:
        _add_auxiliary_stream(batch_dataset, batch_size, int_stream, int)

    for bool_stream in response.auxiliary_bool_streams:
        _add_auxiliary_stream(batch_dataset, batch_size, bool_stream, bool)

    return batch_dataset