def inference(steps=steps_inference): net_name, input_shape, output_shape = build_net(steps=steps, mode="inference") outputs = [out_name + "_predicted" for out_name in output_names] single_block_inference(net_name, input_shape, output_shape, ckpt, outputs, input_file, coordinate=coordinate, output_file=output_file, voxel_size_input=voxel_size, voxel_size_output=voxel_size)
def inference(steps=steps_inference): net_name, input_shape, output_shape = build_net(steps=steps, mode="inference") outputs = [l.labelname for l in labels] single_block_inference(net_name, input_shape, output_shape, ckpt, outputs, input_file, coordinate=coordinate, output_file=output_file, voxel_size_input=voxel_size_input, voxel_size_output=voxel_size)
def inference(ckpt, input_file, input_ds, coordinate, output_file): net_name, input_shape, output_shape = build_net(mode="inference") outputs = [out_name + "_predicted" for out_name in output_names] single_block_inference(net_name, input_shape, output_shape, ckpt, outputs, input_file, input_ds_name=input_ds, coordinate=coordinate, output_file=output_file, voxel_size_input=voxel_size, voxel_size_output=voxel_size, input="raw_input")