NotImplementedError: UFF for YOLO_v3 is not supported when I generate PeopleSemSegNet's TRT engine file in tao_deploy.ipynb

Hello. When I generated TRT engine file for the PeopleSemSegNet’s etlt file on this tao_deloy.ipynb notebook, I got the error message NotImplementedError: UFF for YOLO_v3 is not supported.

How could I do to solve this problem ? Thank you for your help is advance.

My TensorRT version is and python version is 3.8.10

The picture below is error message when generating PeopleSemSegNet tensorrt engine

The content below is the process of generating PeopleSemSegNet TensorRT

#FIXME 8 - data_type: choose fp32 or fp16
os.environ["data_type"] = "fp32"

#FIXME 9 - trt_out_folder: choose output folder for TensorRT engine file writing
trt_out_folder = "/root/nvidia-tao/tao_deploy/trt_out_folder" + ptm_model_name

!mkdir -p $trt_out_folder

import glob
input_etlt_file_list = glob.glob(os.environ.get("ptm_download_folder")+"/**/*.etlt", recursive=True)
if len(input_etlt_file_list) == 0:
    raise Exception("ETLT file was not downloaded")

os.environ["input_etlt_file"] = input_etlt_file_list[0]

if ptm_model_name in ("LicensePlateRecognition","LicensePlateDetection"):
  # FIXME: country
  # us/ccpd for LicensePlateDetection - us for United States, ch for China
  # us/ch for LicensePlateRecongition - us for United States, ch for China

    country = "us"
    for countrywise_ptm in input_etlt_file_list:
        fname = countrywise_ptm.split("/")[-1]
        if fname.startswith(country):
            os.environ["input_etlt_file"] = countrywise_ptm

action = ""
if ptm_model_name in ("PeopleNet","LicensePlateDetection","DashCamNet","TrafficCamNet","FaceDetect","FaceDetectIR"):
    action = "_trt"

os.environ["KEY"] = "tlt_encode"

if ptm_model_name in ("LicensePlateRecognition","LicensePlateDetection","FaceDetect"):
    os.environ["KEY"] = "nvidia_tlt"

os.environ["trt_experiment_spec"] = f"{os.environ.get('COLAB_NOTEBOOKS_PATH')}/tao_deploy/specs/{ptm_model_name}/{ptm_model_name}{action}.txt"
os.environ["trt_out_file_name"] = f'{trt_out_folder}/{ptm_model_name}.trt.{os.environ["data_type"]}'

if ptm_model_name == "PeopleSemSegNet":
    !unet gen_trt_engine \
                    -m $input_etlt_file \
                    -k $KEY  \
                    -e $trt_experiment_spec \
                    --data_type $data_type \
                    --batch_size 1 \
                    --max_batch_size 3 \
                    --engine_file $trt_out_file_name

The content below is PeopleSemSegNet.txt refernced from this file

model_config {
  num_layers: 18
  model_input_width: 960
  model_input_height: 544
  model_input_channels: 3
  all_projections: true
  arch: "vanilla_unet_dynamic"
  use_batch_norm: true
  training_precision {
    backend_floatx: FLOAT32
dataset_config {
  dataset: "custom"
  augment: False
  input_image_type: "color"
  train_data_sources: {
    data_source: {
      image_path: "/root/nvidia-tao/tao_deploy/specs/PeopleSemSegNet/PeopleSemSegNet_data.txt"
      masks_path: ""

  val_data_sources: {
    data_source: {
      image_path: "/root/nvidia-tao/tao_deploy/specs/PeopleSemSegNet/PeopleSemSegNet_data.txt"
      masks_path: ""
  test_data_sources: {
    data_source: {
      image_path: "/root/nvidia-tao/tao_deploy/specs/PeopleSemSegNet/PeopleSemSegNet_data.txt"


  data_class_config {
    target_classes {
      name: "person"
      mapping_class: "person"
      label_id: 1
    target_classes {
      name: "background"
      mapping_class: "background"
      label_id: 0
    target_classes {
      name: "bag"
      mapping_class: "background"
      label_id: 2
    target_classes {
      name: "face"
      mapping_class: "person"
      label_id: 3

There is no update from you for a period, assuming this is not an issue anymore. Hence we are closing this topic. If need further support, please open a new one. Thanks

Above notebook is for google Colab. Instead, please download notebook from TAO Toolkit Quick Start Guide - NVIDIA DocsTAO Toolkit Getting Started | NVIDIA NGC

This topic was automatically closed 14 days after the last reply. New replies are no longer allowed.