NavOCR

A lightweight, navigation-oriented OCR framework.

It is designed for robotic navigation scenarios, where only navigation-relevant text should be detected, such as:

• Signboards
• Room numbers
• (coming soon) Directional signs

while irrelevant text, such as advertisements or price tags, is ignored.
If you'd like to see an example of SLAM using NavOCR, check it out our TextMap examples.

Key features

• Focuses on navigation-relevant text to reduce unnecessary information and improve OCR speed
• Supports both standalone and ROS 2 integration
• Optimized for CPU-first robotic platforms, achieving ~6 FPS on CPUs
• Supports PaddlePaddle for GPU environments

Overview

• navocr_standalone.py: Run detection + OCR on a single image or a directory
• navocr/ros_node.py: ROS 2 node entry point
• configs/navocr_onnx.params.yaml: ONNX detector + ONNX OCR config (default)
• configs/navocr_openvino.params.yaml: OpenVINO detector + OpenVINO OCR config
• configs/navocr_paddle.params.yaml: PaddleDetection detector + Paddle OCR config
• configs/navocr_pytorch.params.yaml: PyTorch detector + Paddle OCR config

Backend Composition

Model format	Runtime / engine	Hardware	Text detection	Text recognition	FPS
ONNX	ONNX Runtime	CPU / GPU	RT-DETRv4 (Fine-tuned)	PP-OCRv5	4.51
OpenVINO IR	OpenVINO Runtime	Intel CPU	RT-DETRv4 (Fine-tuned)	PP-OCRv5	6.07
Paddle model	Paddle Inference	CPU / GPU	PP-YOLOE (Fine-tuned)	PP-OCRv5	1.79
PyTorch	PyTorch	CPU / GPU	RT-DETRv4 (Fine-tuned)	PP-OCRv5	2.05

*All FPS was measured on 11th Gen Intel(R) Core(TM) i5-1135G7.

Installation

Download Model

ONNX, OpenVINO, PaddlePaddle models are included in this repository.

git clone git@github.com:kc-ml2/NavOCR.git

Python Environment Setup (recommended)

Using a venv keeps NavOCR's Python dependencies isolated from the system Python and avoids conflicts with colcon build.

python3 -m venv ~/.venvs/navocr
source ~/.venvs/navocr/bin/activate

pip install --upgrade pip
pip install colcon-common-extensions

For ONNX runtime (default)

pip install onnxruntime pyyaml opencv-python numpy

If you want to run ONNX Runtime on CUDA, install onnxruntime-gpu instead of onnxruntime.

For OpenVINO runtime (Optional)

pip install openvino pyyaml opencv-python numpy

For PyTorch runtime (Optional)

pip install pyyaml opencv-python numpy
pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu

# Download weight
pip install gdown==5.2.0
gdown https://drive.google.com/uc?id=1D0zRUmyPvxgXq2rytrzVqg3-5_-5gkDn
mv rtv4_hgnetv2_s.pth model/pytorch/rtv4_hgnetv2_s.pth

For Paddle runtime (Optional)

This is only required for paddlepaddle backend.

Tested with paddlepaddle==3.0.0 and paddleocr==3.4.0.

Install PaddlePaddle following the official installation guide for your OS / Python / CUDA version:

• https://www.paddlepaddle.org.cn/en/install/quick

Then install PaddleDetection and PaddleOCR:

pip install pyyaml opencv-python numpy

# PaddleDetection
git clone https://github.com/PaddlePaddle/PaddleDetection.git

cd PaddleDetection
pip install -r requirements.txt
python setup.py install

# PaddleOCR
pip install paddleocr

Standalone Inference

Download Testset

# Setup python env
pip install gdown==5.2.0

# Download sample testset
mkdir data && cd data
gdown https://drive.google.com/uc?id=1GcgddRm4GsjPKUOVdmWFzeF5gElCZfx2
unzip example_sequence.zip 
cd .. && mkdir results

Run with ONNX runtime (default)

python navocr_standalone.py \
  --params-file configs/navocr_onnx.params.yaml \
  --infer_dir data/example_sequence/images

Run with OpenVINO runtime

# If you encounter oneDNN compatibility issues on CPU, set these before running:
export FLAGS_enable_pir_api=0
export FLAGS_enable_pir_in_executor=0

python navocr_standalone.py \
  --params-file configs/navocr_openvino.params.yaml \
  --infer_dir data/example_sequence/images

Run with PyTorch runtime

python navocr_standalone.py \
  --params-file configs/navocr_pytorch.params.yaml \
  --infer_dir data/example_sequence/images

Run with Paddle runtime

python navocr_standalone.py \
  --params-file configs/navocr_paddle.params.yaml \
  --infer_dir data/example_sequence/images

Single image

python navocr_standalone.py \
  --params-file configs/navocr_onnx.params.yaml \
  --input data/example_sequence/images/000000.jpg

ROS 2 Node

Build ROS 2 package

ROS dependencies are declared in package.xml. Install them from the workspace root with:

cd ~/ros2_ws  # your ros2 workspace
rosdep install --from-paths src --ignore-src -r -y

colcon build --symlink-install --packages-select navocr
python -m colcon build --symlink-install --packages-select navocr  # if you're using venv

source install/setup.bash

Run ros2 node

ros2 run navocr navocr_with_ocr_node

The default ROS 2 params file is configs/navocr_onnx.params.yaml.

If you want to select a different params file at runtime:

ros2 run navocr navocr_with_ocr_node --ros-args \
  -p params_file:=/absolute/path/to/configs/navocr_pytorch.params.yaml

ros2 run navocr navocr_with_ocr_node --ros-args \
  -p params_file:=/absolute/path/to/configs/navocr_openvino.params.yaml

ros2 run navocr navocr_with_ocr_node --ros-args \
  -p params_file:=/absolute/path/to/configs/navocr_paddle.params.yaml

Published topics:

• detections_topic default: /navocr/detections
• annotated_image_topic default: /navocr/annotated_image

Acknowledgements

We gratefully acknowledge the open-source projects that made this work possible: RT-DETRv4, PaddleDetection, PaddleOCR / PP-OCRv5, OpenVINO, and ONNX.

🚧 Planned Updates

We're working on expanding support beyond store signboards detection model. Stay tuned for upcoming features for broader navigation use cases.

• Library migration due to a license issue (ultralytics -> PaddleDetection)
• Alternative inference for higher FPS on CPU (Add OpenVINO support)
• Integration with text recognition (PaddleOCR)
• Integration with SLAM packages via ROS (TextMap)
• Model training scripts (Dataset crawling, model fine-tuning, ...)
• Floor sign detection
• Directional guide text detection

License

This repository is licensed under the Apache License, Version 2.0.

This project includes code and configuration files derived from PaddleDetection (https://github.com/PaddlePaddle/PaddleDetection) and RT-DETRv4 (https://github.com/RT-DETRs/RT-DETRv4), which are also licensed under the Apache License, Version 2.0.