BrightSign Python Extension for CV Development (ALPHA RELEASE)

Python 3.8 + OpenCV + PyTorch + NPU acceleration for BrightSign digital signage players

Quick Links: Quick Start | QUICKSTART.md | WORKFLOWS.md | FAQ.md

What Is This?

A complete Python development environment for BrightSign Series 5 players with:

Python 3.8 + standard library
Computer Vision: OpenCV, scikit-image, PIL
Deep Learning: PyTorch, ONNX
NPU Acceleration: RKNN toolkit for 10x faster inference
Scientific Stack: NumPy, pandas, SciPy, matplotlib

Use Cases: Audience analytics, interactive displays, retail analytics, smart signage, edge AI

System Architecture

┌─────────────────────────────────┐         ┌──────────────────────────────────┐
│   Development Host (x86_64)     │         │  BrightSign Player (ARM64)       │
│                                 │         │                                  │
│  ┌──────────────────────────┐  │         │  ┌────────────────────────────┐  │
│  │  1. Setup (5-10 min)     │  │         │  │  BrightSign OS 9.1.79.3+   │  │
│  │  - Download sources      │  │         │  │  (Read-only Linux)         │  │
│  │  - Build Docker image    │  │         │  └────────────────────────────┘  │
│  └──────────────────────────┘  │         │                                  │
│            ↓                    │         │  ┌────────────────────────────┐  │
│  ┌──────────────────────────┐  │         │  │  Extension                 │  │
│  │  2. Build (30-60 min)    │  │         │  │  /var/volatile/bsext/      │  │
│  │  - Cross-compile         │  │         │  │  - Python 3.8 runtime      │  │
│  │  - Python + CV packages  │  │         │  │  - CV/ML libraries         │  │
│  │  - Extract SDK           │  │         │  │  - RKNN NPU toolkit        │  │
│  └──────────────────────────┘  │         │  │  - Auto-start on boot      │  │
│            ↓                    │         │  └────────────────────────────┘  │
│  ┌──────────────────────────┐  │         │                                  │
│  │  3. Package (5 min)      │  │         │  ┌────────────────────────────┐  │
│  │  - Create .zip files     │──┼────────▶│  │  User Scripts (Optional)   │  │
│  │  - Dev + Production      │  │ Deploy │  │  /storage/sd/python-init/  │  │
│  └──────────────────────────┘  │         │  │  - Custom initialization   │  │
│                                 │         │  │  - Auto-run on startup     │  │
└─────────────────────────────────┘         │  └────────────────────────────┘  │
                                            │                                  │
                                            │  ┌────────────────────────────┐  │
                                            │  │  NPU (Neural Processor)    │  │
                                            │  │  RK3588 - 6 TOPS           │  │
                                            │  │  ~10x faster inference     │  │
                                            │  └────────────────────────────┘  │
                                            └──────────────────────────────────┘

Build Time: 60-90 minutes first time, 5-15 minutes incremental Package Size: 420MB development, 370MB production Target: ARM64 BrightSign players with RK3588 NPU

Prerequisites

Critical Requirements

Requirement	Details	Why
x86_64 architecture	Intel/AMD CPU	RKNN toolchain limitation
16GB+ RAM	32GB recommended	Cross-compilation memory needs
50GB+ disk space	SSD preferred	Build artifacts (~20GB) + source (~20GB) + SDK (~10GB)
Docker	Docker Desktop or docker-ce	Isolated build environment
OS 9.1.79.3+	BrightSign firmware	NPU runtime library required

❌ NOT Compatible

Apple Silicon (M1/M2/M3/M4) - use x86_64 cloud VM instead
ARM64 / aarch64 Linux
Raspberry Pi
BrightSign OS < 9.1.79.3

Validate your system:

./check-prerequisites  # Checks architecture, Docker, disk space, etc.

See FAQ.md for Apple Silicon workarounds.

Quick Start

Three Commands to Build

# 1. Validate and setup (5-10 min)
./check-prerequisites && ./setup -y

# 2. Build SDK (30-60 min - safe to background)
./build --extract-sdk

# 3. Package extension (5 min)
./brightsign-x86_64-cobra-toolchain-*.sh -d ./sdk -y && ./package

Output: Two deployment packages

pydev-YYYYMMDD-HHMMSS.zip - Development (volatile, fast iteration)
ext_pydev-YYYYMMDD-HHMMSS.zip - Production (persistent, auto-start)

Detailed walkthrough: See QUICKSTART.md for step-by-step guide with troubleshooting.

Deploy to Player

Quick deploy (development package):

# Transfer via DWS (http://<player-ip>:8080 → SD tab)
# Then install via SSH:

ssh brightsign@<player-ip>
# Exit to Linux shell (type 'exit' twice)

mkdir -p /usr/local/pydev && cd /usr/local/pydev
unzip /storage/sd/pydev-*.zip
source sh/setup_python_env

# Test it works
python3 -c "import cv2, torch, numpy; print('Ready!')"

Production deploy (persistent extension):

# Transfer ext_pydev-*.zip via DWS, then:
ssh brightsign@<player-ip>

mkdir -p /usr/local && cd /usr/local
unzip /storage/sd/ext_pydev-*.zip
bash ./ext_pydev_install-lvm.sh
reboot  # Extension auto-starts after reboot

See: docs/deployment.md for complete deployment guide.

Documentation

Getting Started

QUICKSTART.md - 60-90 minute walkthrough (START HERE)
WORKFLOWS.md - Copy-paste commands for common tasks
FAQ.md - Answers to 25+ common questions
check-prerequisites - Validate system before building

Detailed Guides

docs/getting-started.md - First-time setup details
docs/building.md - Build system and recipe development
docs/deployment.md - Player setup and deployment
docs/model-zoo-guide.md - NPU examples and usage
docs/troubleshooting.md - Common issues and fixes

Advanced Topics

user-init/README.md - Custom initialization scripts
docs/architecture-understanding.md - System architecture
docs/adr/ - Architecture Decision Records

Features

Python Environment

Core Python (built-in):

Python 3.8.19 + standard library
pip, setuptools, wheel
Full cross-compilation for ARM64

Pre-installed Packages:

# Computer Vision
import cv2              # OpenCV 4.x
import PIL              # Pillow image processing
from skimage import *   # scikit-image

# Deep Learning
import torch            # PyTorch 2.4.1
import onnx             # ONNX model format

# NPU Acceleration
from rknnlite.api import RKNNLite  # RKNN toolkit 2.3.2

# Scientific Computing
import numpy            # NumPy 1.24.4
import pandas           # pandas 2.0.3
import scipy            # SciPy 1.10.1
import matplotlib       # matplotlib 3.7.5

# And 50+ more packages...

NPU Acceleration

RK3588 Neural Processing Unit:

6 TOPS performance
~10x faster than CPU inference
Low power consumption
Official RKNN model zoo support

Example: YOLOX object detection

CPU: ~100ms per frame
NPU: ~10ms per frame (6 FPS → 60+ FPS real-time)

Model Zoo: 50+ pre-trained models available (YOLO, RetinaFace, SegFormer, etc.)

User Initialization System

Automatic package installation:

# Place requirements.txt in /storage/sd/python-init/
# Packages auto-install on boot

echo "opencv-contrib-python" >> /storage/sd/python-init/requirements.txt
# Installs automatically next reboot

Custom init scripts:

# Shell scripts in /storage/sd/python-init/*.sh
# Auto-run on extension startup
# Use for: model downloads, env setup, validation checks

Security: User scripts disabled by default (run as root), must enable via registry.

See user-init/README.md for details.

Supported Players

Player Model	Minimum OS Version	Status
XT-5 (XT1145, XT2145)	9.1.79.3	✅ Tested
Firebird	9.1.79.3+	🔄 In Process
LS-5 (LS445)	9.1.79.3+	🔄 In Process

Why 9.1.79.3+? This OS version includes the NPU runtime library (librknnrt.so) at /usr/lib/librknnrt.so. Earlier versions will encounter RKNN initialization failures.

Configuration

Registry Settings (via DWS)

Access DWS at http://<player-ip>:8080 → Registry tab:

Registry Key	Default	Description
`bsext-pydev-enable-user-scripts`	`false`	Enable user init scripts (security: runs as root)
`bsext-pydev-disable-auto-start`	`false`	Disable extension auto-start (for debugging)

Enable user scripts:

registry write extension bsext-pydev-enable-user-scripts true
# Restart player for changes to take effect

Disable auto-start (for troubleshooting):

registry write extension bsext-pydev-disable-auto-start true
# Restart, then manually control extension

Example: NPU Object Detection

Run YOLOX object detection with NPU acceleration in <10 minutes:

# 1. Download model and test image (on dev machine)
wget https://github.com/airockchip/rknn_model_zoo/releases/download/v2.3.2/yolox_s_rk3588.rknn
wget https://raw.githubusercontent.com/airockchip/rknn_model_zoo/v2.3.2/examples/yolox/model/bus.jpg
scp yolox_s_rk3588.rknn bus.jpg brightsign@<player-ip>:/usr/local/

# 2. On player: Setup model_zoo
ssh brightsign@<player-ip>
source /usr/local/pydev/sh/setup_python_env

cd /usr/local
wget https://github.com/airockchip/rknn_model_zoo/archive/refs/tags/v2.3.2.zip
unzip v2.3.2.zip && mv rknn_model_zoo-2.3.2 rknn_model_zoo

# Copy compatibility wrapper (enables RKNNLite API)
cp -r /usr/local/pydev/examples/py_utils \
      /usr/local/rknn_model_zoo/examples/yolox/python/

# 3. Run inference
cd /usr/local/rknn_model_zoo/examples/yolox/python
python3 yolox.py --model_path /usr/local/yolox_s_rk3588.rknn \
                 --target rk3588 \
                 --img_folder /usr/local/ \
                 --img_save

# Results: ./result/bus.jpg with bounding boxes

Expected: Detects bus (93% confidence), people (85-90%) using NPU in ~10ms

See: docs/model-zoo-guide.md for more examples and custom models.

Troubleshooting

Quick Diagnostics

# On dev host: Validate prerequisites
./check-prerequisites

# On player: Check extension status
ssh brightsign@<player-ip>
/var/volatile/bsext/ext_pydev/bsext_init status

# View logs
tail -f /var/log/bsext-pydev.log

# Test Python environment
source /var/volatile/bsext/ext_pydev/sh/setup_python_env
python3 -c "import cv2, torch, numpy; print('OK')"

Common Issues

Issue	Quick Fix
Build fails: "Not x86_64"	Use x86_64 machine or cloud VM (see FAQ)
Build fails: "No space"	Free 50GB+ disk space
Player: RKNN init fails	Upgrade to OS 9.1.79.3+
Extension won't install	Unsecure player (`SECURE_CHECKS=0`)
Scripts don't run	Enable user scripts via registry (see troubleshooting guide)

Full troubleshooting:

Build issues: docs/troubleshooting.md
User script issues: docs/troubleshooting-user-init.md

Project Structure

.
├── setup                    # Setup script (run once)
├── build                    # Build script (main build tool)
├── package                  # Package creation script
├── check-prerequisites      # System validation script
├── QUICKSTART.md            # 60-90 min quick start guide
├── WORKFLOWS.md             # Common workflow commands
├── FAQ.md                   # Frequently asked questions
│
├── bsoe-recipes/            # BitBake recipe overlays
│   └── meta-bs/recipes-devtools/python/  # Python package recipes
│
├── user-init/               # User initialization system
│   ├── examples/            # Ready-to-deploy scripts
│   ├── templates/           # Script templates
│   └── tools/               # Deployment helpers
│
├── docs/                    # Detailed documentation
│   ├── getting-started.md
│   ├── building.md
│   ├── deployment.md
│   ├── model-zoo-guide.md
│   ├── troubleshooting.md
│   └── adr/                 # Architecture decisions
│
└── sh/                      # Build and extension scripts

Development Workflow

First-Time Setup

./check-prerequisites  # Validate system
./setup -y             # Setup (5-10 min)
./build --extract-sdk  # Build (30-60 min)
./package              # Package (5 min)

Incremental Rebuild

# After modifying a recipe
./build --clean python3-opencv
./build python3-opencv
./build --extract-sdk
./package

Add Python Package

# Create recipe in bsoe-recipes/meta-bs/recipes-devtools/python/
./check-recipe-syntax.py python3-newpackage.bb
./build python3-newpackage
./build --extract-sdk
./package

See WORKFLOWS.md for more common tasks.

Contributing

Contributions welcome! Areas of interest:

Python packages: Add more CV/ML libraries
Documentation: Improve guides and examples
Testing: Validate on different players
Examples: Create demo applications

See CONTRIBUTING.md for guidelines.

Licensing

Project: Apache 2.0 License (see LICENSE.txt)
Models: Check individual model licenses (see model-licenses.md)
Dependencies: Various open source licenses

Getting Help

Quick start: QUICKSTART.md
Common workflows: WORKFLOWS.md
FAQ: FAQ.md
Troubleshooting: docs/troubleshooting.md
Issues: GitHub Issues

Credits

Built with:

BrightSign OS (OpenEmbedded/Yocto)
Rockchip RKNN toolkit
Python 3.8 + ecosystem
Docker

Maintained by BrightSign development team.

Name		Name	Last commit message	Last commit date
Latest commit History 41 Commits
.claude		.claude
.vscode		.vscode
bsoe-recipes/meta-bs		bsoe-recipes/meta-bs
docs		docs
include		include
plans		plans
scripts		scripts
sh		sh
src		src
user-init		user-init
.gitignore		.gitignore
BUGS.md		BUGS.md
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
Dockerfile		Dockerfile
FAQ.md		FAQ.md
LICENSE.txt		LICENSE.txt
QUICKSTART.md		QUICKSTART.md
README-original.md		README-original.md
README.md		README.md
TODO.md		TODO.md
WORKFLOWS.md		WORKFLOWS.md
build		build
build_plan.md		build_plan.md
check-prerequisites		check-prerequisites
check-recipe-syntax.py		check-recipe-syntax.py
check_recipes.py		check_recipes.py
dnn_fix.md		dnn_fix.md
gap_plan.md		gap_plan.md
package		package
rknn_executor_patched.py		rknn_executor_patched.py
setup		setup
validate		validate
verify_checksums.py		verify_checksums.py
wmt-test.py		wmt-test.py
wmt_requirements.txt		wmt_requirements.txt

License

brightsign/python-cv-dev-extension

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BrightSign Python Extension for CV Development (ALPHA RELEASE)

What Is This?

System Architecture

Prerequisites

Critical Requirements

❌ NOT Compatible

Quick Start

Three Commands to Build

Deploy to Player

Documentation

Getting Started

Detailed Guides

Advanced Topics

Features

Python Environment

NPU Acceleration

User Initialization System

Supported Players

Configuration

Registry Settings (via DWS)

Example: NPU Object Detection

Troubleshooting

Quick Diagnostics

Common Issues

Project Structure

Development Workflow

First-Time Setup

Incremental Rebuild

Add Python Package

Contributing

Licensing

Getting Help

Credits

About

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