Computer Vision & AI Lab Setup
From Pixels to Intelligence — Real-Time AI at the Edge
Advanced computer vision and AI lab for 20 students. Covers classical computer vision with OpenCV, deep learning (PyTorch/TensorFlow), object detection, pose estimation, and edge AI deployment on NVIDIA Jetson.
Choose Your Package
All packages designed for 20 students — scalable on request
Starter
Jetson Nano per student with USB cameras and GPU workstations
- NVIDIA Jetson Nano 4GB × 20
- USB Webcam 1080p/60fps × 20
- Raspberry Pi 4 4GB + Camera v3 × 10 (per pair)
- GPU Workstation (RTX 3060) × 5 (1 per 4 students)
- Monitor 24" × 5 (for workstations)
- microSD 64GB Class 10 × 20
- Cooling fan + case for Jetson Nano × 20
Standard
Stereo + depth cameras, NVIDIA Jetson AGX, full deep learning stack
- Everything in Starter
- NVIDIA Jetson AGX Orin 32GB × 2 (class demo)
- Intel RealSense D435i stereo depth camera × 4
- FLIR Lepton thermal camera module × 2
- GPU Workstation (RTX 4070) × 5
- Green screen backdrop + LED lighting kit × 1
- GPU server (RTX 4090 or A5000) × 1 for model training
Professional
Industrial cameras, Hailo-8 accelerator, video analytics platform
- Everything in Standard
- Basler acA1920-50gc industrial camera × 4
- Hailo-8L AI acceleration hat × 10 (for Raspberry Pi)
- Stereoscopic 360° camera × 2
- NVIDIA DGX Station A100 × 1 (central training)
- TensorRT + DeepStream server × 1
- Calibration targets + optical bench × 2
- Model annotation workstations × 5
Equipment List
Complete equipment for 20 students — varies by selected package
| Equipment | Qty | Specification |
|---|---|---|
| NVIDIA Jetson Nano 4GB | 20 units | Quad-core Cortex-A57 + 128-core Maxwell GPU, 4GB LPDDR4 |
| NVIDIA Jetson AGX Orin 32GB | 2 units | 12-core Cortex-A78AE + 2048-core Ampere GPU, 275 TOPS, 32GB |
| Raspberry Pi 4 4GB + Camera v3 | 10 sets | Cortex-A72 + 12MP Sony IMX708, autofocus, 120° FoV |
| Hailo-8L AI Hat (for Raspberry Pi) | 10 units | 13 TOPS inference, PCIe M.2 + hat form factor, ResNet50 @ 156fps |
Software & Tools
Included software stack — licensed for each student workstation
Python 3 + OpenCV 4
Open-SourceClassical CV — filtering, edge detection, feature matching, video processing
PyTorch + torchvision
Open-SourceDeep learning — CNN, transfer learning, custom model training
YOLOv8 (Ultralytics)
Open-SourceReal-time object detection, segmentation, pose estimation
NVIDIA TensorRT + DeepStream
FreeModel optimization and video analytics pipeline on Jetson
CVAT / LabelMe
Open-SourceImage and video annotation for custom dataset creation
Jupyter Lab + Google Colab
FreeInteractive notebooks + cloud GPU training for large models
Curriculum Modules
6 modules from Beginner to Advanced — typically covered in one academic semester
Duration: 2 weeks
- Image as array (BGR, HSV)
- Pixel manipulation, color spaces
- NumPy vectorized operations
- Matplotlib visualization
What Makes This Lab Complete
20 NVIDIA Jetson Nano for per-student edge AI inference
Jetson AGX Orin for class-level demo of production AI pipelines
Stereo depth (RealSense) + thermal (FLIR) for specialized CV labs
Full pipeline: data annotation → training → INT8 quantization → edge deploy
GPU training server shared across class for large model training
Industry frameworks: PyTorch, TensorRT, DeepStream, YOLOv8
Infrastructure Requirements
What your institution needs to provide before installation
Room Size
Minimum 800 sq ft — GPU workstations + Jetson benches + studio area for camera experiments
Power
GPU workstations need 600–800W each; plan 5× 15A circuits + 20× 5A for Jetson benches
Network
1 Gbps LAN mandatory — large datasets (10–50GB) need fast internal transfer; 100 Mbps broadband + cloud access
GPU Cooling
Powerful AC (1.5+ ton) — RTX 4090 training server generates 450W continuous heat; rack placement with top-exhaust preferred
Internet / Cloud
Google Colab / AWS credits for students — training large models locally on Jetson Nano is not practical
Setup Process
Consultation
Our team reviews your space, budget and learning objectives to recommend the right package.
Procurement
We source all equipment, verify quality and arrange delivery to your institution.
Installation
Our engineers set up all hardware, networking, software and test every workstation.
Training
Faculty training session included — start teaching from day one with our curriculum guide.
Get a Custom Quote
For Computer Vision & AI Lab Setup — 20 students