ESP32-S3 TinyML Image Classifier
ESP32-S3 TinyML Image Classifier: Deploy MobileNet on a 240MHz Microcontroller
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Point a camera at a banana, an apple, or a person, and watch the ESP32-S3 identify it instantly — no cloud, no Wi-Fi. This kit puts a full image classifier in your hands, running TensorFlow Lite Micro MobileNet on a 240MHz dual-core chip. Whether you're exploring the CBSE AI curriculum or building a hackathon prototype, you'll learn to shrink and deploy a real neural network onto embedded hardware.
What You'll Build
A standalone image classification camera that captures frames with the OV2640 sensor, runs a quantized MobileNet model, and shows the predicted class and confidence on a 0.96-inch OLED. The entire pipeline runs on the ESP32-S3 — no laptop required after upload. Use it for automated sorting, gesture recognition, or a portable vision system for your next Smart India Hackathon entry.
What You'll Learn
- Convert a TensorFlow MobileNet model to TensorFlow Lite and quantize it for an 8-bit microcontroller
- Configure the ESP32-S3's PSRAM and camera driver to read OV2640 frames in RGB565
- Integrate the TensorFlow Lite Micro interpreter and run inference at ~2 frames per second
- Output predictions to an I2C OLED and use serial debugging to profile model latency
Kit Contents
| Component | Quantity |
|---|---|
| ESP32-S3 Dev Board | 1 |
| OV2640 Camera Module | 1 |
| 0.96in OLED | 1 |
| MicroUSB Cable | 1 |
| M-M Wires | 15 |
Why Buy This Kit Instead of Sourcing Parts Separately
| Factor | Sourcing Separately | Compoden Kit |
|---|---|---|
| Compatibility checks | You verify every part | Pre-tested as a system |
| Build support | Forums and scattered tutorials | AI companion trained on this exact project |
| Time to first working build | Days of debugging | Hours, with step-by-step guidance |
| Shipping coordination | Multiple sellers, multiple delays | One shipment from Bengaluru in 3-5 days |
Who This Kit Is For
Ideal for CBSE Class 11-12 students taking the AI elective who need a working TinyML project for their practical file. B.Tech ECE/EEE students can use it for final-year mini projects, while ATL Tinkering Lab mentors get a ready-to-assemble computer vision kit. It fits hackathon teams from IIT, NIT, VIT, and BITS tackling Smart India Hackathon problem statements on edge AI.
Built and Backed by Compoden
Every Compoden kit ships with an AI build companion trained on this exact project — accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.
What if I get stuck during the build?
Scan the QR code on the box to talk to the AI companion, which has been trained on this exact kit. It visualises wiring, explains code block by block, and if needed, a human engineer jumps in over WhatsApp — usually within an hour.
Do I need prior AI/ML knowledge to use this kit?
Some familiarity with C/C++ and Arduino IDE is enough. The AI companion walks you through model conversion and deployment steps even if you’re new to TensorFlow Lite. If you've trained a model before, you can swap in your own MobileNet variant.
Can I train my own custom model for this hardware?
Yes. The ESP32-S3 can run any quantized TensorFlow Lite Micro model that fits within PSRAM. You can train a new image model on Teachable Machine or TensorFlow and then follow our companion’s conversion guide to deploy it.
How do I power the setup away from a laptop?
The ESP32-S3 board can run from any standard USB power bank using the microUSB cable. The camera and OLED draw minimal current, so a 5V/1A supply is more than sufficient for portable demos.
TensorFlow Lite Micro runs MobileNet on ESP32-S3 with OV2640 camera — on-device image classification with 240MHz MCU.
What's in this kit
- ESP32-S3 Dev Board
- OV2640 Camera Module
- 0.96in OLED
- MicroUSB Cable
- M-M Wires x15
Shipping Information
- Prepaid Orders: ₹75 for orders up to ₹999, FREE shipping above ₹999
- COD Orders: ₹125 shipping + ₹50 COD fee = ₹175 total
- Delivery Timeline: Dispatch in 1-2 days, delivery in 2-7 days depending on location
Returns & Warranty
- 7-Day Return: Manufacturing defects only (approval required)
- Warranty: 7 days from delivery
- Non-Returnable: Batteries, consumables, cut wires, clearance items