# Arducam Pico4ML - RP2040 TinyML Dev Kit

**Type:** Product page · **SKU:** CE08479 · **Brand:** [The Pi Hut](https://core-electronics.com.au/brands/the-pi-hut)
**Page:** https://core-electronics.com.au/arducam-pico4ml-rp2040-tinyml-dev-kit.html ([markdown](https://core-electronics.com.au/arducam-pico4ml-rp2040-tinyml-dev-kit.html.md))

To make the Raspberry Pi Pico more robust for TensorFlow Lite Micro, the Arducam team took the Raspberry Silicon (also known as the RP2040 chip) and...

## Pricing

- **Price:** $72.30 (inc GST) — $65.73 AUD, exc GST
- **Quantity discounts:** 6+ $63.23 (exc GST) · 12+ $61.25 (exc GST)

## Availability & dispatch

- In stock, ships same business day if ordered before 2PM (Australia/Sydney). Delivered by Tue, 11th of Aug.
- We can dispatch 1 today; more stock is typically available with a 5–8 day lead time.

## Description

To make the [Raspberry Pi Pico](https://core-electronics.com.au/catalog/product/view/sku/CE07564) more robust for TensorFlow Lite Micro, the Arducam team took the Raspberry Silicon (also known as the RP2040 chip) and created the open-source Pico4ML, a microcontroller development board made exclusively for running and training machine learning examples!

**This compact RP2040-based board packs an inertial measurement unit (IMU), camera module, 0.96" OLED and microphone!** The Pico4ML also comes with its own micro-USB cable.

[User manual available here](https://core-electronics.com.au/attachments/localcontent/b0302_pico4ml_user_manual_44512374a0b.pdf) and a [dedicated GitHub repo](https://github.com/ArduCAM/pico-tflmicro) can be found here. More documentation is available in the resources section further down the page.

**QVGA Camera Module**

A QVGA camera module with ultra-low power consumption, configurable 1-bit video data serial interface with video frame and line sync, and the monochrome sensor make image processing an easy part for most machine vision applications.

**0.96" LCD**

The small TFT display at the back of Pico4ML is a 160×80 LCD, it’s connected to the board through the SPI interface, you can do a live preview of the camera, or display the results of any of your ML models in real-time.

**Onboard Microphone & IMU**

The audio chip on the Pico4ML is capable of directly outputting PDM (Pulse-density modulation) signals, this integration allows the RP2040 to receive audio input, and it’s great for all the speech/voice recognition models. Motion tracking is also a built-in feature, the 2.5 mW low-power 9-axis IMU we used is just another ideal match for the RP2040 chip.

**Open Source**

Arducam Pico4ML is completely open-source, all its codes, design files, and schematics will be made available for anyone to use, rebuild or modify.

**Pico4ML Specifications**

- Microcontroller: Raspberry Pi RP2040
- IMU: ICM-20948 (low power)
- Mono channel microphone w/ direct PCM output
- Buttons: Reset & Boot
- Camera Module: HiMax HM01B0, Up to QVGA (320 x 240)
- Screen: 0.96 inch LCD SPI Display (160 x 80, ST7735)
- Operating Voltage: 3.3V
- Current Draw (standby): 40mA
- Current Draw (running ML models): 60mA
- Input Voltage: VBUS: 5V +/- 10%. VSYS Max: 5.5V
- Length: 51 mm
- Width: 21 mm

**Three Pre-trained TF Lite Models from The Official TinyML Book**

Arducam have included three pre-trained TensorFlow Lite micro examples, including Person Detection, Magic Wand, and Wake-Word Detection. You can also build, train and deploy your models on it.

**Demo 1: Wake-Word Detection**

“Hey, Google” “Alexa.” Use a pre-trained speech detection model to provide always-on wake-word detection using a tiny microcontroller.

**Demo 2: Magic Wand (Gesture Detection)**

Wave it to cast several types of spells in one of the following three gestures: “Wing”, “Ring” and “Slope”.

**Demo 3: Person Detection**

Classify Images captured by a camera to recognize if a person is in the camera input or not

**Package Contents**

- 1 x Arducam Pico4ML Dev Board
- 1 x Micro USB Cable

**Resources**

- [User Manual](https://core-electronics.com.au/attachments/localcontent/b0302_pico4ml_user_manual_44512374a0b.pdf)
- [Github](https://github.com/ArduCAM/pico-tflmicro)
- Pico4ML Enclosure STEP File
- [Getting Started with MicroPython on RPi Pico](https://core-electronics.com.au/products/get-started-with-micropython-on-raspberry-pi-pico)
- [C/C++ Development w/ Pico and RP2040-based Boards](https://core-electronics.com.au/attachments/localcontent/getting-started-with-pico_345508fef8d.pdf)
- [Raspberry Pi Pico Datasheet](https://core-electronics.com.au/attachments/localcontent/pico-datasheet_17326d9cb0c.pdf)
- [RP2040 Datasheet](https://core-electronics.com.au/attachments/localcontent/rp2040-datasheet_51483bc02aa.pdf)
- [RPi Pico C/C++ SDK](https://core-electronics.com.au/attachments/localcontent/raspberry-pi-pico-c-sdk_3876448922c.pdf)
- [RPi Pico Python SDK](https://core-electronics.com.au/attachments/localcontent/raspberry-pi-pico-python-sdk_181315361b0.pdf)
- [API references](https://raspberrypi.github.io/pico-sdk-doxygen/modules.html)
- [Burn firmware](https://www.raspberrypi.org/documentation/rp2040/getting-started/#getting-started-with-c)

**Pico4ML Pinout**

![Pico4ML Pinout](https://core-electronics.com.au/attachments/localcontent/pico4ml-pinout_600x600_78077dcae1a.jpg)

**RP2040 Specifications**

- Dual-core Arm Cortex-M0+ processor, flexible clock running up to 133 MHz.
- 264KB on-chip SRAM.
- 2MB on-board QSPI Flash.
- 26 multifunction GPIO pins, including 3 analogue inputs.
- 2 × UART, 2 × SPI controllers, 2 × I2C controllers, 16 × PWM channels.
- 1 × USB 1.1 controller and PHY, with host and device support.
- 8 × Programmable I/O (PIO) state machines for custom peripheral support.
- Supported input power 1.8–5.5V DC.
- Operating temperature -20°C to +85°C.
- Castellated module allows soldering direct to carrier boards.
- Drag-and-drop programming using mass storage over USB.
- Low-power sleep and dormant modes.
- Accurate on-chip clock.
- Temperature sensor.
- Accelerated integer and floating-point libraries on-chip.

## Images

- [Product image 1](https://core-electronics.com.au/media/catalog/product/i/m/image_13612.jpg)