esp32 with camera and tft display for sale

A beautiful 3.5” touchscreen display, based on ESP32-WROVER, with a built-in 2M pixel OV2640 camera, makes it an ever perfect platform for your ESP32 projects.

Makerfabs ESP32 3.5” Touch with camera is absolutely open for makers, and besides, Makerfabs provide plenty of Demos to help the users on the usage. Have a try at this fantastic display in your next ESP32 project!~

This module is the 3.2” version of the ESP32 touchscreen display, based on ESP32-WROVER, with a built-in 2M pixel OV2640 camera. The LCD is 320x240 TFT, with driver is ILI9341, it uses SPI for communication with ESP32, the SPI main clock could be up to 60M~80M, make the display smooth enough for videos; and the camera OV2640 with pixel 2M, with this camera, you can make applications such as remote photography, face recognition…

While the camera not used, you can freely use all these pins with the breakout connectors, to connect the ESP32 display with sensors/ actuators, suitable for IoT applications.

The ESP32 3.5-inch TFT Touch (Capacitive) w/ Camera offers a 3.5-inch 320 x 480 TFT LCD touchscreen display. Based on ESP32-WROVER, with a built-in 2M pixel OV2640 camera, which makes it is an ever-perfect platform for your ESP32 projects.

It uses SPI for communication with ESP32, the SPI main clock could be up to 60M ~ 80M, making the display smooth enough for videos, and the camera OV2640 with pixel 2M, with this camera, you can make applications such as remote photography, face recognition.

While the camera is not used, you can freely use all these pins with the breakout connectors, to connect the ESP32 display with sensors/ actuators, suitable for IoT applications.

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Free 16G SanDisk SD Card for ESP32 3.5"/3.2" TFT Touch, so you can test the display and camera by simply powering it up. Check this video: https://youtu.be/ep8f4jEe2gE

A beautiful 3.5” touchscreen display, based on ESP32-WROVER, with built-in 2M pixel OV2640 camera, which makes it an ever perfect platform for your ESP32 projects.

The 3.5” 320x480 TFT LCD driver is ILI9488, it uses SPI for communication with ESP32, the SPI main clock could be up to 60M~80M, make the display smooth enough for videos; and the camera OV2640 with pixel 2M, with this camera, you can make applications such as remote photography, face recognition…. While the camera not used, you can freely use all these pins with the breakout connectors, to connect the ESP32 display with sensors/ actuators, suitable for IoT applications.

The ESP32 TFT Touch support Arduino or MicroPython programming. This version is Touch Capacitive, you can also get the Touch Resistive here, both precisely and stable, select the one you prefer.

Makerfabs ESP32 3.5” Touch with camera is absolutely open for makers, and besides, Makerfabs provide plenty of Demos to help the users on the usage. Have a try of this fantastic display in your next ESP32 project!~

If you receive a product with a manufacturing defect, please notify us within the 3 days of you receive the product, supported by proper pictures and description. Once our support team accept the return, we will provide a replacement or a complete refund including the return shipping cost. Please note that if your item is already soldered or modified in manner we will not be able to take it under return.

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We don"t accept the returns for the products damanged by improper use of the product. Moreover we don"t accept the return, if the ordered product is not fit for any specific application. Please read the product specifications and datasheet before selecting and ordering a product. Returns are accepted only with 3 days from the date of delivery.

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The ESP32-CAM board is a $7 device that combines an ESP32-S chip and an OV2640 camera. It allows you to set up a video streaming web server, build a surveillance camera to integrate with your home automation system, do face recognition and detection, and much more.

Besides the OV2640 camera and several GPIOs to connect peripherals, the ESP32-CAM also features a microSD card slot that can be useful to store images taken with the camera or to store files to serve to clients.

Note: to upload code to the ESP32-CAM board, you need an FTDI programmer, so you might consider getting one when you buy your board. Or you can get the best ESP32-CAM-MB Micro USB Programmer – CH340G Serial Chip.

For a quick introduction to the ESP32-CAM, you can watch the video below or read our full getting started guide: ESP32-CAM Video Streaming and Face Recognition with Arduino IDE. This guide shows you how to quickly set up a video streaming with face recognition and detection in less than 5 minutes.

The following video shows how to build a simple video streaming web server with the ESP32-CAM and how to integrate it with Home Assistant. For the written instructions, you can read our tutorial: ESP32-CAM Video Streaming Web Server (works with Home Assistant).

Learn how to take photos with the ESP32-CAM and save them in the microSD card by watching the following video tutorial. You can read our project page or the written instructions and code: ESP32-CAM Take Photo and Save to MicroSD Card.

In this project, we’ve built a motion sensor detector with photo capture using an ESP32-CAM. When your PIR sensor detects motion, it wakes up, takes a photo, and saves it in the microSD card. Read project page: ESP32-CAM PIR Motion Detector with Photo Capture.

Learn how to build a web server with the ESP32-CAM board that allows you to send a command to take a photo and visualize the latest captured photo in your browser saved in SPIFFS. We also added the option to rotate the image if necessary. Read project page: ESP32-CAM Take Photo and Display in Web Server.

Register in our brand new ESP32 course with Arduino IDE. This is our complete guide to program the ESP32 with Arduino IDE, including projects, tips, and tricks! The registrations are open, so

A while ago, I decided to try out the examplebut found it broken. A lot of library dependencies were missing. It turns out that Espressif had overhauled theiresp-facerepo intoesp-dl, and focused more on the more expensive ESP-EYE.You can find instructions in the original repo orthis articleof how to train your own TinyML model onEdge Impulse. After download the deployed Arduino library, change the imported library name in my script.

I copied the necessary files and made it work. But it is still not an elegant solution; you have to view the image in a browser, on a computer connected to the same (stable) WiFi. And you need to refresh the page (send a new request) in order to get a new photo.

At first it was not successful, since most examples useTJpg_Decoderand it use a lot of memory, causing the ESP32-CAM crash then reboot. Then I found out that there"s an function from the ESP32 library to convert JPEG into RGB565 (which is the format used by the Adafruit driver). I can even scale the image to 1/2 side size (= 1/4) so it fit the ST7735S 160x128 or 128x128 displays nicely. Everything works and problem solved.

You can find some more details about wiring, the training data (Kaggle Cats and Dogs Dataset) and the model (MobileNetV1 96x96 0.25 with transfer learning) on my repo. There"s also a copy of my model library and a boilerplate version (without using button and TFT).

The train accuracy is 89.8% and test accuracy is 86.97% on Edge Impulse. Captured image is 240x240 (resized to 120x120 on TFT and 96x96 for the model). Model inference (predict) time on ESP32-CAM is 2607 ms (2.6 secs). It"s not fast, but the setup is so cheap I think this can actually be useful as real world applications...?

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For this tutorial I’ve used an ESP32 -CAM, a 1.8″ TFT screen, an 18650 USB powerbank and a 3D printed case to make a selfie camera that automatically takes a photo when it sees a person’s face. The project has a lot of steps but is fairly simple. You can make it version without having a 3D printer.

Before uploading the code a few things need to be set up in the Arduino IDE. If this is your first time with the ESP32-CAM in the Arduino IDE you need to set up the ESP32 hardware libraries, learn to connect and test by following this tutorial ESP32-CAM in the Arduino IDE

There’s three libraries that need to be installed. The TFT_eSPI can easily be installed from the IDE library manager (Tools > Manage Libraries) by searching for TFT_eSPI. The TFT_eFEX and ESPAsyncWebserver libraries need to be installed by downloading the libraries using the the ‘Download ZIP’ link and in the IDE installing them with Sketch > Include Library > Add .ZIP Library.

The TFT_eSPI library needs to be configured to work with the ST7735S TFT panel. Copy the contents of the User_Setup.h file into the newly installed library file User_Setup.h file found in Documents > Arduino > libraries > TFT_eSPI. If you find the image quality is poor you can try other xxxxTAB versions. These refer to the colours of the tab on the screen protector but don’t match 100%.

If you want to use the countdown animation, the images for this need to be uploaded to the ESP32 memory. To do this follow the instructions to install the data folder uploader here: ESP32 Data Folder Uploader . Remember if you change the partition scheme in the IDE this data will be over-written.

Download the ZIP file from the project folder on Github https://github.com/robotzero1/esp32cam-selfiecam and unzip to your Arduino folder (In Windows 10 – Libraries > Documents > Arduino) in a directory named SelfieCam.

Below is a quick video showing the the selfie capture sequence, starting with the face being detected, the flash lighting up, the photo being taken and finally the photo being displayed from the ESP32 SPIFFS storage:

The code uses a mixture of HTTP requests and WebSockets. When the browser first connects to the ESP32 the HTML interface is sent via HTTP with this code: webserver.on("/", HTTP_GET, [](AsyncWebServerRequest * request) {

In the browser the interface loads and opens a WebSocket connection to the ESP32. This replies with a list of files in the ESP32 storage – the results of the function below: String filelist_spiffs()

Back in the browser it processes the list with the code below. addSelfieToScreen() is a function that creates objects in the DOM and fills them to create the visible interface. var filelistFromESP32 = message.data; // list of files from ESP32

When all the objects in the interface are created, the populateImgtags() function runs. This uses the fetch() method to request the selfie images from the ESP32. The images are sent from the ESP32 storage to the browser via HTTP with this code: webserver.on("/image", HTTP_GET, [](AsyncWebServerRequest * request) {

Every time a new selfie is taken another WebSocket message is sent to the browser using the command ws.textAll((char*)addtobrowser). Again on the browser a new DOM object is created with addSelfieToScreen() and the image is requested with populateImgtag() as above when the interface is first created.

Deleting an image. During the creation of the DOM each image has ‘X’ added which has an event listener attached with this code: deleteItem.addEventListener("click", function() {