Python on ESP32

Real-Time Vision AI in Just a Few Lines

Learn More

Python on ESP32

Real-Time Vision AI in
Just a Few Lines

Capture, processing, inference, and display — all on the device.

Flash It Now Open Web IDE ↗

01LOW-CODE

Less code. More power.

Camera, image processing, on-device inference, and hardware peripherals are all accessible through Python APIs.

OUTPUTESP32-P4

Per-frame inference with a quantized ESP-DL modelVision AI

main.py17 lines

import espdl
import sensor
import time

sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(time=1000)

det = espdl.ESPDet("/sdcard/hand_det.espdl", score=0.5, nms=0.7)
while True:
    img = sensor.snapshot()
    for x, y, w, h, score, category in det.detect(img):
        img.draw_rectangle(x, y, w, h, color=(255, 0, 0), thickness=2)
        img.draw_string(x, max(0, y - 12), "%.2f:%d" % (score, category))
    img.flush()
    time.sleep_ms(20)

02CAPABILITIES

Complexity. Handled.

Capture, processing, inference, and control all run on the device.

API01

Low-Code Python API

Unified sensor · image · display · espdl APIs — real-time results in a few lines of Python. Flash online, connect the Web IDE, no toolchain to set up.

AI02

On-Device ESP-DL Inference

Object detection, pose estimation, and image classification; load a quantized .espdl model in one line — real-time, offline, on device — or bring your own PyTorch / TensorFlow model.

VLM03

Cloud Vision LLMs

Stream straight to OpenAI-compatible vision APIs and tap multimodal models like GPT-4o — complex scene understanding with no local compute.

IMG04

Image Processing

Drawing, filtering, color tracking, feature detection, QR codes, barcodes, and AprilTags.

CDC05

Hardware Codec

H.264 / MJPEG / RTSP and USB CDC live preview, saturating the on-chip multimedia accelerators.

IO06

Rich Peripheral Support

Cameras, displays, SPI, I2C, UART, SD cards and more work out of the box, with a MicroPython machine-compatible API.

03SETUP

Zero setup. Just go.

No toolchain installation is required; flashing, writing, and running all happen in the browser.

BROWSER

One-Click Flashing

Connect your board straight from the browser and flash the official firmware.

Online Flashing · Web Serial○ No device connected

1. Select Firmware
2. Flash
3. Start Device
4. Connect Wi-Fi

Chip

Board

Firmware

Connect the board with a data cable (not a charge-only cable) using desktop Chrome / Edge. Click Connect Serial to read firmware and model information. The board enters download mode only when you click Start Flashing.

Flash Mode

Checking flashing support for the selected firmware…

Download firmware bin (2026.10.23)

IDE / VS CODE

Write & Run

Write scripts in the Web IDE or VS Code and watch capture and inference results in real time.

Open Web IDE Download VS Code Extension

04CONNECT AI

Describe it. AI builds it.

Connect the ESP-VISION MCP to an AI assistant to build edge vision applications through conversation.

Server URL

https://mcp.vision.espressif.com

Auto Install

Click the button below to add this server to Cursor automatically.

Add to Cursor →

Manual config (mcp.json)

{
  "mcpServers": {
    "esp-vision-mcp": {
      "url": "https://mcp.vision.espressif.com"
    }
  }
}

Auto Install

Click the button below to add this server to VS Code automatically.

Install to VS Code →

VS Code config

{
  "mcp": {
    "servers": {
      "esp-vision-mcp": {
        "type": "http",
        "url": "https://mcp.vision.espressif.com"
      }
    }
  }
}

05MODELS

Any model. Just one line.

ESP-DL and TFLite Micro models are loaded from device storage in a single line of code.

Connect the running board to import models without flashing firmware.

Download saves to your computer. Import writes to the connected board and does not run the model.

Use desktop Chrome or Edge with a USB data cable to connect a device.

ESP-DL12 models

Model	Task	Input	Dataset	Size	Actions
ESPDet Pico Cat ESPDet Pico · `espdl.ESPDet` Detects cats in camera images. cat	Object Detection	224×224 RGB565	Cat	487 KB	Download Locally ↓
ESPDet Pico Cat & Dog ESPDet Pico · `espdl.ESPDet` Detects cats and dogs in camera images. catdog	Object Detection	224×224 RGB565	Cat & Dog↗	561 KB	Download Locally ↓
ESPDet Pico Dog ESPDet Pico · `espdl.ESPDet` Detects dogs in camera images. dog	Object Detection	224×224 RGB565	Dog	486 KB	Download Locally ↓
ESPDet Pico Face ESPDet Pico · `espdl.ESPDet` Detects human faces in camera images. face	Object Detection	224×224 RGB565	Face	484 KB	Download Locally ↓
ESPDet Pico Hand ESPDet Pico · `espdl.ESPDet` Detects human hands in camera images. hand	Object Detection	224×224 RGB565	Hand	486 KB	Download Locally ↓
ESPDet Pico Hardhat ESPDet Pico · `espdl.ESPDet` Detects safety helmets in camera images. helmet	Object Detection	320×320 RGB565	Hard Hat Workers Computer Vision Model	561 KB	Download Locally ↓
YOLO11n COCO YOLO11n · `espdl.YOLO11` Detects the 80 COCO object classes in camera images.	Object Detection	160×160 RGB565	COCO	2.7 MB	Download Locally ↓
YOLO11n-Pose COCO YOLO11n-Pose · `espdl.YOLO11nPose` Detects people and estimates 17 COCO body keypoints (human pose) in camera images. person	Pose Estimation	160×160 RGB565	COCO	3.0 MB	Download Locally ↓
NanoTrack V2 Search INT8 NanoTrack V2 · `espdl.NanoTrack` Search branch for touch-selected single-object tracking. Requires all three NanoTrack V2 model files.	tracking	255×255 RGB565	Training set of upstream published weights not independently verified	320 KB	Download Locally ↓
NanoTrack V2 Head INT8 NanoTrack V2 · `espdl.NanoTrack` Head branch for touch-selected single-object tracking. Requires all three NanoTrack V2 model files.	tracking	8×8×48 + 16×16×48 INT8 NHWC features	Training set of upstream published weights not independently verified	236 KB	Download Locally ↓
NanoTrack V2 Template INT8 NanoTrack V2 · `espdl.NanoTrack` Template branch for touch-selected single-object tracking. Requires all three NanoTrack V2 model files.	tracking	127×127 RGB565	Training set of upstream published weights not independently verified	320 KB	Download Locally ↓
PicoDet Pedestrian Detection PicoDet · `espdl.PedestrianDetect` Detects pedestrians in camera images with the shared ESP32-P4 model export. person	Object Detection	224×224 RGB565	Not specified by upstream	425 KB	Download Locally ↓

TFLite Micro2 models

Model	Task	Input	Dataset	Size	Actions
Person Detection MobileNet · `tflite.Model` TensorFlow Lite Micro person-detection model: classifies whether a person is present in a 96x96 grayscale camera frame. no personperson	Image Classification	96×96 GRAYSCALE	Visual Wake Words	294 KB	Download Locally ↓
Sine MLP · `tflite.Model` TensorFlow Lite Micro "hello world" model: approximates sin(x) for x in [0, 2*pi] from a single scalar input.	Regression	1 FLOAT32	Synthetic	2 KB	Download Locally ↓

Add a Custom Model ↗

06BOARDS

One framework. Every board.

Camera, display, and storage work out of the box across the ESP32-S31, ESP32-P4, and ESP32-S3 series.

Board	Chip	ESP-VISION Support
AtomS3R-M12↗	ESP32-S3	Supported sensor · image · display · lcd_touch · espdl · tflite · imageio
ESP32-P4X-EYE↗	ESP32-P4	Supported sensor · image · display · lcd_touch · espdl · tflite · imageio · h264 · rtsp · barcode
ESP32-P4X-Function-EV-Board↗	ESP32-P4	Supported sensor · image · display · lcd_touch · espdl · tflite · imageio · h264 · rtsp · barcode
ESP32-P4X-VISION↗	ESP32-P4	Supported sensor · image · display · lcd_touch · espdl · tflite · imageio · h264 · rtsp
ESP32-S3-EYE↗	ESP32-S3	Supported sensor · image · display · lcd_touch · espdl · tflite · imageio
ESP32-S31-Korvo-1↗	ESP32-S31	Supported sensor · image · display · lcd_touch · espdl · tflite · imageio