README.md

ESP-DL Model Zoo

Model Name	Description	Latest Version	Supported Chips	Examples
YOLO26	Universal NMS-Free object detection (COCO 80 classes)		ESP32-S3, ESP32-P4	Link
COCO Detect	YOLO11n object detection for 80 COCO categories		ESP32-S3, ESP32-P4	Link
COCO Pose	YOLO11n-Pose estimation for human keypoints		ESP32-S3, ESP32-P4	Link
Human Face Detect	High-performance face detection (MSR/MNP/ESPDet)		ESP32-S3, ESP32-P4	Link
Human Face Recognition	Face feature extraction and ID matching		ESP32-S3, ESP32-P4	Link
Cat Detect	Lightweight cat detection (espdet-pico)		ESP32-S3, ESP32-P4	Link
Dog Detect	Lightweight dog detection (espdet-pico)		ESP32-S3, ESP32-P4	Link
Hand Detect	Real-time hand detection (espdet-pico)		ESP32-S3, ESP32-P4	Link
Hand Gesture	Classification of 8+ hand gestures		ESP32-S3, ESP32-P4	Link
Imagenet Cls	MobileNetV2 image classification (1000 classes)		ESP32-S3, ESP32-P4	Link
Pedestrian Detect	Pedestrian detection for surveillance/robotics		ESP32-S3, ESP32-P4	Link
Speaker Verification	Voiceprint recognition and verification		ESP32-P4	Link
Motion Detect	Frame-to-frame motion change detection		All ESP32 Series	Link
Color Detect	Color-based object tracking (OpenCV-mobile)		All ESP32 Series	Link

Visual Showcase

Cat Detection	Hand Gesture	Hand Detection
Dog Detection	COCO Detection

How to Use Models

All models in this directory are structured as ESP-IDF components. To use them in your project:

1. Add as Dependency: Add the model component to your main/idf_component.yml or project root.
2. Configuration: Use idf.py menuconfig to select the model location (Flash/PSRAM/SDCard) and default sub-models.
3. Loading:

   #include "cat_detect.hpp"
   CatDetect *detect = new CatDetect();
   auto results = detect->run(img);

For detailed metrics and latency, please refer to the README.md within each model's directory.