espressif/esp-dl

3.3.6

Latest
uploaded 14 hours ago
esp-dl is a lightweight and efficient neural network inference framework designed specifically for ESP series chips.

19 examples

  • how_to_deploy_streaming_model 1
  • cat_detect
    A simple image inference example using `cat.jpg` for testing to demonstrate object detection results.
    226.87 KB
  • color_detect
    A simple image inference example for color detection.
    13.26 KB
  • dog_detect
    A simple image inference example using dog.jpg for testing, showcasing detection results before and after quantization.
    634.21 KB
  • hand_detect
    A simple image inference example using hand detection with configurable model options for ESP32 devices.
    367.67 KB
  • hand_gesture_recognition
    A simple image inference example supporting 10 hand gestures and a "no_hand" category using the HaGRID dataset.
    751.48 KB
  • how_to_run_model
    12.84 KB
  • human_face_detect
    A simple image inference example for human face detection using ESP-IDF with configurable options.
    43.03 KB
  • human_face_recognition
    A simple example for human face recognition using image inference. It supports models for face detection and feature extraction.
    103.18 KB
  • mobilenetv2_cls
    A simple image inference example for IMAGENET classification that outputs category scores.
    39.50 KB
  • model_in_sdcard
    10.71 KB
  • motion_detect
    52.64 KB
  • pedestrian_detect
    A simple image inference example for pedestrian detection using ESP-IDF.
    97.44 KB
  • speaker_verification
    A simple audio inference example that compares audio samples from different speakers using cosine similarity.
    682.25 KB
  • yolo11_detect
    A simple image inference example using Yolo11 for object detection with quantization results shown.
    399.39 KB
  • yolo11_pose
    A simple image inference example using Yolo11 Pose with ESP32-P4, testing with a default image and settings.
    267.49 KB
  • yolo26_detect
    This example demonstrates YOLOv26n inference on Espressif SoCs with optimizations for various custom models.
    3.21 MB