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100312dog/esp-dl

3.3.0

Latest
uploaded 1 day 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 detection with specific configurations for ESP32-P4 and ESP32-S3.
    226.36 KB
  • color_detect
    A simple image inference example that detects colors from an image.
    13.23 KB
  • dog_detect
    A simple image inference example that uses a test image to demonstrate detection results with and without quantization.
    633.70 KB
  • hand_detect
    A simple image inference example using hand detection with specified configurations for different ESP32 chips.
    365.57 KB
  • hand_gesture_recognition
    A simple image inference example for hand gesture recognition supporting 10 gestures plus a 'no_hand' category.
    750.97 KB
  • how_to_run_model
    12.81 KB
  • human_face_detect
    A simple image inference example for human face detection, showcasing how to use the ESP-IDF framework.
    42.52 KB
  • human_face_recognition
    A simple image inference example for human face recognition, utilizing two models for detection and feature extraction.
    102.67 KB
  • mobilenetv2_cls
    A simple image inference example using IMAGENET classification. Follow the quick start guide to flash the example.
    38.99 KB
  • model_in_sdcard
    10.68 KB
  • motion_detect
    52.15 KB
  • pedestrian_detect
    A simple image inference example for pedestrian detection, showing results through an IDF monitor.
    96.93 KB
  • speaker_verification
    A simple audio inference example for speaker verification using three audio samples to determine cosine similarity.
    681.76 KB
  • yolo11_detect
    A simple image inference example using Yolo11, demonstrating detection results before and after quantization.
    670.34 KB
  • yolo11_pose
    A simple image inference example using Yolo11 for pose detection on ESP32 hardware. Outputs can be viewed in the IDF monitor.
    266.98 KB
  • yolo26_detect
    This example demonstrates running quantized YOLOv26n inference on Espressif SoCs with high performance and flexibility.
    3.21 MB