AI Recognition

Overview

AI object detection is the cutting-edge direction of drone intelligence. In this project, you will learn how to deploy TinyYOLOv3 model on ESP32-S3 for object detection.

What You’ll Learn

• Neural network basics
• Model quantization
• TensorFlow Lite for Microcontrollers
• Edge AI deployment

Materials Needed

Step 1: Understand TinyYOLOv3

TinyYOLOv3 is a lightweight object detection model suitable for deployment on resource-constrained devices.

Step 2: Model Quantization

Use TensorFlow Lite to quantize the model:

import tensorflow as tf

# Load model
model = tf.keras.models.load_model('tiny_yolo_v3.h5')

# Quantize model
converter = tf.lite.TFLiteConverter.from_keras_model(model)
converter.optimizations = [tf.lite.Optimize.DEFAULT]
tflite_model = converter.convert()

# Save quantized model
with open('tiny_yolo_v3.tflite', 'wb') as f:
    f.write(tflite_model)

Step 3: Deploy Model on ESP32-S3

Open ai_detection.c and implement model inference:

void yolo_detect(uint8_t* frame, int width, int height, 
                 Detection* detections, int* detection_count) {
    // 1. Preprocess image: resize to 416x416, normalize
    preprocess_image(frame, width, height);
    
    // 2. Load model and execute inference
    load_model("/sdcard/tiny_yolo_v3.tflite");
    run_inference(preprocessed_frame);
    
    // 3. Postprocess: decode output, filter low confidence detections
    decode_output(output, detections, detection_count);
    filter_detections(detections, detection_count, 0.5); // Confidence threshold 0.5
}

Step 4: Compile, Flash and Test

1. Copy the model file to SD card
2. Compile and flash the code
3. Test object detection functionality

Troubleshooting

Model loading fails

• Check if model file path is correct
• Confirm model format is correct

Detection speed is slow

• Reduce input image resolution
• Use more lightweight models

Achievement

Congratulations! You have successfully deployed AI object detection model on ESP32-S3, which is the cutting-edge direction of drone intelligence!

Next Steps

In the next project, you will learn how to build multi-drone communication networks.

Continue to Project 08: Multi-Drone Mesh Network →