AI Recognition

Overview

AI recognition is a cutting-edge technology in drone intelligence. In this project, you will learn how to deploy a TinyYOLOv3 model on ESP32-S3 to perform object detection.

What You’ll Learn

• Deep learning model deployment
• Model quantization
• Inference optimization
• Object detection algorithms

Materials Needed

Item	Quantity	Notes
ESP32-S3 Drone	1	-
OV2640 Camera Module	1	-
MicroSD Card	1	8GB+

Step 1: Prepare the Model

1. Download a pre-trained TinyYOLOv3 model (COCO dataset)
2. Use the tensorflow lite converter to convert the model to INT8 quantized .tflite format
3. Copy the model and the label file coco_labels.txt to the MicroSD card

Step 2: Hardware Wiring

MicroSD card module → ESP32-S3 SPI interface

Step 3: Open the Project

Unzip ai_detection.zip and open it with VS Code.

Step 4: Implement the Inference Function

Open yolo_detect.c and implement object detection:

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 run inference
    load_model("/sdcard/tiny_yolo_v3.tflite");
    run_inference(preprocessed_frame);

    // 3. Postprocess: decode output and filter low-confidence detections
    decode_output(output, detections, detection_count);
    filter_detections(detections, detection_count, 0.5); // confidence threshold 0.5
}

Step 5: Testing

1. Place different targets (e.g., person, chair) in front of the drone
2. Observe the detection results
3. Challenge: add a “target priority” feature so the drone tracks people first instead of other objects

Troubleshooting

Slow inference

• Optimize the model size
• Use INT8 quantization

Low detection accuracy

• Adjust the confidence threshold
• Improve the input image quality

Achievement

Congratulations! You have successfully implemented AI object detection — a cutting-edge technology in drone intelligence!

Next Steps

In the next project, you will learn how to build a multi-drone MESH network.