RKNN metrics

This repository allows you to evaluate results using mAP metrics.

Usage

Running Inference

Use main.py to perform object detection inference on a set of images.

Command-Line Arguments

• --model_path (str, required): Path to the model file (.rknn, .onnx).
• --dataset_path (str): Path to validation-images and YOLO annotation files (labels) (default: data/).

Example Command

python main.py \
    --model_path models/yolov8.rknn \
    --dataset_path data/

Example

1. Prepare Data

   • Place your images in data/images.
   • Place your annotations .txt files in data/labels.

2. Configure detector

   Adjust thresholds, input-image sizes, and class labels as needed.

3. Run Inference and Evaluation

   python main.py \
       --model_path models/yolov8.rknn \
       --dataset_path data/ 

4. View Results

   • mAP metrics will be printed in the console.