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All Projects → huma-teknofest → Keras Retinanet For Teknofest 2019

huma-teknofest / Keras Retinanet For Teknofest 2019

Using RetinaNet for object detection from drone images in Teknofest istanbul 2019 Artificial Intelligence Competition

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Keras RetinaNet for Teknofest 2019 AI Competition

Using RetinaNet for object detection from drone images in Teknofest istanbul 2019 Artificial Intelligence Competition

🚀 Teknofest 2019 - Yapay Zeka Yarışması:

TEKNOFEST 2019 Yapay Zeka Yarışması kapsamında takımlar bir drone ile önceden kaydedilmiş görüntüler üzerinden verilen süre içerisinde araç ve insan tespitini özel bir metrik üzerinden IoU puanı ile puanlandırılmıştır.

📚 Öğretici Döküman (Tutorial)

Keras RetinaNet kurulum ve kendi veri kümenizi eğitmek ve test etmek için detaylı öğretici dökümanını buradan inceleyebilirsiniz.

📋 Başlangıç Kılavuzu (Getting Started)

💾 Ön Koşullar (Software Prerequisites)

📘 Klasör Yapısı (Folder Structure)

main_dir
- dataset_test
- retinanet
    - keras_retinanet
    - models
        - teknofest19_huma_resnet50_21_37_inference.h5
    - snapshots
        - teknofest19_huma_resnet50_21_37_ss.h5
    - results
    - detect_all_images.py

⌛️ Eğitim (Train)

RetinaNet'in Keras implementasyonuna ve eğitim dökümanına buradan ulaşabilirsiniz.

Drone ile çekilmiş yaklaşık 30bin görüntü üzerinden etiketlenmiş araç ve insan veri kümesi ile 58 epoch eğitilmiş ResNet-50 RetinaNet snapshot dosyasını buradan indirebilirsiniz.

⌚️ Test

Önceden eğitilmiş ve dönüştürülmüş model dosyası olan teknofest19_huma_resnet50_21_37_inference.h5 dosyasını buradan indirerek retinanet klasörü altında models klasörü altına kopyalayınız.

Test yapabilmeniz için örnek test görüntülerini buradan indererek dataset_test klasörü altına kopyalayınız.

Eğitilmiş model ile dataset_test klasöründeki resimler üzerinde nesne tespiti yapmak için detect_all_images.py python programını çalıştırabilirsiniz. Tahmin (prediction) sonuçlarını results klasörü altına resmin üzerine çizilmiş şekilde çıkartılacaktır.

🎉 Sonuçlar (Results)

📡 Contact (İletişim)

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