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flower-species-classification's Introduction

Flower-Species-Prediction

© Raj Gupta 2021


Paper Referenced from:

VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION. Karen Simonyan∗ & Andrew Zisserman + Visual Geometry Group, Department of Engineering Science, University of Oxford {karen,az}@robots.ox.ac.uk
https://arxiv.org/pdf/1409.1556.pdf


Dataset:

https://www.kaggle.com/alxmamaev/flowers-recognition

Architecture used

  • VGG16
  • MobileNetV2
  • Self created 5 CNN models
  • No. of classes: 5


Metrics for 20 Epochs (for VGG16)

  • loss: 0.0066
  • accuracy: 1.0000
  • val_loss: 0.7674
  • val_accuracy: 0.8125


    • Deployment

    • Deployed it as a web app using Flask.



    Libraries used

    • Flask==1.1.2
    • numpy==1.18.4
    • tensorflow==2.2.0
    • Werkzeug==1.0.1


    Tools used

    • Pycharm
    • Google Colab
    • git






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