Building a Deep learning model with Keras and ResNet-50

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  • OpenCV

    Open Source Computer Vision Library

  • You first import the OpenCV library. It will pre-process the selected flower image to ensure it has the same dimensions as the images that trained the deep learning model.

  • stylegan2-projecting-images

    Projecting images to latent space with StyleGAN2.

  • Ensure you use Google Colab notebook to run the Python code. Google Colab is powerful since it uses Google's cloud GPUs to run the deep learning model. Once you have the Google Colab notebook, let's start setting up our project.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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