Gradio AI web application: Hands-on Python example with JoJoGAN face stylization model
Prodramp
In this hand-on Python tutorial, you will learn how to deploy your ML model with python gradio library while running it at the Google Colab. I am using the JoJoGAN face style transfer model which we have covered in previous videos as source model to be deployed with gradio.
---------------------- One-shot Face Stylization with JoJoGAN ---------------------- Part 1/3: - In-depth Face style transfer tutorial (https://youtu.be/uXBbY1_vhSQ) Part 2/3: Code walk-through with detailed theory (https://youtu.be/K1qPbjrJuKA) Part 3/3: Model Export & Deployment (https://youtu.be/lMl7Yd7jC6A)
GitHub Resources:
ā¬ā¬ā¬ā¬ā¬ā¬ ā° TUTORIAL TIME STAMPS ā° ā¬ā¬ā¬ā¬ā¬ā¬
- (00:00) Video Starts
- (00:11) Video Content Review
- (03:37) What is covered?
- (04:13) Why Gradio?
- (05:30) Setting JoJoGAN in Colab
- (06:40) Copying models to Colab
- (08:44) Inference code as function
- (10:05) GPU Tensor to CPU numpy conversion
- (12:10) Python gradio app interface
- (13:40) Python gradio app launch
- (14:15) Testing app in as public link
- (15:20) Export notebook to GitHub
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Content Creator: Avkash Chauhan (@avkashchauhan)
Tags: #stylegan #gradio #ml #cnn #ml #lime #aicloud #h2oai #driverlessai #machinelearning #cloud #mlops #model #collaboration #deeplearning #modelserving #modeldeployment #pytorch #datarobot #datahub #streamlit #modeltesting #codeartifact #dataartifact #modelartifact #onnx #aws #kaggle #mapbox #lightgbm #xgboost #classification #dataengineering #pandas #keras #tensorflow #tensorboard #cnn #prodramp #avkashchauhan #LIME #mli #xai ... https://www.youtube.com/watch?v=ZMQAC-VKpVM
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