this is my repository for the quick draw prediction model project
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Updated
Nov 22, 2017 - Python
this is my repository for the quick draw prediction model project
Quick, Draw! Doodle Recognition Challenge (Rank 11/1316)
Web app to detect user hand-drawn sketches on a canvas. Using google's quickdraw dataset. App built using python with flask and keras API.
Classifying Google Quick, Draw! Dataset Using Tensoflow 2.0
Doodle image recognition with TensorFlow.
Quickdraw_grid generates a grid of vector drawings from Google's "Quick, Draw!" database, based on user's input - selected category, number of rows and columns.
Conditional GAN for the quickdraw dataset
Implementation of Quickdraw - an online game developed by Google
Implementation of Quickdraw - an online game developed by Google
Hand-drawn image recognition project using Python, inspired by Google's Quick, Draw!.
Real-time drawing recognition game using MediaPipe hand tracking and a deep learning model trained on the Google Quick, Draw! dataset.
Implementation of Google's QuickDraw Game, instead of drawing on screen, drawing is done in air, and i used CNN to create the model. This is just an experimental project.
Farms GitHub achievements via backdated commits, coauthored PRs, and seeded discussions on your repos.
SketchGuess AI is a small interactive machine learning project where users draw a simple doodle, and a CNN model predicts the top three possible objects with confidence scores using a selected subset of Google’s Quick, Draw! dataset.
Zero-shot vector sketch generation via GMM prior flow in CLIP latent space
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