robin
These-People-Do-Not-Exist
robin | These-People-Do-Not-Exist | |
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1 | 2 | |
169 | 15 | |
- | - | |
0.0 | 0.0 | |
almost 2 years ago | over 2 years ago | |
Python | Python | |
MIT License | - |
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robin
These-People-Do-Not-Exist
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Github
two
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TinyML: Deploying TensorFlow models to Android
A while back, researchers at NVIDIA released StyleGAN, a machine learning model that synthesizes images of pretty much anything from random noise, say images of landscapes, art, people, or vehicles. I saw a demo of it and it honestly blew my mind. Shortly after I implemented StyleGAN myself.
What are some alternatives?
Single-Image-Dehazing-Python - python implementation of the paper: "Efficient Image Dehazing with Boundary Constraint and Contextual Regularization"
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
image-quality-assessment - Convolutional Neural Networks to predict the aesthetic and technical quality of images.
open-mcr - :pencil: Exam bubble sheet scorer. Created with OpenCV and Python.
IAmNotReal - App that uses machine learning to generate human faces
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
deepfake-scanner - Deepfake Scanner by Deepware.
pandora - Pandora is an analysis framework to discover if a file is suspicious and conveniently show the results
ALAE - [CVPR2020] Adversarial Latent Autoencoders
MODNet-BGRemover - A deep learning approach to remove background & adding new background image
Crystal-Rush - An open world platformer game