These-People-Do-Not-Exist
image-quality-assessment
These-People-Do-Not-Exist | image-quality-assessment | |
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2 | 2 | |
15 | 2,009 | |
- | 1.5% | |
0.0 | 0.0 | |
over 2 years ago | 5 months ago | |
Python | Python | |
- | Apache License 2.0 |
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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.
image-quality-assessment
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And so it begins: AI(Midjourney) wins art competition without anyone realising.
It's an ongoing research area, but here's a Google model that assigns images ratings based on how good they look. It's pretty good, and it's from 2019 so not even close to state of the art. Paired with Stable Diffusion, it could indeed curate itself. I might have to try that actually.
- Extracting Images from Video
What are some alternatives?
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
student-teacher-anomaly-detection - Student–Teacher Anomaly Detection with Discriminative Latent Embeddings
IAmNotReal - App that uses machine learning to generate human faces
GLOM-TensorFlow - An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data
deepfake-scanner - Deepfake Scanner by Deepware.
DarkMark - Marking up images for use with Darknet.
ALAE - [CVPR2020] Adversarial Latent Autoencoders
imagededup - 😎 Finding duplicate images made easy!
Crystal-Rush - An open world platformer game
image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
robin - RObust document image BINarization
efficientnet - Implementation of EfficientNet model. Keras and TensorFlow Keras.