Deepfakes Software For All
-
Updated
Sep 24, 2019 - 891 commits
- 61 contributors
- Python
Deepfakes Software For All
DeepFaceLab is a tool that utilizes machine learning to replace faces in videos. Includes prebuilt ready to work standalone Windows 7,8,10 binary (look readme.md).
This is the placeholder for information regarding the building of deepdetect on Ubuntu 16.04 LTS (expected future reference platform).
Build status: successful, tested with Caffe back-end on CPU
Thanks to @MartinThoma the correct way of doing it is below:
$ sudo apt-get remove libcurlpp0
$ cd [wherever]
$ git clone https://github.com/jpbarrette/curlpp.git
$ cd curlpp
$ cmake .
$ s
Minicourse in Deep Learning with PyTorch
Evolutionary Algorithm using Python
A deep neural net toolkit for emotion analysis via Facial Expression Recognition (FER)
Machine learning for C# .Net
Hierarchical Attentive Recurrent Tracking
(Spring 2017) Assignment 2: GPU Executor
Classifying the Blur and Clear Images
Trying to understand neural nets by building a simple one from scratch
Bidirectional Attention Flow for Machine Comprehension implemented in Keras 2
A Python-Tensorflow neural network for classifying cancer data
Neural network + training framework in Golang
Adam, NAdam and AAdam optimizers
Efficient Self-Organizing Map for Sparse Data
Targeting EEG/LFP synchrony with neural nets
This repository contains a collection of neural network models that we used to demonstrate the utility of our dataset.
Jupyter notebooks on Julia programming
A neural branch predictor tested using CPU emulator, testing both supervised learning and reinforcement learning (for COS 583: Great Moments in Computing at Princeton University)
Create simple neural networks in Go
Easy to use neural network library in java
McCulloch & Pitts neural net simulator.
A list of awesome and easy-to-read NN articles
Neural networks with dynamic topologies trained using a genetic algorithm
An invalid image causes internal server error.
Image should be:
Or maybe preprocess the image?
Issue Description
I'm unable to run DL4J with nvidia CUDA back end despiite following the instructions here:
https://deeplearning4j.org/docs/latest/deeplearning4j-config-gpu-cpu
Project works fine with native back end. When I debug, I can see the service loader finding the JCublasBackend.java class and then failing on isAvailable().
As far as I can tell I've done everything recommende