xuqiantong / Gan Metrics
An empirical study on evaluation metrics of generative adversarial networks.
Stars: ✭ 307
Labels
Projects that are alternatives of or similar to Gan Metrics
Musicautobot
Using deep learning to generate music in MIDI format.
Stars: ✭ 304 (-0.98%)
Mutual labels: jupyter-notebook
Bayesmadesimple
Code for a tutorial on Bayesian Statistics by Allen Downey.
Stars: ✭ 303 (-1.3%)
Mutual labels: jupyter-notebook
Deepsurv
DeepSurv is a deep learning approach to survival analysis.
Stars: ✭ 303 (-1.3%)
Mutual labels: jupyter-notebook
Baby Steps Of Rl Ja
Pythonで学ぶ強化学習 -入門から実践まで- サンプルコード
Stars: ✭ 302 (-1.63%)
Mutual labels: jupyter-notebook
Cartola
Extração de dados da API do CartolaFC, análise exploratória dos dados e modelos preditivos em R e Python - 2014-20. [EN] Data munging, analysis and modeling of CartolaFC - the most popular fantasy football game in Brazil and maybe in the world. Data cover years 2014-19.
Stars: ✭ 304 (-0.98%)
Mutual labels: jupyter-notebook
Qiskit Community Tutorials
A collection of Jupyter notebooks developed by the community showing how to use Qiskit
Stars: ✭ 298 (-2.93%)
Mutual labels: jupyter-notebook
Minibook 2nd Code
Code of the IPython Minibook, 2nd edition (2015)
Stars: ✭ 303 (-1.3%)
Mutual labels: jupyter-notebook
Us county level election results 08 20
United States General Election Presidential Results by County from 2008 to 2016
Stars: ✭ 305 (-0.65%)
Mutual labels: jupyter-notebook
Opensleep
platform for sleep hacking and research
Stars: ✭ 304 (-0.98%)
Mutual labels: jupyter-notebook
Zat
Zeek Analysis Tools (ZAT): Processing and analysis of Zeek network data with Pandas, scikit-learn, Kafka and Spark
Stars: ✭ 303 (-1.3%)
Mutual labels: jupyter-notebook
120 Ds Interview Questions
My Answer to 120 Data Science Interview Questions
Stars: ✭ 304 (-0.98%)
Mutual labels: jupyter-notebook
Geopandas Tutorial
Tutorial on geospatial data manipulation with Python
Stars: ✭ 306 (-0.33%)
Mutual labels: jupyter-notebook
Tensorflow 2.x Yolov3
YOLOv3 implementation in TensorFlow 2.3.1
Stars: ✭ 300 (-2.28%)
Mutual labels: jupyter-notebook
Covid19 twitter
Covid-19 Twitter dataset for non-commercial research use and pre-processing scripts - under active development
Stars: ✭ 304 (-0.98%)
Mutual labels: jupyter-notebook
Atpbetting
A strategy for tennis matches betting
Stars: ✭ 306 (-0.33%)
Mutual labels: jupyter-notebook
GAN Metrics
This repository provides the code for An empirical study on evaluation metrics of generative adversarial networks.
Requirement
- Python 3.6.4
- torch 0.4.0
- torchvision 0.2.1
- pot 0.4.0
- tqdm 4.19.6
- numpy, scipy, math
Usage
- We create a demo for DCGAN training as well as computing all the metrics after each epoch.
In the demo, final metrics scores of all epoches will be scored in<outf>/score_tr_ep.npy
- If you want to compute metrics of your own images, you have to modify the codes of function
compute_score_raw()
inmetric.py
by yourself :)
python3 demo_dcgan.py \
--dataset cifar10 \
--cuda \
--dataroot <data_folder> \
--outf <output_folder> \
--sampleSize 2000
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].