Statistical analysis of sample values to approximate the final pixel value

Jérôme BUISINE be401816c8 Merge branch 'release/v0.0.9' 4 年之前
generate 95cba96b9b Use of modules dependency 4 年之前
modules @ d5de038bdc 95cba96b9b Use of modules dependency 4 年之前
notebooks 87b8d18661 Write Keras result script 5 年之前
others 95cba96b9b Use of modules dependency 4 年之前
reconstruct 95cba96b9b Use of modules dependency 4 年之前
.gitignore ab86ef6206 Documentation and ignore files updates 4 年之前
.gitmodules 95cba96b9b Use of modules dependency 4 年之前
LICENSE d0ebc63822 Update of documentation 4 年之前
README.md ab86ef6206 Documentation and ignore files updates 4 年之前
__init__.py beb4716c41 Add of feature choices 4 年之前
compare_images.py 95cba96b9b Use of modules dependency 4 年之前
custom_config.py 95cba96b9b Use of modules dependency 4 年之前
features.py 95cba96b9b Use of modules dependency 4 年之前
generate_data.sh cccee3b412 Update of Keras scripts 5 年之前
run.sh 95cba96b9b Use of modules dependency 4 年之前
run_keras.sh 95cba96b9b Use of modules dependency 4 年之前
train_model.py 018d8e801f Update of train model script 4 年之前
train_model_keras.py 95cba96b9b Use of modules dependency 4 年之前

README.md

Sample Analysis

Description

The aim of this project is to predict the mean pixel value from monte carlo process rendering in synthesis images using only few samples information in input for model.

Data

Data are all scenes samples information obtained during the rendering process.

For each pixel we have a list of all grey value estimated (samples).

Models

List of models tested :

  • Ridge Regression
  • SGD
  • SVR (with rbf kernel)

How to use

First you need to contact jerome.buisine@univ-littoral.fr in order to get datatset version. The dataset is not available with this source code.

python make_dataset.py --n 10 --each_row 8 --each_column 8
python reconstruct.py --scene Scene1 --model_path saved_models/Model1.joblib --n 10 --image_name output.png

License

The MIT license