Illuminated3D This project participates in the Nasa Space Apps Challenge 2021.

Overview

NASA-Space-Apps-Challenge-2021

Illuminated3D This project participates in the Nasa Space Apps Challenge 2021.

Documentation of the Illuminat3d App

Version 1.0

The main scope of this application is to plot the light curve of an asteroid for certain values of the input variables. The project consists of two .py files (.py and .py).

GUIFinal.py file

This is the file that we create the User Interface (UI) of our application. It have a space that the user load his 3D model (.stl file format). Then the user must fill in every enrty of the variables in the right form and finally push the Run Program button to see the light curve plot in the corresponding window. The User Interface except all the widgets (Button, Label, Entry, Images) has and 3 functions:

  • browseFiles(): in this function we set the directory that the application can search to find the user's 3D model. When a file is selected then the label of the file explorer change text to specify the path of the file.
  • popup_window_1(): function that triggered when the info button is pressed and pops out an information message.
  • checkInputs(): in this function we check the validity of the input variables and then create an Illuminated object to start running the main program.

Illuminated_Class_Git.py file

In this file we create a class Illuminated to control the core of our program and to plot the light curves of the input 3D models. This class has several functions to produce the expected output.

  • __ init__(self, filename, initRot, rotAxis, frames, albedo, omega): is the contructor of the class which assigns the proper values to the class variables. It recieves as inputs the filename of the 3D model(filename), the initial rotation axis and angle (initRot), the rotational axis (rotAxis), the number of frames (frames), the albedo (albedo) and the omega angle(omega).
  • checkTheModel(self): this function check if the 3D model that the user inserted is valid(close object). Return boolean value True or False.
  • computeIntersectionsAreas(self, multi): recieves a Multipolygon object and returns its total area.
  • multColumns(self, col1, col2): recieves two arrays and produce a new one of the same length. Each element of this array is the multiplication of the two initial arrays' corresponding elements (i.e. new_col[5] = col1[5]*col2[5])
  • sortCoords(self, arr, ind): this is an extra function which sorts the rows of the 2D arr array under the 1D index array.
  • sortDist(self, arr, ind): this is an extra function which sorts the values of the 1D arr array under the 1D index array.
  • desortDist(self, arr, ind): with this function we de-sort the distances array back to its initial structure.
  • computeCoefs(self, coords, dist, dots): compute the coefficients array depending on the coordinates, distances and dots arrays. By taking one triangle at a time we compute the area of each triangle that is seen by the viewer.
  • n_vec(self, tha, thb, thc): return a normalized vector as the cosines of the given angles tha, thb, thc. Each input is the angle that this vector forms with the corresponding axix (x, y, z).
  • v_surf(self, cube ,n_v): return the viewing surface when looking in the n_v direction (either as the source or as the viewer).
  • execution(self): in this function we calibrate the model with its rotation and the position of the light and the viewer and we plot the asteroid's light curve. The number of the plot's points is implied by the number of frames.

Installation

Use the package manager pip to install the necessary libraries.

pip install python-math
pip install numpy-stl
pip install matplotlib
pip install tk
pip install shapely

Execution

After you download the project in your computer, you must move to the directory that the python files are and run the command below.

python GUIFinal.py

Members

  1. Doli Maria
  2. Eleftheriadis Emmanouil
  3. Komitis Dimitrios
  4. Liodis Ioannis
  5. Noula Konstantina
  6. Rodiou Eirini
Owner
Eleftheriadis Emmanouil
Eleftheriadis Emmanouil
The Environment I built to study Reinforcement Learning + Pokemon Showdown

pokemon-showdown-rl-environment The Environment I built to study Reinforcement Learning + Pokemon Showdown Been a while since I ran this. Think it is

3 Jan 16, 2022
A Python library for common tasks on 3D point clouds

Point Cloud Utils (pcu) - A Python library for common tasks on 3D point clouds Point Cloud Utils (pcu) is a utility library providing the following fu

Francis Williams 622 Dec 27, 2022
Chinese clinical named entity recognition using pre-trained BERT model

Chinese clinical named entity recognition (CNER) using pre-trained BERT model Introduction Code for paper Chinese clinical named entity recognition wi

Xiangyang Li 109 Dec 14, 2022
Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

Yam Peleg 63 Sep 21, 2022
LaBERT - A length-controllable and non-autoregressive image captioning model.

Length-Controllable Image Captioning (ECCV2020) This repo provides the implemetation of the paper Length-Controllable Image Captioning. Install conda

bearcatt 53 Nov 13, 2022
Simultaneous Demand Prediction and Planning

Simultaneous Demand Prediction and Planning Dependencies Python packages: Pytorch, scikit-learn, Pandas, Numpy, PyYAML Data POI: data/poi Road network

Yizong Wang 1 Sep 01, 2022
Bootstrapped Representation Learning on Graphs

Bootstrapped Representation Learning on Graphs This is the PyTorch implementation of BGRL Bootstrapped Representation Learning on Graphs The main scri

NerDS Lab :: Neural Data Science Lab 55 Jan 07, 2023
PartImageNet is a large, high-quality dataset with part segmentation annotations

PartImageNet: A Large, High-Quality Dataset of Parts We will release our dataset and scripts soon after cleaning and approval. Introduction PartImageN

Ju He 77 Nov 30, 2022
Implementation of UNET architecture for Image Segmentation.

Semantic Segmentation using UNET This is the implementation of UNET on Carvana Image Masking Kaggle Challenge About the Dataset This dataset contains

Anushka agarwal 4 Dec 21, 2021
Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective

Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective Zhengzhuo Xu, Zenghao Chai, Chun Yuan This is the PyTorch implement

Sincere 16 Dec 15, 2022
PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks

PyDEns PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks. With PyDEns one can solve PD

Data Analysis Center 220 Dec 26, 2022
PyTorch implementation of Glow

glow-pytorch PyTorch implementation of Glow, Generative Flow with Invertible 1x1 Convolutions (https://arxiv.org/abs/1807.03039) Usage: python train.p

Kim Seonghyeon 433 Dec 27, 2022
a baseline to practice

ccks2021_track3_baseline a baseline to practice 路径可能会有问题,自己改改 torch==1.7.1 pyhton==3.7.1 transformers==4.7.0 cuda==11.0 this is a baseline, you can fi

45 Nov 23, 2022
[ICCV '21] In this repository you find the code to our paper Keypoint Communities

Keypoint Communities In this repository you will find the code to our ICCV '21 paper: Keypoint Communities Duncan Zauss, Sven Kreiss, Alexandre Alahi,

Duncan Zauss 262 Dec 13, 2022
🔥RandLA-Net in Tensorflow (CVPR 2020, Oral & IEEE TPAMI 2021)

RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds (CVPR 2020) This is the official implementation of RandLA-Net (CVPR2020, Oral

Qingyong 1k Dec 30, 2022
GANSketchingJittor - Implementation of Sketch Your Own GAN in Jittor

GANSketching in Jittor Implementation of (Sketch Your Own GAN) in Jittor(计图). Or

Bernard Tan 10 Jul 02, 2022
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22)

Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22) Ok-Topk is a scheme for distributed training with sparse gradients

Shigang Li 9 Oct 29, 2022
Fine-tune pretrained Convolutional Neural Networks with PyTorch

Fine-tune pretrained Convolutional Neural Networks with PyTorch. Features Gives access to the most popular CNN architectures pretrained on ImageNet. A

Alex Parinov 694 Nov 23, 2022
a general-purpose Transformer based vision backbone

Swin Transformer By Ze Liu*, Yutong Lin*, Yue Cao*, Han Hu*, Yixuan Wei, Zheng Zhang, Stephen Lin and Baining Guo. This repo is the official implement

Microsoft 9.9k Jan 08, 2023
Specificity-preserving RGB-D Saliency Detection

Specificity-preserving RGB-D Saliency Detection Authors: Tao Zhou, Huazhu Fu, Geng Chen, Yi Zhou, Deng-Ping Fan, and Ling Shao. 1. Preface This reposi

Tao Zhou 35 Jan 08, 2023