Celestial-bodies-detection

Setup

Tensorflow

Create a virtual environment (recommended)

Python virtual environments are used to isolate package installation from the system.

Create a new virtual environment by choosing a Python interpreter and making a ./venv directory to hold it:

virtualenv --system-site-packages -p python3 ./venv

Activate the virtual environment using a shell-specific command:

source ./venv/bin/activate # sh, bash, ksh, or zsh

If using conda, you can run conda create -n tensorflow python=3.7 source activate tensorflow

Install Requirements

pip install -r requirements.txt

OR

Install Tensorflow

pip install tensorflow==1.14

Install wikipedia

pip install wikipedia

Install PyYAML

pip install PyYAML

Inception

Downloaded automatically while training

Using Model

Classified Neptune Image and percentage of Accuracy

output1

Classified Jupiter Image and percentage of Matched Accuracy

output3

Shows the percentage of every class

output2

Fetched information from Internet

output4

Reverse Search of Classified Image

output5

Accuracy of matching of Spiral Galaxy

output6

Fetched information from Internet of the Classified Class

output7

Train model

python retrain.py --bottleneck_dir=bottlenecks --how_many_training_steps=500 --model_dir=inception --summaries_dir=training_summaries/basic --output_graph=retrained_graph.pb --output_labels=retrained_labels.txt --image_dir=./training_data

Test model

python label_image.py test_data/uranus.jpg

INCEPTION

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The Inception network was an important milestone in the development of CNN classifiers. Prior to its inception (pun intended), most popular CNNs just stacked convolution layers deeper and deeper, hoping to get better performance.

The Inception network, on the other hand, was complex (heavily engineered). It used a lot of tricks to push performance; both in terms of speed and accuracy. Its constant evolution led to the creation of several versions of the network.

The below image is the “naive” inception module. It performs convolution on an input, with 3 different sizes of filters (1x1, 3x3, 5x5). Additionally, max pooling is also performed. The outputs are concatenated and sent to the next inception module.

inception

CELESTIAL BODIES

An astronomical object or celestial object is a naturally occurring physical entity, association, or structure that exists in the observable universe. [1] In astronomy, the terms object and body are often used interchangeably. However, an astronomical body or celestial body is a single, tightly bound, contiguous entity, while an astronomical or celestial object is a complex, less cohesively bound structure, which may consist of multiple bodies or even other objects with substructures.

Examples of astronomical objects include planetary systems, star clusters, nebulae, and galaxies, while asteroids, moons, planets, and stars are astronomical bodies. A comet may be identified as both body and object: It is a body when referring to the frozen nucleus of ice and dust, and an object when describing the entire comet with its diffuse coma and tail.

GALAXIES

A galaxy is an enormous collection of interstellar dust, gas, stellar remnant, stars along with their own solar systems held together by gravity. Earth is situated in the Milky Way galaxy. The Milky Way is a spiral-shaped galaxy with a diameter ranging 100,000 and 180,000 light-years. Our galaxy was thought to contain all the stars in the universe until, in 1920, Edwin Hubble observed that the Milky Way is one of many galaxies in the universe and that every galaxy contains potentially billions or trillions of stars. To this day, only a small fraction of galaxies have been discovered.

In recent years, astronomy has become an immensely data-rich field with numerous digital sky surveys across a wide range of wavelengths. For example, the Sloan Digital Sky Survey will produce over 50,000,000 images of galaxies in the near future. Studying the morphology of galaxies is one of the most important aspects of answering many of the questions to which humanity does not yet know the answer, namely the creation of the universe. Scientists can understand the origin, formation, and evolution of galaxies by classifying galaxies by their structural appearance. The morphological classification of galaxies in a large database is important to help astronomers reduce classification errors and to help them collect statistical and observational data and discover the mystery of nature in general.

Astronomers can look into time and space as far as billions of light years away from Earth and explore millions of galaxies far away using space telescopes that are much more powerful than our eyesight.

galaxies Figure 1: Three classes of galaxy morphological. From left to right: Elliptical Shaped Galaxy, Spiral Shaped Galaxy and Irregular Shaped Galaxy (en.Wikipedia.org, 2006)

There are different types of galaxies:

PLANETS

A planet is an astronomical body orbiting a star or stellar remnant that is massive enough to be rounded by its own gravity, is not massive enough to cause thermonuclear fusion, and has cleared its neighbouring region of planetesimals. There are a total of 8 planets in our solar system:

mercury

venus

earth

mars

jupiter

saturn

uranus

neptune

License

ritwik12/Celestial-bodies-detection is licensed under the GNU General Public License v3.0

Permissions of this strong copyleft license are conditioned on making available complete source code of licensed works and modifications, which include larger works using a licensed work, under the same license. Copyright and license notices must be preserved. Contributors provide an express grant of patent rights.

  1. The origin of this software must not be misrepresented; you must not claim that you wrote the original software. If you use this software in a product, an acknowledgment in the product documentation would be appreciated but is not required.
    1. Altered source versions must be plainly marked as such, and must not be misrepresented as being the original software.