Assistance in Running and Understanding Space-Related Computer Vision Code from GitHub

We are working on a computer vision project in the space domain. Our task is to find existing code for specific space-related applications, run the code on our computers, and understand how it works.

(meaning we just have to run existing code from the internet e.g. GitHub... modifications on the source are allowed but no writing of code with no reference of an existing code)

We have already identified the following applications and their corresponding GitHub repositories:

1. Crater detection on planetary surfaces
Repository: [YOLOv5 Moon and Mars Crater Detection](https://github.com/Krishna8483/YOLOv5_moon_mars_crater_detection/blob/main/Crater_detection_yolov5(Krishna).ipynb)

2. Colorizing grayscale telescope images
Repository: [Colorizing Space Images with GANs](https://www.kaggle.com/code/anshkgoyal/colorizing-greyscale-space-images-with-gans)

3. Predicting the names of planets from their images
Repository: [Planet Name Prediction](https://github.com/Krishna8483/YOLOv5_moon_mars_crater_detection/blob/main/Crater_detection_yolov5(Krishna).ipynb)

4. Meteorite classification
Repository: [Autonomous Meteor Detector and Tracker](https://github.com/BlackBodyCircuits/Autonomous-Meteor-Detector-and-Tracker)

5. Galaxy detection and classification
Repository: [Astronomical Images Classification](https://github.com/yosrinegm/Astronomical-Images-Classification/blob/e340841e3980c69677e8457d272f55bd81f9c9fe/AstronomicalImagesClassification.ipynb)

6. Visualizing NASA data (planet size, mass, etc.) as images + (we think of changing this idea... suggest alternative)
Repository: [NASA Data Visualization](https://github.com/ChloeBors/visualizing-planets-based-on-nasa-data/blob/main/Space%20Project%20(Part%201).ipynb)

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What We Need from You:
We are looking for an experienced individual to:
1. Set up and run the code (in Google Colab):
- Download and prepare any required datasets.
- Handle large datasets (e.g., resizing, reducing size) if necessary.
- Resolve any errors to ensure the code runs smoothly.

NOTE: what we care about is the title of the application (e.g. Galaxy detection and classification)... if you find the reference not suitable you can change the reference as long as it does what the title states

2. Document the process:
- Explain how to run the code step-by-step (including dataset preparation).
- Provide clear instructions or a finalized notebook for each application.

Deliverables:
- A working Google Colab notebook for each application listed above, including the necessary data (or instructions on how to download and prepare it).
- A step-by-step guide for running the code on our own systems.
- Answers to our questions about how the code works.

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Requirements:
- Experience in computer vision, Python, and Google Colab notebooks.
- Familiarity with handling datasets for machine learning.
- Ability to troubleshoot code and resolve errors effectively.

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Additional Details:
- We will run the code on our Google Colab.
- If any dataset is too large, please guide us on how to reduce its size or suggest alternatives.
- We prefer someone who can explain the process clearly and patiently.

If you’re confident in your skills and can help us achieve this, please submit your proposal. Let us know your experience with similar tasks and how you plan to approach this project.