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AI Blitz X: Completed #educational Weight: 30.0
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Welcome to AI Blitz X! πŸš€

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Introduction

High-altitude Unmanned Aerial Vehicle is revolutionary technology! The images from high-altitude UAVs can help detect fires, humans, and wildlife like mountain terrains and thick forests. The images also help in improving understanding of hard-to-reach geographical areas. 

One of the biggest challenges in using high-altitude UAV images in the presence of clouds! One cannot always wait for clear skies to collect data and these clouds act as a major obstacle in getting clear images. 

Your final task for Blitz X is to remove clouds from high-altitude UAV images. Check out the starter kit to make your first submission!


πŸ’ͺ Getting Started

So in this challenge, the task is to remove the clouds from a high-altitude UAV Imagery.

Use our Getting Started Notebook available here. 


πŸ’Ύ Dataset

In this dataset, for a given data file, such as train.zip. There will be two groups of videos, clear and cloud. The number after the video name will represent the video id.   Sample data format  - 

train
β”œβ”€β”€ clear_0.mp4
β”œβ”€β”€ cloud_0.mp4
β”œβ”€β”€ clear_1.mp4
β”œβ”€β”€ cloud_1.mp4
└── ...

Sample Videos - 

Note - 

  • Make sure the videos are in .mp4 format
  • Make sure that there is a total of 24 frames in the video.  

πŸ“ Files

Following files are available in the resources section:

  • train.zip - [ 2000 samples ]  Used for Training. Include labels.
  • partial_train.zip - [ 500 samples ] Subset of train.zip. Use for getting started! 
  • test.zip  - [ 500 samples ] Used for evaluation. Does not include labels. 

πŸš€  Submission

  • Creating a submission directory
  • Create a clear folder inside the submission directory.  
  • Inside a submission directory, put the .ipynb notebook from which you trained the model and made inference and save it as original_notebook.ipynb.
  • Overall, this is what your submission directory should look like
     submission
     β”œβ”€β”€ clear
     β”‚   β”œβ”€β”€ clear_0.mp4
     β”‚   β”œβ”€β”€ clear_1.mp4
     β”‚   β”œβ”€β”€ ...
     β”‚   └── clear_499.mp4
     └── original_notebook.ipynb
  • Zip the submission directory!

Make your first submission here πŸš€ !!


πŸ–Š Evaluation Criteria

During the evaluation, Mean Squared Error will be used to test the efficiency of the model.


πŸ”— Links

πŸ“± Contact

Notebooks

See all
Cloud Removal using Opencv
By
sai_bhargav
Over 2 years ago
0
Solution for submission 152419
By
ksnxr
Over 2 years ago
0
Solution for submission 152002
By
salim_shaikh
Over 2 years ago
0
[Random Submission] Cloud Removal
By
Shubhamaicrowd
Over 2 years ago
0