An F1 racing grid is chaotic! When cars are driven at high speed, it often leaves a bit of a mess around them. Be it in the form of burn tire bits, sparks from the car body or smoke from the exhaust! Racers often call the smoke coming from behind a car “dirty air” which makes navigating tricky and reduces their speed. Can you help them out by removing the smoke from images of cars and provide clarity?
In this problem, you’ll be provided with an image, your job is to remove the smoke from this image using your AI model and output a clean image. Here’s a starter code kit to help you out!
The given dataset contains images of F1 cars with smoke as the noise. You need to remove the smoke and make the F1 car visible. Each image is in RGB format with size of [256,256] and are in .jpg format.
Following files are available in the
20000samples) This zip contains the training dataset containing smoke and clear images.
2000samples) This zip contains a validation dataset containing smoke and clear Images.
5000samples) This zip will be used for actual evaluation for the leaderboard
- Prepare a zip containing clear folder containing predicted images with the name matching the corresponding folder names of
- The name of the above file should be submission.zip.
- Sample submission format available at sample_submission.zip in the resources section.
Make your first submission here 🚀 !!
🖊 Evaluation Criteria
During the evaluation, the average Mean Squared Error will be calculated over all the testing images.
np.mean((real_img - predicted_img)**2)
is the code for calculating MSE for images.
- 💪 Challenge Page: https://www.aicrowd.com/challenges/f1-smoke-elimination
- 🗣️ Discussion Forum: https://www.aicrowd.com/challenges/f1-smoke-elimination/discussion
- 🏆 Leaderboard: https://www.aicrowd.com/challenges/f1-smoke-elimination/leaderboards
[Baseline] F1 Smoke Elimination