As a throwback to Blitz 7, we are putting on our spacesuit again!
Docking is the process of joining one spacecraft to another space station. It is a very high-precision task, requiring accurate hand-eye coordination. Even a small mistake can lead to failure.
SpaceX Dragon spacecraft attempted autonomous docking but what if the sensors onboard malfunctioned?! Can you dock a spacecraft successfully using only the input from the camera?
Your first Blitz X task is to calculate the distance and the central location of the docking port given the input image.
💪 Getting Started
In this challenge, the task is to calculate the distance between the Spacecraft & ISS. and the central location of the docking port.
Use our Getting Started Notebook available here.
In the train set. There are 2 files train.zip & train.csv. Sample train.csv -
- The ImageID column In train.csv is corresponding to the image name in the train.zip.
- The distance column represents the distance from the picture to the docking port on ISS.
- The location is the pixel coordinates ( x, y ) of the docking port.
Few things to note -
- The camera angle does not affect the distance from ISS Docking Port.
- The point of reference for calculating the distance is always the same.
- The camera is stationary in generating the samples.
Following files are available in the
10000samples) - File containing images for the training set.
10000samples) - File containing labels for the training set.
1000samples) - File containing images for the validation set.
1000samples) - File containing labels for the validation set.
5000samples) - File containing images for the testing set.
5000samples) - File containing sample labels for the testing set.
- Creating a submission directory
submission.csvand fill the corresponding labels.
- Save the submission.csv in the assets directory. The name of the above file should be
- Inside a submission directory, put the .ipynb notebook from which you trained the model and made inference and save it as
- Overall, this is what your submission directory should look like -
submission ├── assets │ └── submission.csv └── original_notebook.ipynb
- Zip the submission directory!
Make your first submission here 🚀 !!
🖊 Evaluation Criteria
During the evaluation. For the Distance & Location Column, Mean Squared Error will be used to test the efficiency of the model.
- 💪 Challenge Page: https://www.aicrowd.com/challenges/docking-iss
- 🗣️ Discussion Forum: https://www.aicrowd.com/challenges/docking-iss/discussion
- 🏆 Leaderboard: https://www.aicrowd.com/challenges/docking-iss/leaderboards