AI Blitz XI: Completed #educational #blitz Weight: 10.0

Welcome to AI Blitz XI! πŸš€ | Starter Kit For This Challenge! πŸ› 

Community Contribution Prizes πŸ““  |  Find Teammates πŸ‘―β€β™€οΈ

Easy-2-Follow Notebooks πŸ’»   | Discord AI Community πŸŽ§

πŸ”₯ Introduction

In this challenge, you will have the radar sensor points mounted on a self-driving car moving through a town. Your goal will be to classify if there we any moving obstacle in front of the self-driving car. These obstacles can be pedestrians or another car within a pre-defined distance threshold. In this binary classification task, an output of 1 means there is an obstacle and 0 means there is no obstacle.



βœ”  The Task

The challenge is to use the car radar features from the dataset to build an automated algorithm to predict whether there was a dynamic object in front of the self-driving car or not:

In machine learning terms: this is a binary classification task.

πŸš€ Getting Started

Make your first submission using starter kit. πŸš€

πŸ’Ύ Dataset

The dataset files are available here. The test and train data are both contained in  data.npz .

The dataset contains information about the radars points generated from a Carla Simulator and whether a dynamic object ( pedestrian, vehicle, etc. ) was within a distance threshold or not.

The individual radar points of single training sample features contain below metadata -






Altitude angle in radians.



Azimuth angle in radians.



Distance in meters.



Velocity towards the sensor.

πŸ“ Files

Following files are available in the resources section:

  • data.npz - ( 5k training and 3k testing samples ) This npy file contains both the training set and testing set. You can use the NumPy function np.load to read the file

  • sample_submission.csv - It contains the random labels for testing data which is used for testing purposes and making sure that your submission format is correct.

πŸ“¨ How to submit

Make your first submission using the starter kit πŸš€

  1. Save the submission.csv in the assets directory. The name of the above file should be submission.csv.

  2. Inside a submission directory, put the .ipynb notebook from which you trained the model and made inference and save it as notebook.ipynb.

  3. Zip the submission directory

  4. Overall, this is what your submission directory should look like


Make your first submission here. πŸš€

πŸ–Š Evaluation Criteria

The evaluation metrics for this competition is F1 Score ( Primary Score ) and Accuracy ( Secondary Score )

πŸ“± Contact

If you have any questions, consider posting on the Blitz 11 Community Discussion board, or join the party on our Discord!


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[Getting Started Notebook] Obstacle Prediction
27 days ago