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AI Blitz #7: Completed #educational Weight: 10.0
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🚨 Update in Test Dataset | πŸ“₯ Reminder to Download

πŸ•΅οΈ Introduction

Our mission to Mars is about to start πŸ›Έ but before we can take off we must resolve a mix-up.

Someone has mishandled the labeling of two Mars rover projects β€” Curiosity and Perseverance β€” we must classify them correctly.

Click here to access the starter-kit and avert the emergency!

 

πŸ’Ύ Dataset

The given dataset contains images of two different rovers i.e. Curiosity and Perseverance of size 265*256 in `jpg` format. The images in train.zip and val.zip  have their labels i.e. which rover it is in train.csv and val.csv. The labels for the images in test.zip needs to be predicted. 

πŸ“ Files

Following files are available in the resources section:

  • train.zip - (40000 samples) This zip file contains rover images with images name corresponding to ImageID column of train.csv
  • train.csv - (40000 samples) This csv file contains the ImageID column corresponding to train.zip and label column as the name of rover.
  • val.zip - (4000 samples) This zip file contains rover images with images name corresponding to ImageID column of val.csv
  • val.csv - (4000 samples) This csv file contains the ImageID column corresponding to val.zip and label column as the name of rover.
  • test.zip - (10000 samples) This zip file contains rover images which will be used to evaluate the performance of the model.

πŸš€ Submission

  • Prepare a CSV containing ImageID column corresponding to test.zip and label column as rover name.
  • The name of the above file should be submission.csv.
  • Sample submission format available at sample_submission.csv in the resources section.

Make your first submission here πŸš€ !!

πŸ–Š Evaluation Criteria

During evaluation F1 score is used as Primary Score and Accuracy Score as Secondary Score will be used to test the efficiency of the model.

πŸ”— Links

πŸ“± Contact

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