AI Blitz #7: Completed #educational Weight: 10.0
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## 🕵️ Introduction

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

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

💾 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.

## 📁 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.

## 🚀 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 🚀 !!

## 🖊 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.