Challenge: Completed #educational Weight: 30.0
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🛠 Contribute: Found a typo? Or any other change in the description that you would like to see? Please consider sending us a pull request in the public repo of the challenge here.

🕵️ Introduction

World-class chess players are known for anticipating the moves of the opposition. They have the foresight to see various permutations of moving a chess piece and its implication long before it happens. That’s what makes them the best!

Are you up for a similar challenge? Can you create a model that will predict the winner a chess game? With inputs of few moves before checkmate, can you predict which side will win the match - white or black?

Your model should be able to predict the winner of the game few moves before the checkmate!

Understand with code! Here is getting started code for you.😄

💾 Dataset

The given dataset contains images of chess board with pieces of both black and white. Each image is of size 256 * 256. A CSV is also provided containing the ImageID and label as the color which wins after few moves before checkmate. The CSV also contains turn column which represents which side ( black/white ) has the turn to move it's pieces.

The dataset is divided into train and validation set, each containing a zip file and csv corresponding to it. For evaluation you are provided with the test.zip which contain the images for which you need to find which color wins.

📁 Files

Following files are available in the resources section:

• train.csv - (40000 samples) This csv file contains ImageID column which corresponds to train.zip and turn & label column.
• train.zip - (40000 samples) This zip file contains image corresponding to the first column of train.csv.
• val.csv - (4000 samples) This csv file contains ImageID column which corresponds to val.zip and turn & label column.
• val.zip - (4000 samples) This zip file contains image corresponding to the first column of val.csv.
• test.csv - (10000 samples) This csv file contains ImageID column which corresponds to test.zip and turn column.
• test.zip - (10000 samples) This zip file contains testing images that will be used for actual evaluation for the leaderboard score. The turn column for this set is available in test.csv

🚀 Submission

• Prepare a CSV containing two columns, one is ImageID which corresponds to the images in test.zip and label as predicted value denoting if the white or black won the match.
• Sample submission format available at sample_submission.csv in the resorces 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.