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Back to AI Blitz #6
Challenge: Completed #educational Weight: 10.0
By  AIcrowd 
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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

Let’s keep the first puzzle simple, shall we? Given a set of images, can you identify which side (white or black) has the least number of chess pieces on the board?

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

🚀 Explainer Video

💾 Dataset

The given dataset contains images of chess board with pieces of both black and white. Each image is of size 254 * 254 pixels. A CSV is also provided containing the image id and the color which has least number of peices on the board.

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 has least number of pieces.

📁 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 labels.
  • train.zip - (40000 samples) This zip file contains images corresponding to the first column of train.csv..
  • val.csv - (4000 samples) This csv file contains ImageID column which corresponds to val.zip and labels.
  • val.zip - (4000 samples) This zip file contains images corresponding to the first column of val.csv.
  • test.zip - (10000 samples) This zip file contains testing images that will be used for actual evaluation for the leaderboard score.

🚀 Submission

  • Prepare a CSV containing two columns, one is ImageID which corresponds to the images in test.zip and labels as predicted value denoting if the white or black has the least amount of pieces.
  • 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.

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