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Round 1(Validation Set): Completed Round 2(Test Set): Completed #supervised_learning

TJEDC - Tom and Jerry Emotion Detection Challenge

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🕵️ Introduction

We all remember Tom and Jerry and the immense happiness their misadventures brought in our lives. Now you are required to build a model that detects emotions of the characters in a video frame from our most-loved show. Build a model that detects the emotion of the character present in each frame.

💾 Dataset

The dataset consists of two parameters—

  • Frame_ID that indicates the frame of the video
  • Emotion that categorizes the emotion of the primary character into different labels: angry(0), happy(1), sad(2), surprised(3), or Unknown(4). The number in brackets is the encoding of the emotion.

📁 Files

  • train.csv - (1941 samples) File that should be used for training by the user.
  • test.csv - (275 samples) File that will be used for actual evaluation for the leaderboard score.Note:- This is not the final test set. -train.zip - Contains the images corresponding to train.csv file -test.zip - Contains the images corresponding to test.csv file

🚀 Submission

  • Prepare a csv containing header as emotion and predicted emotion as 0/1/2/3/4 with name as submission.csv.
  • Sample submission format available at ./data/sample_submission.csv.

Make your first submission here 🚀 !!

🖊 Evaluation Criteria

During evaluation F1 score and Accuracy will be used to test the efficiency of the model

📱 Contact

📚 References

  • https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html
  • https://www.analyticsvidhya.com/blog/2019/10/building-image-classification-models-cnn-pytorch/

Participants

Leaderboard

01 Anonomas 1.000
02 2019202010_Ayush 1.000
03 2019900057_mowlanica 1.000
04 2019201032_jyoti 1.000
05 2019201061_madhvi 1.000