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AI Blitz #6

[Baseline] Chess Transcription

A getting started code for the Chess Transcription challenge.

ashivani

AIcrowd-Logo

Getting Started Code for Chess Transcription Challenge on AIcrowd

Author : Shubhamai

Download Necessary Packages 📚

In this baseline we are going to use FastAI as our main library to train out model and making & submitting predictions

In [1]:
!pip install --upgrade fastai git+https://gitlab.aicrowd.com/yoogottamk/aicrowd-cli.git >/dev/null
%load_ext aicrowd.magic

  Running command git clone -q https://gitlab.aicrowd.com/yoogottamk/aicrowd-cli.git /tmp/pip-req-build-ows7ja7c

Download Data

The first step is to download out train test data. We will be training a model on the train data and make predictions on test data. We submit our predictions.

In [2]:
API_KEY = ''  #Please enter your API Key [https://www.aicrowd.com/participants/me]
%aicrowd login --api-key $API_KEY

Verifying API Key...
API Key valid
Saved API Key successfully!
In [3]:
%aicrowd dataset download --challenge chess-transcription -j 3
In [4]:
!rm -rf data
!mkdir data

!unzip train.zip  -d data/ 
!unzip val.zip -d data/ 
!unzip test.zip  -d data/ 

!mv train.csv data/train.csv
!mv val.csv data/val.csv
!mv sample_submission.csv data/sample_submission.csv

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Import packages

In [5]:
import random
import string
import pandas as pd

Load Data

  • We use pandas 🐼 library to load our data.
  • Pandas loads the data into dataframes and facilitates us to analyse the data.
  • Learn more about it here 🤓
In [6]:
sample_submission = pd.read_csv("data/sample_submission.csv")
sample_submission
Out[6]:
VideoID label
0 0 b6h2 h8e7 f7a5 g1d1 a2h8 e3a5
1 1 b4d2 a1h6 c8b7 d5h3 a1b2 b7e5
2 2 h3b4 b7e3 f5f3 f8d2 g7f2 c1b6
3 3 f2h1 d6e6 g4e4 f3b1 f5h8 a6c5
4 4 d7e5 c6d3 f4g6 a6a5 e1c4 f5h1 h2f8 h8e5 f3g4 c1b5
... ... ...
1995 1995 c4f8 b2f1 g1g2 g3g3 c5f1 g8h2 c7b2 d1a3 a8a5 e8b4
1996 1996 c8e2 d1h1 b5g3 c7f6 a6a5 e3g6 g3c4 b4a4 h4b5 f6a4
1997 1997 g4e8 f8c7 c3e8 b1e5 a3h1 b4b3 e6g8 f7e1 e7d6
1998 1998 h6b5 h6d5 c1h7 b6e8 d7f5
1999 1999 d2h5 h8f6 a4f3 b8d3 g7b3 d3e3 f4g5 f8f3 g7g8 e6a3

2000 rows × 2 columns

Creating Random Submission 👀

In below cell, we are going to create a random labels to submit our predictions.

In [7]:
predictions = []


for n in range(0, sample_submission.shape[0]):

  moves = []

  no_of_moves = random.randint(5, 10)

  for i in range(no_of_moves):

      # Crating random location of piece
      previous_location = random.choice(string.ascii_lowercase[:8])+random.choice(string.digits[1:9])
      new_location = random.choice(string.ascii_lowercase[:8])+random.choice(string.digits[1:9])

      prediction = ''.join(previous_location+new_location)

      moves.append(prediction)

  predictions.append(" ".join(moves))
In [8]:
sample_submission['label'] = predictions
sample_submission
Out[8]:
VideoID label
0 0 h6f8 e7e7 g2e4 e7h3 h7a5 f1g5 e1g8 h3c7 a2a2
1 1 d3g1 f3f3 g3a3 a7g7 a5e6 b5c3 h6h7 f4e4
2 2 d2g7 e8f4 c5g1 e2g8 e4c3
3 3 b8f4 h3a7 f1h8 d8d5 b5g6 c7e8 h5e4 b5d6 d1g6
4 4 h8f8 a4g2 h1d2 f1b3 g8b4 b7f8
... ... ...
1995 1995 g1e6 d6a8 c5h8 b7g2 e3a3 f5b6
1996 1996 d1f2 d2f7 c3b3 f6e3 b6a3 e6f8 a4d4 g2b1 b2g4 a5d4
1997 1997 e8a6 f7f6 a8h1 h6c2 a4h1
1998 1998 c1h7 h2g4 h3g7 d5h7 e4e7 e7b6 d8g5 e3d7
1999 1999 a8e8 e8e4 c6e2 c7f3 f1e1 b8g3 f3g5

2000 rows × 2 columns

Save the prediction to csv

In [9]:
sample_submission.to_csv("submission.csv", index=False)

To download the generated csv in colab run the below command

In [10]:
try:
    from google.colab import files
    files.download('submission.csv') 
except:
    print("Option Only avilable in Google Colab")

Well Done! 👍 We are all set to make a submission and see your name on leaderborad. Let navigate to challenge page and make one.

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