TXTOCR

[Getting Started Notebook] TXTOCR Challange

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Getting Started Code for TXTOCR Challenge on AIcrowd¶

Author : Gauransh Kumar, Shubhamai¶

Installing AIcrowd CLI and Authentication¶

This will help in easy downloading dataset and submitting directly via this notebook. Do not forget to participate and accept the rules before ruinning this notebook.

In [1]:

!pip install aicrowd-cli

WARNING: Ignoring invalid distribution -umpy (/home/gauransh/anaconda3/lib/python3.8/site-packages)
WARNING: Ignoring invalid distribution -umpy (/home/gauransh/anaconda3/lib/python3.8/site-packages)
Requirement already satisfied: aicrowd-cli in /home/gauransh/anaconda3/lib/python3.8/site-packages (0.1.10)
Requirement already satisfied: GitPython==3.1.18 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from aicrowd-cli) (3.1.18)
Requirement already satisfied: click<8,>=7.1.2 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from aicrowd-cli) (7.1.2)
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Requirement already satisfied: certifi>=2017.4.17 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from requests<3,>=2.25.1->aicrowd-cli) (2021.10.8)
Requirement already satisfied: pygments<3.0.0,>=2.6.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from rich<11,>=10.0.0->aicrowd-cli) (2.10.0)
Requirement already satisfied: colorama<0.5.0,>=0.4.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from rich<11,>=10.0.0->aicrowd-cli) (0.4.4)
Requirement already satisfied: commonmark<0.10.0,>=0.9.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from rich<11,>=10.0.0->aicrowd-cli) (0.9.1)
WARNING: Ignoring invalid distribution -umpy (/home/gauransh/anaconda3/lib/python3.8/site-packages)
WARNING: Ignoring invalid distribution -umpy (/home/gauransh/anaconda3/lib/python3.8/site-packages)
WARNING: Ignoring invalid distribution -umpy (/home/gauransh/anaconda3/lib/python3.8/site-packages)
WARNING: Ignoring invalid distribution -umpy (/home/gauransh/anaconda3/lib/python3.8/site-packages)

In [2]:

%load_ext aicrowd.magic

In [3]:

!aicrowd login

Please login here: https://api.aicrowd.com/auth/v-sfYy8HASBa_y15PJU4tC5wnrmYZiM2KwZGh88mvZ4
Opening in existing browser session.
API Key valid
Saved API Key successfully!

Download Data¶

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

In [4]:

!aicrowd dataset download -c txtocr >/dev/null

sample_submission.csv: 100%|██████████████████| 109k/109k [00:00<00:00, 138kB/s]
val.zip:  17%|█████▏                        | 1.05M/6.07M [00:01<00:07, 701kB/s]
val.zip: 100%|█████████████████████████████| 6.07M/6.07M [00:02<00:00, 2.36MB/s]
val.csv:   0%|                                      | 0.00/71.6k [00:00<?, ?B/s]
train.zip:   2%|▍                           | 1.05M/60.7M [00:01<01:33, 640kB/s]
train.zip:   3%|▉                          | 2.10M/60.7M [00:01<00:46, 1.25MB/s]
val.csv: 100%|██████████████████████████████| 71.6k/71.6k [00:00<00:00, 150kB/s]

train.zip:   7%|█▊                         | 4.19M/60.7M [00:02<00:21, 2.59MB/s]
train.zip:   9%|██▎                        | 5.24M/60.7M [00:02<00:17, 3.23MB/s]
train.zip:  10%|██▊                        | 6.29M/60.7M [00:02<00:18, 2.90MB/s]
test.zip:   0%|                                     | 0.00/15.1M [00:00<?, ?B/s]

train.csv:   0%|                                     | 0.00/756k [00:00<?, ?B/s]
train.zip:  16%|████▎                       | 9.44M/60.7M [00:14<02:09, 396kB/s]
test.zip:   7%|██                           | 1.05M/15.1M [00:02<00:34, 412kB/s]
train.zip:  19%|█████▎                      | 11.5M/60.7M [00:15<01:12, 676kB/s]

train.csv: 100%|██████████████████████████████| 756k/756k [00:01<00:00, 429kB/s]
test.zip:  14%|████                         | 2.10M/15.1M [00:02<00:15, 854kB/s]
test.zip:  21%|█████▊                      | 3.15M/15.1M [00:03<00:11, 1.06MB/s]
train.zip:  24%|██████▌                    | 14.7M/60.7M [00:16<00:37, 1.23MB/s]
train.zip:  26%|███████▎                    | 15.7M/60.7M [00:17<00:45, 997kB/s]
test.zip:  28%|████████                     | 4.19M/15.1M [00:06<00:16, 664kB/s]
test.zip:  35%|██████████                   | 5.24M/15.1M [00:06<00:11, 870kB/s]
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test.zip:  76%|█████████████████████▎      | 11.5M/15.1M [00:08<00:01, 2.85MB/s]
test.zip:  83%|███████████████████████▎    | 12.6M/15.1M [00:08<00:00, 3.03MB/s]
test.zip:  90%|█████████████████████████▏  | 13.6M/15.1M [00:08<00:00, 3.04MB/s]
test.zip:  97%|███████████████████████████▏| 14.7M/15.1M [00:09<00:00, 3.04MB/s]
test.zip: 100%|████████████████████████████| 15.1M/15.1M [00:09<00:00, 1.65MB/s]

train.zip:  47%|████████████▌              | 28.3M/60.7M [00:22<00:09, 3.43MB/s]
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train.zip:  66%|█████████████████▋         | 39.8M/60.7M [00:30<00:12, 1.65MB/s]
train.zip:  67%|██████████████████▏        | 40.9M/60.7M [00:30<00:10, 1.94MB/s]
train.zip:  69%|██████████████████▋        | 41.9M/60.7M [00:30<00:09, 1.95MB/s]
train.zip:  71%|███████████████████▏       | 43.0M/60.7M [00:31<00:08, 2.09MB/s]
train.zip:  73%|███████████████████▌       | 44.0M/60.7M [00:32<00:08, 1.95MB/s]
train.zip:  76%|████████████████████▌      | 46.1M/60.7M [00:32<00:05, 2.60MB/s]
train.zip:  78%|████████████████████▉      | 47.2M/60.7M [00:32<00:05, 2.58MB/s]
train.zip:  80%|█████████████████████▍     | 48.2M/60.7M [00:33<00:04, 2.57MB/s]
train.zip:  81%|██████████████████████▋     | 49.3M/60.7M [00:38<00:18, 604kB/s]
train.zip:  83%|███████████████████████▏    | 50.3M/60.7M [00:42<00:23, 433kB/s]
train.zip:  85%|███████████████████████▋    | 51.4M/60.7M [00:45<00:21, 437kB/s]
train.zip:  86%|████████████████████████▏   | 52.4M/60.7M [00:46<00:16, 488kB/s]
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train.zip:  92%|█████████████████████████▋  | 55.6M/60.7M [00:57<00:18, 276kB/s]
train.zip:  93%|██████████████████████████▏ | 56.6M/60.7M [00:58<00:11, 350kB/s]
train.zip:  95%|██████████████████████████▌ | 57.7M/60.7M [00:59<00:06, 443kB/s]
train.zip:  97%|███████████████████████████ | 58.7M/60.7M [01:00<00:03, 566kB/s]
train.zip:  99%|███████████████████████████▌| 59.8M/60.7M [01:01<00:01, 707kB/s]
train.zip: 100%|████████████████████████████| 60.7M/60.7M [01:01<00:00, 985kB/s]

In [5]:

!rm -rf data
!mkdir data

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

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

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