TXTOCR
[Getting Started Notebook] TXTOCR Challange
This is a Baseline Code to get you started with the challenge.
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) Requirement already satisfied: toml<1,>=0.10.2 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from aicrowd-cli) (0.10.2) Requirement already satisfied: rich<11,>=10.0.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from aicrowd-cli) (10.15.2) Requirement already satisfied: requests<3,>=2.25.1 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from aicrowd-cli) (2.26.0) Requirement already satisfied: pyzmq==22.1.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from aicrowd-cli) (22.1.0) Requirement already satisfied: tqdm<5,>=4.56.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from aicrowd-cli) (4.60.0) Requirement already satisfied: requests-toolbelt<1,>=0.9.1 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from aicrowd-cli) (0.9.1) Requirement already satisfied: gitdb<5,>=4.0.1 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from GitPython==3.1.18->aicrowd-cli) (4.0.9) Requirement already satisfied: smmap<6,>=3.0.1 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from gitdb<5,>=4.0.1->GitPython==3.1.18->aicrowd-cli) (5.0.0) Requirement already satisfied: charset-normalizer~=2.0.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from requests<3,>=2.25.1->aicrowd-cli) (2.0.0) Requirement already satisfied: idna<4,>=2.5 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from requests<3,>=2.25.1->aicrowd-cli) (3.1) Requirement already satisfied: urllib3<1.27,>=1.21.1 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from requests<3,>=2.25.1->aicrowd-cli) (1.26.6) 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] test.zip: 48%|█████████████▌ | 7.34M/15.1M [00:07<00:05, 1.53MB/s] test.zip: 55%|███████████████▌ | 8.39M/15.1M [00:07<00:03, 2.01MB/s] test.zip: 69%|███████████████████▍ | 10.5M/15.1M [00:07<00:01, 2.90MB/s] 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] train.zip: 48%|█████████████ | 29.4M/60.7M [00:22<00:08, 3.79MB/s] train.zip: 50%|█████████████▌ | 30.4M/60.7M [00:22<00:07, 4.25MB/s] train.zip: 52%|█████████████▉ | 31.5M/60.7M [00:22<00:06, 4.50MB/s] train.zip: 54%|██████████████▍ | 32.5M/60.7M [00:22<00:05, 4.77MB/s] train.zip: 55%|██████████████▉ | 33.6M/60.7M [00:23<00:07, 3.43MB/s] train.zip: 57%|███████████████▉ | 34.6M/60.7M [00:28<00:39, 657kB/s] train.zip: 59%|████████████████▍ | 35.7M/60.7M [00:28<00:29, 859kB/s] train.zip: 60%|████████████████▎ | 36.7M/60.7M [00:28<00:22, 1.09MB/s] train.zip: 62%|████████████████▊ | 37.7M/60.7M [00:29<00:19, 1.20MB/s] train.zip: 64%|█████████████████▎ | 38.8M/60.7M [00:29<00:13, 1.58MB/s] 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] train.zip: 88%|████████████████████████▋ | 53.5M/60.7M [00:47<00:12, 561kB/s] train.zip: 90%|█████████████████████████▏ | 54.5M/60.7M [00:48<00:09, 661kB/s] 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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Importing Libraries¶
In [6]:
!apt update
!apt install tesseract-ocr
!apt install libtesseract-dev
!pip install --upgrade fastai
!pip install pytesseract
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: fastai in /home/gauransh/anaconda3/lib/python3.8/site-packages (1.0.61) Collecting fastai Downloading fastai-2.5.3-py3-none-any.whl (189 kB) |████████████████████████████████| 189 kB 1.2 MB/s eta 0:00:01 Requirement already satisfied: torchvision>=0.8.2 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (0.10.0a0) Requirement already satisfied: requests in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (2.26.0) Requirement already satisfied: scipy in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (1.6.2) Requirement already satisfied: spacy<4 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (3.2.0) Requirement already satisfied: pyyaml in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (5.1) Requirement already satisfied: fastcore<1.4,>=1.3.22 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (1.3.26) Requirement already satisfied: pip in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (21.2.4) Requirement already satisfied: fastdownload<2,>=0.0.5 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (0.0.5) Requirement already satisfied: pandas in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (1.3.2) Requirement already satisfied: scikit-learn in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (0.24.2) Requirement already satisfied: fastprogress>=0.2.4 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (1.0.0) Requirement already satisfied: pillow>6.0.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (8.3.1) Requirement already satisfied: packaging in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (21.3) Requirement already satisfied: torch<1.11,>=1.7.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (1.9.0) Requirement already satisfied: matplotlib in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastai) (3.4.3) Requirement already satisfied: numpy in /home/gauransh/anaconda3/lib/python3.8/site-packages (from fastprogress>=0.2.4->fastai) (1.22.2) Requirement already satisfied: langcodes<4.0.0,>=3.2.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from spacy<4->fastai) (3.3.0) Requirement already satisfied: jinja2 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from spacy<4->fastai) (2.11.3) Requirement already satisfied: thinc<8.1.0,>=8.0.12 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from spacy<4->fastai) (8.0.12) Requirement already satisfied: spacy-legacy<3.1.0,>=3.0.8 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from spacy<4->fastai) (3.0.8) Requirement already satisfied: setuptools in /home/gauransh/anaconda3/lib/python3.8/site-packages (from spacy<4->fastai) (57.4.0) Requirement already satisfied: cymem<2.1.0,>=2.0.2 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from spacy<4->fastai) (2.0.6) Requirement already satisfied: pathy>=0.3.5 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from spacy<4->fastai) (0.6.1) Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from spacy<4->fastai) (1.0.6) Requirement already satisfied: blis<0.8.0,>=0.4.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from spacy<4->fastai) (0.7.5) Requirement already satisfied: catalogue<2.1.0,>=2.0.6 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from spacy<4->fastai) (2.0.6) Requirement already satisfied: spacy-loggers<2.0.0,>=1.0.0 in /home/gauransh/anaconda3/lib/python3.8/site-packages (from spacy<4->fastai) (1.0.1) 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In [7]:
import pandas as pd
from fastai import *
from fastai.vision import *
from fastai.vision.data import *
from fastai.vision.all import *
import pytesseract
from tqdm.notebook import tqdm
In [8]:
train_df = pd.read_csv("data/train.csv")
val_df = pd.read_csv("data/val.csv")
train_df.head()
Out[8]:
image_id | label | |
---|---|---|
0 | 0 | inventory |
1 | 1 | directories letter |
2 | 2 | growth splints |
3 | 3 | kicks |
4 | 4 | seventies |
In [9]:
# Adding full image path
train_df['image_id'] = "data/train/"+train_df['image_id'].astype(str)+".png"
train_df
Out[9]:
image_id | label | |
---|---|---|
0 | data/train/0.png | inventory |
1 | data/train/1.png | directories letter |
2 | data/train/2.png | growth splints |
3 | data/train/3.png | kicks |
4 | data/train/4.png | seventies |
... | ... | ... |
39995 | data/train/39995.png | output dioxide |
39996 | data/train/39996.png | cruises fellow |
39997 | data/train/39997.png | turn |
39998 | data/train/39998.png | drift search |
39999 | data/train/39999.png | handler |
40000 rows × 2 columns
Making Predictions¶
Instead of training our model on training set and then making predictions, we are going to directly make predictions by using pytesseract
,an optical character recognition tool for python
In [10]:
test_imgs_paths = os.listdir("data/test")
predictions = []
for test_img_path in tqdm(test_imgs_paths):
label = pytesseract.image_to_string(Image.open("data/test/"+test_img_path))
#Removing garbage characters
label = label.replace("\x0c","")
label = label.replace("\n","")
predictions.append(label)
In [11]:
# Making our testing dataframe
test_imgs_paths = [int(i.split(".")[0]) for i in test_imgs_paths]
test_df = pd.DataFrame(test_imgs_paths, columns=["image_id"])
test_df['label'] = predictions
test_df
Out[11]:
image_id | label | |
---|---|---|
0 | 1001 | CANALS |
1 | 1099 | shell |
2 | 2230 | Poca |
3 | 3866 | |
4 | 9565 | |
... | ... | ... |
9995 | 5519 | lock formul |
9996 | 2842 | colds |
9997 | 9632 | Srl mete |
9998 | 6344 | mixture nozzles |
9999 | 893 | reductions |
10000 rows × 2 columns
In [14]:
# Saving predictions
!rm -rf assets
!mkdir assets
test_df.to_csv(os.path.join("assets", "submission.csv"), index=False)
Submitting our Predictions¶
In [15]:
!aicrowd submission create -c txtocr -f assets/submission.csv
submission.csv ━━━━━━━━━━━━━━━━━━ 100.0% • 138.5/136.9 KB • 166.6 kB/s • 0:00:00[36m0:00:01[36m0:00:01:01 ╭─────────────────────────╮ │ Successfully submitted! │ ╰─────────────────────────╯ Important links ┌──────────────────┬───────────────────────────────────────────────────────────────────────────────────────────────┐ │ This submission │ https://www.aicrowd.com/challenges/ai-blitz-5/problems/txtocr/submissions/176731 │ │ │ │ │ All submissions │ https://www.aicrowd.com/challenges/ai-blitz-5/problems/txtocr/submissions?my_submissions=true │ │ │ │ │ Leaderboard │ https://www.aicrowd.com/challenges/ai-blitz-5/problems/txtocr/leaderboards │ │ │ │ │ Discussion forum │ https://discourse.aicrowd.com/c/ai-blitz-5 │ │ │ │ │ Challenge page │ https://www.aicrowd.com/challenges/ai-blitz-5/problems/txtocr │ └──────────────────┴───────────────────────────────────────────────────────────────────────────────────────────────┘ {'submission_id': 176731, 'created_at': '2022-03-14T12:19:22.914Z'}
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