feat: Split DocArtefacts into subsets and updated its class mapping

[fg-mindee]

This PR introduces the following modifications:

• updates the URL of the zip which now contains a train and val subset
• updates the labels target: rather than being a list of string, it will return a numpy.array of class indices
• updates the docstring of the class

Any feedback is welcome!

[charlesmindee]

Thanks!

[SiddhantBahuguna]

1. Should we add the collate function here?
2. Also, we need to obtain absolute box coordinates. Right now we use relative ones.

[fg-mindee]

1. Should we add the collate function here?

Oh yeah, you're right, I'll change this

2. Also, we need to obtain absolute box coordinates. Right now we use relative ones.

But that's OK, most of our datasets are in relative coords, and we convert it if not.

[fg-mindee]

For the collate function, actually I just checked and it's already working @SiddhantBahuguna :

from doctr.datasets import DocArtefacts
from doctr.datasets import DataLoader

ds = DocArtefacts(train=True, download=True)
train_loader = DataLoader(ds, batch_size=2)
train_iter = iter(train_loader)
x, targets = next(train_iter)

And the results look satisfactory to me:

# Check shape of input
print(x.shape)

TensorShape([2, 1024, 800, 3])

print(len(targets))
print(targets[0])

2
{'boxes': array([[0.94625   , 0.39746094, 0.99375   , 0.4345703 ],
       [0.38375   , 0.5957031 , 0.4275    , 0.6269531 ],
       [0.41875   , 0.28027344, 0.52875   , 0.36621094],
       [0.39625   , 0.36816406, 0.6675    , 0.57910156],
       [0.26625   , 0.5332031 , 0.2975    , 0.5576172 ],
       [0.20125   , 0.1953125 , 0.2575    , 0.23925781],
       [0.105     , 0.00976562, 0.17125   , 0.06152344],
       [0.15875   , 0.078125  , 0.2425    , 0.14355469],
       [0.10125   , 0.5292969 , 0.25875   , 0.6796875 ],
       [0.73625   , 0.7138672 , 0.85375   , 0.8261719 ]], dtype=float32), 'labels': array([1, 2, 1, 1, 1, 1, 3, 3, 4, 4])}

[codecov]

Codecov Report

Merging #601 (bd74611) into main (f97e92b) will increase coverage by 0.00%.
The diff coverage is 100.00%.

❗ Current head bd74611 differs from pull request most recent head 0c7c672. Consider uploading reports for the commit 0c7c672 to get more accurate results

@@           Coverage Diff           @@
##             main     #601   +/-   ##
=======================================
  Coverage   96.06%   96.06%           
=======================================
  Files         110      110           
  Lines        4265     4269    +4     
=======================================
+ Hits         4097     4101    +4     
  Misses        168      168           

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Impacted Files	Coverage Δ
doctr/datasets/doc_artefacts.py	94.11% <100.00%> (+0.78%)	⬆️

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[SiddhantBahuguna]

The output is following our expectations. Collate problem is resolved now. Thanks:)