add object detection prediction example and fix batch

[edgarriba]

What does this PR do?

Add object detection example #277

Before submitting

• Was this discussed/approved via a Github issue? (no need for typos and docs improvements)
• Did you read the contributor guideline, Pull Request section?
• Did you make sure your PR does only one thing, instead of bundling different changes together?
• Did you make sure to update the documentation with your changes?
• Did you write any new necessary tests? [not needed for typos/docs]
• Did you verify new and existing tests pass locally with your changes?
• If you made a notable change (that affects users), did you update the CHANGELOG?

PR review

• Is this pull request ready for review? (if not, please submit in draft mode)

Anyone in the community is free to review the PR once the tests have passed.
If we didn't discuss your PR in Github issues there's a high chance it will not be merged.

Did you have fun?

Make sure you had fun coding 🙃

[codecov]

Codecov Report

Merging #283 (95aed15) into master (1380c53) will increase coverage by 5.73%.
The diff coverage is 100.00%.

❗ Current head 95aed15 differs from pull request most recent head 2dc2410. Consider uploading reports for the commit 2dc2410 to get more accurate results

@@            Coverage Diff             @@
##           master     #283      +/-   ##
==========================================
+ Coverage   82.48%   88.22%   +5.73%     
==========================================
  Files          74       74              
  Lines        3575     3576       +1     
==========================================
+ Hits         2949     3155     +206     
+ Misses        626      421     -205     

Flag	Coverage Δ
unittests	88.22% <100.00%> (+5.73%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
flash/data/batch.py	80.62% <100.00%> (+4.24%)	⬆️
flash/vision/segmentation/data.py	88.63% <0.00%> (ø)
flash/data/data_pipeline.py	93.05% <0.00%> (+0.69%)	⬆️
flash/vision/classification/data.py	93.40% <0.00%> (+1.09%)	⬆️
flash/data/properties.py	83.11% <0.00%> (+1.29%)	⬆️
flash/vision/backbones.py	77.66% <0.00%> (+1.94%)	⬆️
flash/data/data_module.py	92.34% <0.00%> (+2.39%)	⬆️
flash/data/data_source.py	96.72% <0.00%> (+2.41%)	⬆️
flash/core/trainer.py	87.17% <0.00%> (+5.12%)	⬆️
... and 15 more

---

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 1380c53...2dc2410. Read the comment docs.

[tchaton]

LGTM !

[ethanwharris]

LGTM

[ethanwharris]

Any reason not to return a list here? (like [batch])