Consistent image output

[hadim]

Checklist:

• Was this PR discussed in a issue? It is recommended to first discuss a new feature into a GitHub issue before opening a PR.
• Add tests to cover the fixed bug(s) or the new introduced feature(s) (if appropriate).
• Update the API documentation is a new function is added or an existing one is deleted.
• Added a news entry.
  • copy news/TEMPLATE.rst to news/my-feature-or-branch.rst) and edit it.

---

[codecov]

Codecov Report

Merging #179 (d4ffa75) into main (b978fc5) will increase coverage by 0.01%.
The diff coverage is 93.93%.

@@            Coverage Diff             @@
##             main     #179      +/-   ##
==========================================
+ Coverage   91.01%   91.02%   +0.01%     
==========================================
  Files          48       48              
  Lines        3785     3801      +16     
==========================================
+ Hits         3445     3460      +15     
- Misses        340      341       +1     

Flag	Coverage Δ
unittests	91.02% <93.93%> (+0.01%)	⬆️

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

Impacted Files	Coverage Δ
datamol/viz/utils.py	87.17% <91.30%> (+4.82%)	⬆️
datamol/viz/_lasso_highlight.py	90.82% <100.00%> (+0.19%)	⬆️

... and 1 file with indirect coverage changes

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[hadim]

@cwognum @dessygil FYI I noticed a few mistakes we've made in the previous PR:

• The IPython lib was imported globally while we don't want that lib to be a direct dep of datamol but an optional dep.
• The returned image object was inconsistent with datamol.to_image and rdkit. So, I modified the logic to match it to rdkit.

Nothing to do on your side and it's mostly FYI here.

[hadim]

Merging here as I don't think the failing osx test is legit here. (will fix in main if needed).