Adding doctest for `object-detection` pipeline.
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_The documentation is not available anymore as the PR was closed or merged._<|||||>> I still think the `candidate_labels` argument/naming is not very aligned with zero-shot object detection but the PR looks good to me otherwise.

Here it's just an alias.
I'm really not sure I understand how it could be a bad name.

The content end up being within `label` section of the output, so saying they are `labels` doesn't seem all that shocking to me.
The fact that they are `candidate` is because there is no guarantee that you will be able to detect them.

Overall I find `candidate_labels` not that bad.

Why I think `text_queries` is not the best choice:
- It is not aligned with other `zero-shot` pipelines
- `text_queries` implies `text` but you're not looking for text within an image but readers might understand this:
   ```pipe(image, text_query="Restaurant")``` Are we looking for places where the text restaurant is written ?
- `queries` implies asking for information so I'm somehow expecting to always receive something, I feel it conveys less well the idea of "potentiality" than `canddiate`.

The main counterargument in the original PR was that `candidate_labels` was using `hypothesis_template`. I feel like it's not really a strong stance, since `hypothesis_template` isn't really meant to be used so much (it's kind of  a power user tool). Even then, I don't think just because there is no `hypothesis_template` should prevent us from using the same name, if the name is readable, and serves the same purpose, then it's a good name, the rest is implementation detail imo.

Happy to hear your thoughts on why you think it fits better.<|||||>
> Here it's just an alias. I'm really not sure I understand how it could be a bad name.
> 
> Happy to hear your thoughts on why you think it fits better.

@Narsil my main concern is that zero-shot-classification pipeline selects one of the `candidate_labels` to assign a final class / label to the image, whereas zero-shot-object-detection queries the image for each query and might find instances of all query objects. It'd be less confusing to users if we add a better docstring example -> using an image where both candidate_labels=["head", "bird"] are detected instead of just "bird".
<|||||>> @Narsil my main concern is that zero-shot-classification pipeline selects one of the candidate_labels to assign a final class / label to the image, whereas zero-shot-object-detection queries the image for each query and might find instances of all query objects. It'd be less confusing to users if we add a better docstring example -> using an image where both candidate_labels=["head", "bird"] are detected instead of just "bird".

Oh, but no, `zero-shot-classification` does multi label classification actually. The default is to normalize scores across labels, but it's not mandatory, by default the models can handle multiple label just fine (results tend to be more noisy though).

https://huggingface.co/facebook/bart-large-mnli?candidateLabels=space+%26+cosmos%2C+scientific+discovery%2C+microbiology%2C+robots%2C+archeology&multiClass=true&text=A+new+model+offers+an+explanation+for+how+the+Galilean+satellites+formed+around+the+solar+system%E2%80%99s+largest+world.+Konstantin+Batygin+did+not+set+out+to+solve+one+of+the+solar+system%E2%80%99s+most+puzzling+mysteries+when+he+went+for+a+run+up+a+hill+in+Nice%2C+France.+Dr.+Batygin%2C+a+Caltech+researcher%2C+best+known+for+his+contributions+to+the+search+for+the+solar+system%E2%80%99s+missing+%E2%80%9CPlanet+Nine%2C%E2%80%9D+spotted+a+beer+bottle.+At+a+steep%2C+20+degree+grade%2C+he+wondered+why+it+wasn%E2%80%99t+rolling+down+the+hill.+He+realized+there+was+a+breeze+at+his+back+holding+the+bottle+in+place.+Then+he+had+a+thought+that+would+only+pop+into+the+mind+of+a+theoretical+astrophysicist%3A+%E2%80%9COh%21+This+is+how+Europa+formed.%E2%80%9D+Europa+is+one+of+Jupiter%E2%80%99s+four+large+Galilean+moons.+And+in+a+paper+published+Monday+in+the+Astrophysical+Journal%2C+Dr.+Batygin+and+a+co-author%2C+Alessandro+Morbidelli%2C+a+planetary+scientist+at+the+C%C3%B4te+d%E2%80%99Azur+Observatory+in+France%2C+present+a+theory+explaining+how+some+moons+form+around+gas+giants+like+Jupiter+and+Saturn%2C+suggesting+that+millimeter-sized+grains+of+hail+produced+during+the+solar+system%E2%80%99s+formation+became+trapped+around+these+massive+worlds%2C+taking+shape+one+at+a+time+into+the+potentially+habitable+moons+we+know+today.