Add support for metadata files to `imagefolder`
_The documentation is not available anymore as the PR was closed or merged._ Love it !

+1 to using JSON Lines rather than CSV. I've also seen image datasets for which JSON Lines was used.

A `file_name` column sounds good as well, and it means we could reuse the same name for audio. And ok to check the metadata file by default :)

You suggested to name the file infos.json - since we already have a datasets_infos.json file, maybe it would be nice to have a name for the metadata/annotations that doesn't contain "info" ? (e.g. metadata.json, annotations.json, labels.json) @lhoestq I've addressed your comments and my TODOs. Additionally, I've updated `encode_nested_example`/`decode_nested_example` to support null values in place of a dictionary (if it's not top-level) since JSON Lines also supports this.  @lhoestq Sure, feel free to add more tests if you have the time.  I created a dedicated test file for `imagefolder`, moved some existing tests there from `test_packaged_modules.py`, and added an end-to-end test of `imagefolder` with metadata. I tested for train split only, and for two splits train and test.

Let me know if the test looks ok to you. I'll add similar tests but with the other structures we support on tuesday Thanks a lot for working on this! The test looks great :).  Added a test for archives. Will also add a test when the metadata file is not named correctly, and see if we can raise an informative error
This PR adds support for metadata files to `imagefolder` to add an ability to specify image fields other than `image` and `label`, which are inferred from the directory structure in the loaded dataset.

To be parsed as an image metadata file, a file should be named `"info.csv"` and should have the following structure:
```
image_id,some_col1_name,some_col2_name
rel/path/to/image1.jpg,image1_col1_value,image1_col2_value
rel/path/to/image2.jpg,image2_col1_value,image2_col2_value 
...
```

This is how the resolution works:
```
- path/to/imagefolder/directory
  - info.csv
  - 10.jpg # referenced as 10.jpg in "info.csv"
  - Cat
    - 0.jpg  # referenced as Cat/0.jpg in "info.csv"
    - 1.jpg  # referenced as Cat/1.jpg in "info.csv"
  - Dog
    - 0.jpg  # referenced as Dog/0.jpg in "info.csv"
    - 1.jpg  # referenced as Dog/1.jpg in "info.csv"
```

Open questions:
1. IMO it makes more sense to store image metadata as JSON Lines than CSV. CSV is sufficient for textual metadata but not the best for representing bounding boxes, for instance. Also, JSON Lines is more strict, which is good in this case (CSV supports various delimiters, the header line is optional, etc., so it's easier to enforce rules on JSON Lines that it's on CSV)
2. A better name for the `image_id` column, which contains image identifiers? Maybe `image_file` or `image_filename`?
3. WDYT about making `with_metadata=True` the default behavior if the loaded repo/directory contains an `info.csv` file?

An example repository: https://huggingface.co/datasets/mariosasko/PetImages. Can be loaded by installing `datasets` from the PR branch and running `load_dataset("mariosasko/PetImages", with_metadata=True)`.

cc: @abhishekkrthakur (this PR should address https://huggingface.slack.com/archives/C02JB9L6JKF/p1645450017434029?thread_ts=1645157416.389499&cid=C02JB9L6JKF)

TODOs:
- [x] Test 
- [x] Metadata file nesting
   ```
    - path/to/imagefolder/directory
      - info.csv
      - 10.jpg
      - Cat
        - info.csv  # should have higher precedence in this directory than the top-level info.csv, but we choose the first "eligible" metadata file currently
        - 0.jpg
        - 1.jpg
   ```