Prioritize using PIL to get image size (#1259)

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-->

### Summary

Accelerate loading of image file-based datasets.

I found that printing out the YOLO dataset information for the first
time was slow. After some digging I found that `datamaro` was reading
the entire dataset through to get the size of each image.

```python
ds = Dataset.import_from("/yolo-ultralytics", "yolo")
print(ds)  # <-- wait a long time
```

```python
    # from class Image
    @Property
    def size(self) -> Optional[Tuple[int, int]]:
        """Returns (H, W)"""

        if self._size is None:
            try:
                data = self.data  # <-- load the whole media into memory
            except _image_loading_errors:
                return None
            if data is not None:
                self._size = tuple(map(int, data.shape[:2]))
        return self._size
```

Interactive encoding with datasets on HDD is slow. So I added an
override `size()` property in the `ImageFromFile` class which first
tries to get the image size using `PIL`. The `PIL` library is about 8
times faster than `OpenCV` in getting the image size.

All dataset classes that use the `size` property of `ImageFromFile` can
benefit from this modification.

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### Checklist
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- [ ] I have added unit tests to cover my changes.​
- [ ] I have added integration tests to cover my changes.​
- [ ] I have added the description of my changes into
[CHANGELOG](https://github.com/openvinotoolkit/datumaro/blob/develop/CHANGELOG.md).​
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[documentation](https://github.com/openvinotoolkit/datumaro/tree/develop/docs)
accordingly

### License

- [x] I submit _my code changes_ under the same [MIT
License](https://github.com/openvinotoolkit/datumaro/blob/develop/LICENSE)
that covers the project.
  Feel free to contact the maintainers if that's a concern.
- [x] I have updated the license header for each file (see an example
below).

```python
# Copyright (C) 2023 Intel Corporation
#
# SPDX-License-Identifier: MIT
```

---------

Co-authored-by: Vinnam Kim <[email protected]>

requirements-core.txt

@@ -1,6 +1,7 @@
 attrs>=21.3.0
 defusedxml>=0.7.0
 h5py>=2.10.0
+imagesize>=1.4.1
 lxml>=4.4.1
 matplotlib>=3.3.1
 networkx>=2.6

src/datumaro/components/media.py

@@ -29,6 +29,7 @@
 )
 
 import cv2
+import imagesize
 import numpy as np
 
 from datumaro.components.crypter import NULL_CRYPTER, Crypter
@@ -330,6 +331,19 @@ def data(self) -> Optional[np.ndarray]:
             self._size = tuple(map(int, data.shape[:2]))
         return data
 
+    @property
+    def size(self) -> Optional[Tuple[int, int]]:
+        """Returns (H, W)"""
+
+        if self._size is None:
+            try:
+                width, height = imagesize.get(self.path)
+                assert width != -1 and height != -1
+                self._size = (height, width)
+            except Exception:
+                _ = super().size
+        return self._size
+
     def save(
         self,
         fp: Union[str, io.IOBase],