add support for fiftyone > 0.14.2 (#296)

* add support for fiftyone > 0.14.2

* update to v0.8.13

* handle when coco image names inclue folder

README.md

@@ -195,7 +195,7 @@ sahi predict --slice_width 256 --slice_height 256 --overlap_height_ratio 0.1 --o
 <big><b>Explore COCO dataset via FiftyOne app:</b></big>
 </summary>
 
-For supported version: `pip install fiftyone>=0.11.1<0.15.0`
+For supported version: `pip install fiftyone>=0.14.2<0.15.0`
 
 ```python
 from sahi.utils.fiftyone import launch_fiftyone_app
@@ -437,15 +437,8 @@ If you use this package in your work, please cite it as:
 
 ```
 @software{akyon2021sahi,
-  author       = {Akyon, Fatih Cagatay and
-                  Cengiz, Cemil and
-                  Altinuc, Sinan Onur and
-                  Cavusoglu, Devrim and
-                  Sahin, Kadir and
-                  Eryuksel, Ogulcan},
-  title        = {{SAHI: A lightweight vision library for performing 
-                   large scale object detection and instance
-                   segmentation}},
+  author       = {Akyon, Fatih Cagatay and Cengiz, Cemil and Altinuc, Sinan Onur and Cavusoglu, Devrim and Sahin, Kadir and Eryuksel, Ogulcan},
+  title        = {{SAHI: A lightweight vision library for performing large scale object detection and instance segmentation}},
   month        = nov,
   year         = 2021,
   publisher    = {Zenodo},

sahi/__init__.py

@@ -1 +1 @@
-__version__ = "0.8.12"
+__version__ = "0.8.13"

sahi/utils/fiftyone.py

@@ -3,72 +3,12 @@
 try:
     import fiftyone as fo
     from fiftyone.utils.coco import COCODetectionDatasetImporter as BaseCOCODetectionDatasetImporter
-    from fiftyone.utils.coco import _get_matching_image_ids, _parse_label_types, load_coco_detection_annotations
+    from fiftyone.utils.coco import _get_matching_image_ids, load_coco_detection_annotations
 except ModuleNotFoundError:
     raise ModuleNotFoundError('Please run "pip install -U fiftyone" to install fiftyone first for fiftyone utilities.')
 
 
 class COCODetectionDatasetImporter(BaseCOCODetectionDatasetImporter):
-    def __init__(
-        self,
-        dataset_dir=None,
-        data_path=None,
-        labels_path=None,
-        label_types=None,
-        classes=None,
-        image_ids=None,
-        include_id=False,
-        extra_attrs=None,
-        only_matching=False,
-        use_polylines=False,
-        tolerance=None,
-        shuffle=False,
-        seed=None,
-        max_samples=None,
-    ):
-        data_path = self._parse_data_path(
-            dataset_dir=dataset_dir,
-            data_path=data_path,
-            default="data/",
-        )
-
-        labels_path = self._parse_labels_path(
-            dataset_dir=dataset_dir,
-            labels_path=labels_path,
-            default="labels.json",
-        )
-
-        label_types = _parse_label_types(label_types)
-
-        if include_id:
-            label_types.append("coco_id")
-
-        super().__init__(
-            dataset_dir=dataset_dir,
-            shuffle=shuffle,
-            seed=seed,
-            max_samples=max_samples,
-        )
-
-        self.data_path = data_path
-        self.labels_path = labels_path
-        self.label_types = label_types
-        self.classes = classes
-        self.image_ids = image_ids
-        self.extra_attrs = extra_attrs
-        self.only_matching = only_matching
-        self.use_polylines = use_polylines
-        self.tolerance = tolerance
-
-        self._info = None
-        self._classes = None
-        self._supercategory_map = None
-        self._image_paths_map = None
-        self._image_dicts_map = None
-        self._annotations = None
-        self._filenames = None
-        self._iter_filenames = None
-
     def setup(self):
         if self.labels_path is not None and os.path.isfile(self.labels_path):
             (