renaming yolov8 to ultralytics yolo

README.md

@@ -175,11 +175,11 @@ For more information about the supported formats, see:
 | [Kitti Raw Format](https://www.cvlibs.net/datasets/kitti/raw_data.php)                           | ✔️     | ✔️     |
 | [LFW](http://vis-www.cs.umass.edu/lfw/)                                                          | ✔️     | ✔️     |
 | [Supervisely Point Cloud Format](https://docs.supervise.ly/data-organization/00_ann_format_navi) | ✔️     | ✔️     |
-| [YOLOv8 Detection](https://docs.ultralytics.com/datasets/detect/)                                | ✔️     | ✔️     |
-| [YOLOv8 Oriented Bounding Boxes](https://docs.ultralytics.com/datasets/obb/)                     | ✔️     | ✔️     |
-| [YOLOv8 Segmentation](https://docs.ultralytics.com/datasets/segment/)                            | ✔️     | ✔️     |
-| [YOLOv8 Pose](https://docs.ultralytics.com/datasets/pose/)                                       | ✔️     | ✔️     |
-| [YOLOv8 Classification](https://docs.ultralytics.com/datasets/classify/)                         | ✔️     | ✔️     |
+| [Ultralytics YOLO Detection](https://docs.ultralytics.com/datasets/detect/)                      | ✔️     | ✔️     |
+| [Ultralytics YOLO Oriented Bounding Boxes](https://docs.ultralytics.com/datasets/obb/)                     | ✔️     | ✔️     |
+| [Ultralytics YOLO Segmentation](https://docs.ultralytics.com/datasets/segment/)                            | ✔️     | ✔️     |
+| [Ultralytics YOLO Pose](https://docs.ultralytics.com/datasets/pose/)                                       | ✔️     | ✔️     |
+| [Ultralytics YOLO Classification](https://docs.ultralytics.com/datasets/classify/)                         | ✔️     | ✔️     |
 
 <!--lint enable maximum-line-length-->
 

cvat/apps/dataset_manager/formats/yolo.py

@@ -77,53 +77,53 @@ def _import_yolo(*args, **kwargs):
     _import_common(*args, format_name="yolo", **kwargs)
 
 
-@exporter(name='YOLOv8 Detection', ext='ZIP', version='1.0')
-def _export_yolov8_detection(*args, **kwargs):
-    _export_common(*args, format_name='yolov8_detection', **kwargs)
+@exporter(name='Ultralytics YOLO Detection', ext='ZIP', version='1.0')
+def _export_yolo_ultralytics_detection(*args, **kwargs):
+    _export_common(*args, format_name='yolo_ultralytics_detection', **kwargs)
 
 
-@exporter(name='YOLOv8 Oriented Bounding Boxes', ext='ZIP', version='1.0')
-def _export_yolov8_oriented_boxes(*args, **kwargs):
-    _export_common(*args, format_name='yolov8_oriented_boxes', **kwargs)
+@exporter(name='Ultralytics YOLO Oriented Bounding Boxes', ext='ZIP', version='1.0')
+def _export_yolo_ultralytics_oriented_boxes(*args, **kwargs):
+    _export_common(*args, format_name='yolo_ultralytics_oriented_boxes', **kwargs)
 
 
-@exporter(name='YOLOv8 Segmentation', ext='ZIP', version='1.0')
-def _export_yolov8_segmentation(dst_file, temp_dir, instance_data, *, save_images=False):
+@exporter(name='Ultralytics YOLO Segmentation', ext='ZIP', version='1.0')
+def _export_yolo_ultralytics_segmentation(dst_file, temp_dir, instance_data, *, save_images=False):
     with GetCVATDataExtractor(instance_data, include_images=save_images) as extractor:
         dataset = Dataset.from_extractors(extractor, env=dm_env)
         dataset = dataset.transform('masks_to_polygons')
-        dataset.export(temp_dir, 'yolov8_segmentation', save_images=save_images)
+        dataset.export(temp_dir, 'yolo_ultralytics_segmentation', save_images=save_images)
 
     make_zip_archive(temp_dir, dst_file)
 
 
-@exporter(name='YOLOv8 Pose', ext='ZIP', version='1.0')
-def _export_yolov8_pose(*args, **kwargs):
-    _export_common(*args, format_name='yolov8_pose', **kwargs)
+@exporter(name='Ultralytics YOLO Pose', ext='ZIP', version='1.0')
+def _export_yolo_ultralytics_pose(*args, **kwargs):
+    _export_common(*args, format_name='yolo_ultralytics_pose', **kwargs)
 
 
-@exporter(name='YOLOv8 Classification', ext='ZIP', version='1.0')
-def _export_yolov8_classification(*args, **kwargs):
-    _export_common(*args, format_name='yolov8_classification', **kwargs)
+@exporter(name='Ultralytics YOLO Classification', ext='ZIP', version='1.0')
+def _export_yolo_ultralytics_classification(*args, **kwargs):
+    _export_common(*args, format_name='yolo_ultralytics_classification', **kwargs)
 
 
-@importer(name='YOLOv8 Detection', ext="ZIP", version="1.0")
-def _import_yolov8_detection(*args, **kwargs):
-    _import_common(*args, format_name="yolov8_detection", **kwargs)
+@importer(name='Ultralytics YOLO Detection', ext="ZIP", version="1.0")
+def _import_yolo_ultralytics_detection(*args, **kwargs):
+    _import_common(*args, format_name="yolo_ultralytics_detection", **kwargs)
 
 
-@importer(name='YOLOv8 Segmentation', ext="ZIP", version="1.0")
-def _import_yolov8_segmentation(*args, **kwargs):
-    _import_common(*args, format_name="yolov8_segmentation", **kwargs)
+@importer(name='Ultralytics YOLO Segmentation', ext="ZIP", version="1.0")
+def _import_yolo_ultralytics_segmentation(*args, **kwargs):
+    _import_common(*args, format_name="yolo_ultralytics_segmentation", **kwargs)
 
 
-@importer(name='YOLOv8 Oriented Bounding Boxes', ext="ZIP", version="1.0")
-def _import_yolov8_oriented_boxes(*args, **kwargs):
-    _import_common(*args, format_name="yolov8_oriented_boxes", **kwargs)
+@importer(name='Ultralytics YOLO Oriented Bounding Boxes', ext="ZIP", version="1.0")
+def _import_yolo_ultralytics_oriented_boxes(*args, **kwargs):
+    _import_common(*args, format_name="yolo_ultralytics_oriented_boxes", **kwargs)
 
 
-@importer(name='YOLOv8 Pose', ext="ZIP", version="1.0")
-def _import_yolov8_pose(src_file, temp_dir, instance_data, **kwargs):
+@importer(name='Ultralytics YOLO Pose', ext="ZIP", version="1.0")
+def _import_yolo_ultralytics_pose(src_file, temp_dir, instance_data, **kwargs):
     with GetCVATDataExtractor(instance_data) as extractor:
         point_categories = extractor.categories().get(AnnotationType.points)
         label_categories = extractor.categories().get(AnnotationType.label)
@@ -135,12 +135,12 @@ def _import_yolov8_pose(src_file, temp_dir, instance_data, **kwargs):
         src_file,
         temp_dir,
         instance_data,
-        format_name="yolov8_pose",
+        format_name="yolo_ultralytics_pose",
         import_kwargs=dict(skeleton_sub_labels=true_skeleton_point_labels),
         **kwargs
     )
 
 
-@importer(name='YOLOv8 Classification', ext="ZIP", version="1.0")
-def _import_yolov8_classification(*args, **kwargs):
-    _import_common(*args, format_name="yolov8_classification", **kwargs)
+@importer(name='Ultralytics YOLO Classification', ext="ZIP", version="1.0")
+def _import_yolo_ultralytics_classification(*args, **kwargs):
+    _import_common(*args, format_name="yolo_ultralytics_classification", **kwargs)

cvat/apps/dataset_manager/tests/assets/annotations.json

@@ -976,7 +976,7 @@
     ],
     "tracks": []
   },
-  "YOLOv8 Classification 1.0": {
+  "Ultralytics YOLO Classification 1.0": {
     "version": 0,
     "tags": [
       {
@@ -990,7 +990,7 @@
     "shapes": [],
     "tracks": []
   },
-  "YOLOv8 Detection 1.0": {
+  "Ultralytics YOLO Detection 1.0": {
     "version": 0,
     "tags": [],
     "shapes": [
@@ -1008,7 +1008,7 @@
     ],
     "tracks": []
   },
-  "YOLOv8 Oriented Bounding Boxes 1.0": {
+  "Ultralytics YOLO Oriented Bounding Boxes 1.0": {
     "version": 0,
     "tags": [],
     "shapes": [
@@ -1027,7 +1027,7 @@
     ],
     "tracks": []
   },
-  "YOLOv8 Segmentation 1.0": {
+  "Ultralytics YOLO Segmentation 1.0": {
     "version": 0,
     "tags": [],
     "shapes": [
@@ -1045,7 +1045,7 @@
     ],
     "tracks": []
   },
-  "YOLOv8 Pose 1.0": {
+  "Ultralytics YOLO Pose 1.0": {
     "version": 0,
     "tags": [],
     "shapes": [

cvat/apps/dataset_manager/tests/assets/tasks.json

@@ -634,8 +634,8 @@
       }
     ]
   },
-  "YOLOv8 Pose 1.0": {
-    "name": "YOLOv8 pose task",
+  "Ultralytics YOLO Pose 1.0": {
+    "name": "Ultralytics YOLO pose task",
     "overlap": 0,
     "segment_size": 100,
     "labels": [

cvat/apps/dataset_manager/tests/test_formats.py

@@ -292,11 +292,11 @@ def test_export_formats_query(self):
             'LFW 1.0',
             'Cityscapes 1.0',
             'Open Images V6 1.0',
-            'YOLOv8 Classification 1.0',
-            'YOLOv8 Oriented Bounding Boxes 1.0',
-            'YOLOv8 Detection 1.0',
-            'YOLOv8 Pose 1.0',
-            'YOLOv8 Segmentation 1.0',
+            'Ultralytics YOLO Classification 1.0',
+            'Ultralytics YOLO Oriented Bounding Boxes 1.0',
+            'Ultralytics YOLO Detection 1.0',
+            'Ultralytics YOLO Pose 1.0',
+            'Ultralytics YOLO Segmentation 1.0',
         })
 
     def test_import_formats_query(self):
@@ -329,11 +329,11 @@ def test_import_formats_query(self):
             'Open Images V6 1.0',
             'Datumaro 1.0',
             'Datumaro 3D 1.0',
-            'YOLOv8 Classification 1.0',
-            'YOLOv8 Oriented Bounding Boxes 1.0',
-            'YOLOv8 Detection 1.0',
-            'YOLOv8 Pose 1.0',
-            'YOLOv8 Segmentation 1.0',
+            'Ultralytics YOLO Classification 1.0',
+            'Ultralytics YOLO Oriented Bounding Boxes 1.0',
+            'Ultralytics YOLO Detection 1.0',
+            'Ultralytics YOLO Pose 1.0',
+            'Ultralytics YOLO Segmentation 1.0',
         })
 
     def test_exports(self):
@@ -383,11 +383,11 @@ def test_empty_images_are_exported(self):
             # ('KITTI 1.0', 'kitti') format does not support empty annotations
             ('LFW 1.0', 'lfw'),
             # ('Cityscapes 1.0', 'cityscapes'), does not support, empty annotations
-            ('YOLOv8 Classification 1.0', 'yolov8_classification'),
-            ('YOLOv8 Oriented Bounding Boxes 1.0', 'yolov8_oriented_boxes'),
-            ('YOLOv8 Detection 1.0', 'yolov8_detection'),
-            ('YOLOv8 Pose 1.0', 'yolov8_pose'),
-            ('YOLOv8 Segmentation 1.0', 'yolov8_segmentation'),
+            ('Ultralytics YOLO Classification 1.0', 'yolo_ultralytics_classification'),
+            ('Ultralytics YOLO Oriented Bounding Boxes 1.0', 'yyolo_ultralytics_oriented_boxes'),
+            ('Ultralytics YOLO Detection 1.0', 'yolo_ultralytics_detection'),
+            ('Ultralytics YOLO Pose 1.0', 'yolo_ultralytics_pose'),
+            ('Ultralytics YOLO Segmentation 1.0', 'yolo_ultralytics_segmentation'),
         ]:
             with self.subTest(format=format_name):
                 if not dm.formats.registry.EXPORT_FORMATS[format_name].ENABLED:

cvat/apps/dataset_manager/tests/test_rest_api_formats.py

@@ -55,12 +55,12 @@
 DEFAULT_ATTRIBUTES_FORMATS = [
     "VGGFace2 1.0",
     "WiderFace 1.0",
-    "YOLOv8 Classification 1.0",
+    "Ultralytics YOLO Classification 1.0",
     "YOLO 1.1",
-    "YOLOv8 Detection 1.0",
-    "YOLOv8 Segmentation 1.0",
-    "YOLOv8 Oriented Bounding Boxes 1.0",
-    "YOLOv8 Pose 1.0",
+    "Ultralytics YOLO Detection 1.0",
+    "Ultralytics YOLO Segmentation 1.0",
+    "Ultralytics YOLO Oriented Bounding Boxes 1.0",
+    "Ultralytics YOLO Pose 1.0",
     "PASCAL VOC 1.1",
     "Segmentation mask 1.1",
     "ImageNet 1.0",
@@ -411,7 +411,7 @@ def test_api_v2_dump_and_upload_annotations_with_objects_type_is_shape(self):
                         "Cityscapes 1.0", "COCO Keypoints 1.0",
                         "ICDAR Localization 1.0", "ICDAR Recognition 1.0",
                         "ICDAR Segmentation 1.0", "Market-1501 1.0", "MOT 1.1",
-                        "YOLOv8 Pose 1.0",
+                        "Ultralytics YOLO Pose 1.0",
                     ]:
                         task = self._create_task(tasks[dump_format_name], images)
                     else:
@@ -469,7 +469,7 @@ def test_api_v2_dump_and_upload_annotations_with_objects_type_is_shape(self):
                                 "Cityscapes 1.0", "COCO Keypoints 1.0",
                                 "ICDAR Localization 1.0", "ICDAR Recognition 1.0",
                                 "ICDAR Segmentation 1.0", "Market-1501 1.0", "MOT 1.1",
-                                "YOLOv8 Pose 1.0",
+                                "Ultralytics YOLO Pose 1.0",
                             ]:
                                 task = self._create_task(tasks[upload_format_name], images)
                             else:
@@ -513,7 +513,7 @@ def test_api_v2_dump_annotations_with_objects_type_is_track(self):
                         "Cityscapes 1.0", "COCO Keypoints 1.0",
                         "ICDAR Localization 1.0", "ICDAR Recognition 1.0",
                         "ICDAR Segmentation 1.0", "Market-1501 1.0", "MOT 1.1",
-                        "YOLOv8 Pose 1.0",
+                        "Ultralytics YOLO Pose 1.0",
                     ]:
                         task = self._create_task(tasks[dump_format_name], video)
                     else:
@@ -569,7 +569,7 @@ def test_api_v2_dump_annotations_with_objects_type_is_track(self):
                                 "Cityscapes 1.0", "COCO Keypoints 1.0",
                                 "ICDAR Localization 1.0", "ICDAR Recognition 1.0",
                                 "ICDAR Segmentation 1.0", "Market-1501 1.0", "MOT 1.1",
-                                "YOLOv8 Pose 1.0",
+                                "Ultralytics YOLO Pose 1.0",
                             ]:
                                 task = self._create_task(tasks[upload_format_name], video)
                             else:
@@ -846,7 +846,7 @@ def test_api_v2_export_dataset(self):
                         "Cityscapes 1.0", "COCO Keypoints 1.0",
                         "ICDAR Localization 1.0", "ICDAR Recognition 1.0",
                         "ICDAR Segmentation 1.0", "Market-1501 1.0", "MOT 1.1",
-                        "YOLOv8 Pose 1.0",
+                        "Ultralytics YOLO Pose 1.0",
                     ]:
                         task = self._create_task(tasks[dump_format_name], images)
                     else:
@@ -947,7 +947,7 @@ def test_api_v2_rewriting_annotations(self):
                     if dump_format_name in [
                         "Market-1501 1.0",
                         "ICDAR Localization 1.0", "ICDAR Recognition 1.0",
-                        "ICDAR Segmentation 1.0", "COCO Keypoints 1.0", "YOLOv8 Pose 1.0",
+                        "ICDAR Segmentation 1.0", "COCO Keypoints 1.0", "Ultralytics YOLO Pose 1.0",
                     ]:
                         task = self._create_task(tasks[dump_format_name], images)
                     else:
@@ -1058,7 +1058,7 @@ def test_api_v2_tasks_annotations_dump_and_upload_with_datumaro(self):
                         "Market-1501 1.0", "Cityscapes 1.0",
                         "ICDAR Localization 1.0", "ICDAR Recognition 1.0",
                         "ICDAR Segmentation 1.0", "COCO Keypoints 1.0",
-                        "YOLOv8 Pose 1.0",
+                        "Ultralytics YOLO Pose 1.0",
                     ]:
                         task = self._create_task(tasks[dump_format_name], images)
                     else:

cvat/apps/engine/tests/test_rest_api.py

@@ -6127,13 +6127,13 @@ def _get_initial_annotation(annotation_format):
             elif annotation_format == "YOLO 1.1":
                 annotations["shapes"] = rectangle_shapes_wo_attrs
 
-            elif annotation_format == "YOLOv8 Detection 1.0":
+            elif annotation_format == "Ultralytics YOLO Detection 1.0":
                 annotations["shapes"] = rectangle_shapes_wo_attrs
 
-            elif annotation_format == "YOLOv8 Oriented Bounding Boxes 1.0":
+            elif annotation_format == "Ultralytics YOLO Oriented Bounding Boxes 1.0":
                 annotations["shapes"] = rectangle_shapes_wo_attrs
 
-            elif annotation_format == "YOLOv8 Segmentation 1.0":
+            elif annotation_format == "Ultralytics YOLO Segmentation 1.0":
                 annotations["shapes"] = polygon_shapes_wo_attrs
 
             elif annotation_format == "COCO 1.0":
@@ -6493,7 +6493,10 @@ def etree_to_dict(t):
                     self.assertEqual(meta["task"]["name"], task["name"])
         elif format_name == "PASCAL VOC 1.1":
             self.assertTrue(zipfile.is_zipfile(content))
-        elif format_name in ["YOLO 1.1", "YOLOv8 Detection 1.0", "YOLOv8 Segmentation 1.0", "YOLOv8 Oriented Bounding Boxes 1.0", "YOLOv8 Pose 1.0"]:
+        elif format_name in [
+            "YOLO 1.1", "Ultralytics YOLO Detection 1.0", "Ultralytics YOLO Segmentation 1.0",
+            "Ultralytics YOLO Oriented Bounding Boxes 1.0", "Ultralytics YOLO Pose 1.0",
+        ]:
             self.assertTrue(zipfile.is_zipfile(content))
         elif format_name in ['Kitti Raw Format 1.0','Sly Point Cloud Format 1.0']:
             self.assertTrue(zipfile.is_zipfile(content))

cvat/requirements/base.in

@@ -12,7 +12,7 @@ azure-storage-blob==12.13.0
 boto3==1.17.61
 clickhouse-connect==0.6.8
 coreapi==2.3.3
-datumaro @ git+https://github.com/cvat-ai/datumaro.git@bf0374689df50599a34a4f220b9e5329aca695ce
+datumaro @ git+https://github.com/cvat-ai/datumaro.git@f55ccf92f7d61d7dad276dd0007fc4aeed72e0bb
 dj-pagination==2.5.0
 # Despite direct indication allauth in requirements we should keep 'with_social' for dj-rest-auth
 # to avoid possible further versions conflicts (we use registration functionality)

cvat/requirements/base.txt

@@ -56,7 +56,7 @@ cryptography==44.0.0
     #   pyjwt
 cycler==0.12.1
     # via matplotlib
-datumaro @ git+https://github.com/cvat-ai/datumaro.git@bf0374689df50599a34a4f220b9e5329aca695ce
+datumaro @ git+https://github.com/cvat-ai/datumaro.git@f55ccf92f7d61d7dad276dd0007fc4aeed72e0bb
     # via -r cvat/requirements/base.in
 defusedxml==0.7.1
     # via