diff --git a/supervision/dataset/core.py b/supervision/dataset/core.py index 48043dbb..551e96da 100644 --- a/supervision/dataset/core.py +++ b/supervision/dataset/core.py @@ -118,13 +118,13 @@ class DetectionDataset(BaseDataset): Example: ```python - >>> import supervision as sv + import supervision as sv - >>> ds = sv.DetectionDataset(...) - >>> train_ds, test_ds = ds.split(split_ratio=0.7, - ... random_state=42, shuffle=True) - >>> len(train_ds), len(test_ds) - (700, 300) + ds = sv.DetectionDataset(...) + train_ds, test_ds = ds.split(split_ratio=0.7, + random_state=42, shuffle=True) + len(train_ds), len(test_ds) + # (700, 300) ``` """ @@ -231,24 +231,24 @@ class DetectionDataset(BaseDataset): Example: ```python - >>> import roboflow - >>> from roboflow import Roboflow - >>> import supervision as sv + import roboflow + from roboflow import Roboflow + import supervision as sv - >>> roboflow.login() + roboflow.login() - >>> rf = Roboflow() + rf = Roboflow() - >>> project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID) - >>> dataset = project.version(PROJECT_VERSION).download("voc") + project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID) + dataset = project.version(PROJECT_VERSION).download("voc") - >>> ds = sv.DetectionDataset.from_pascal_voc( - ... images_directory_path=f"{dataset.location}/train/images", - ... annotations_directory_path=f"{dataset.location}/train/labels" - ... ) + ds = sv.DetectionDataset.from_pascal_voc( + images_directory_path=f"{dataset.location}/train/images", + annotations_directory_path=f"{dataset.location}/train/labels" + ) - >>> ds.classes - ['dog', 'person'] + ds.classes + # ['dog', 'person'] ``` """ @@ -288,25 +288,24 @@ class DetectionDataset(BaseDataset): Example: ```python - >>> import roboflow - >>> from roboflow import Roboflow - >>> import supervision as sv + import roboflow + from roboflow import Roboflow + import supervision as sv - >>> roboflow.login() + roboflow.login() + rf = Roboflow() - >>> rf = Roboflow() + project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID) + dataset = project.version(PROJECT_VERSION).download("yolov5") - >>> project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID) - >>> dataset = project.version(PROJECT_VERSION).download("yolov5") + ds = sv.DetectionDataset.from_yolo( + images_directory_path=f"{dataset.location}/train/images", + annotations_directory_path=f"{dataset.location}/train/labels", + data_yaml_path=f"{dataset.location}/data.yaml" + ) - >>> ds = sv.DetectionDataset.from_yolo( - ... images_directory_path=f"{dataset.location}/train/images", - ... annotations_directory_path=f"{dataset.location}/train/labels", - ... data_yaml_path=f"{dataset.location}/data.yaml" - ... ) - - >>> ds.classes - ['dog', 'person'] + ds.classes + # ['dog', 'person'] ``` """ classes, images, annotations = load_yolo_annotations( @@ -394,24 +393,23 @@ class DetectionDataset(BaseDataset): Example: ```python - >>> import roboflow - >>> from roboflow import Roboflow - >>> import supervision as sv + import roboflow + from roboflow import Roboflow + import supervision as sv - >>> roboflow.login() + roboflow.login() + rf = Roboflow() - >>> rf = Roboflow() + project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID) + dataset = project.version(PROJECT_VERSION).download("coco") - >>> project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID) - >>> dataset = project.version(PROJECT_VERSION).download("coco") + ds = sv.DetectionDataset.from_coco( + images_directory_path=f"{dataset.location}/train", + annotations_path=f"{dataset.location}/train/_annotations.coco.json", + ) - >>> ds = sv.DetectionDataset.from_coco( - ... images_directory_path=f"{dataset.location}/train", - ... annotations_path=f"{dataset.location}/train/_annotations.coco.json", - ... ) - - >>> ds.classes - ['dog', 'person'] + ds.classes + # ['dog', 'person'] ``` """ classes, images, annotations = load_coco_annotations( @@ -486,25 +484,25 @@ class DetectionDataset(BaseDataset): Example: ```python - >>> import supervision as sv + import supervision as sv - >>> ds_1 = sv.DetectionDataset(...) - >>> len(ds_1) - 100 - >>> ds_1.classes - ['dog', 'person'] + ds_1 = sv.DetectionDataset(...) + len(ds_1) + # 100 + ds_1.classes + # ['dog', 'person'] - >>> ds_2 = sv.DetectionDataset(...) - >>> len(ds_2) - 200 - >>> ds_2.classes - ['cat'] + ds_2 = sv.DetectionDataset(...) + len(ds_2) + # 200 + ds_2.classes + # ['cat'] - >>> ds_merged = sv.DetectionDataset.merge([ds_1, ds_2]) - >>> len(ds_merged) - 300 - >>> ds_merged.classes - ['cat', 'dog', 'person'] + ds_merged = sv.DetectionDataset.merge([ds_1, ds_2]) + len(ds_merged) + # 300 + ds_merged.classes + # ['cat', 'dog', 'person'] ``` """ merged_images, merged_annotations = {}, {} @@ -571,13 +569,13 @@ class ClassificationDataset(BaseDataset): Example: ```python - >>> import supervision as sv + import supervision as sv - >>> cd = sv.ClassificationDataset(...) - >>> train_cd,test_cd = cd.split(split_ratio=0.7, - ... random_state=42,shuffle=True) - >>> len(train_cd), len(test_cd) - (700, 300) + cd = sv.ClassificationDataset(...) + train_cd,test_cd = cd.split(split_ratio=0.7, + random_state=42,shuffle=True) + len(train_cd), len(test_cd) + # (700, 300) ``` """ image_names = list(self.images.keys()) @@ -639,20 +637,19 @@ class ClassificationDataset(BaseDataset): Example: ```python - >>> import roboflow - >>> from roboflow import Roboflow - >>> import supervision as sv + import roboflow + from roboflow import Roboflow + import supervision as sv - >>> roboflow.login() + roboflow.login() + rf = Roboflow() - >>> rf = Roboflow() + project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID) + dataset = project.version(PROJECT_VERSION).download("folder") - >>> project = rf.workspace(WORKSPACE_ID).project(PROJECT_ID) - >>> dataset = project.version(PROJECT_VERSION).download("folder") - - >>> cd = sv.ClassificationDataset.from_folder_structure( - ... root_directory_path=f"{dataset.location}/train" - ... ) + cd = sv.ClassificationDataset.from_folder_structure( + root_directory_path=f"{dataset.location}/train" + ) ``` """ classes = os.listdir(root_directory_path)