review_changes

sanjaychelliah · sanjaychelliah · commit a63ff14e9246 · 2024-01-24T13:52:14.000+05:30
diff --git a/README.md b/README.md
@@ -46,9 +46,9 @@ pip3 install -r requirements.txt
 Quick intro to Image Annotation Conversion feature
 
 ```python
-from clarifai_utils import Image_Annotations
+from clarifai_utils import ImageAnnotations
 
-annotated_dataset = Image_Annotations.import_from(path= 'folder_path', format= 'annotation_format')
+annotated_dataset = ImageAnnotations.import_from(path= 'folder_path', format= 'annotation_format')
 ```
 
 ## Features
@@ -63,12 +63,12 @@ annotated_dataset = Image_Annotations.import_from(path= 'folder_path', format= '
 ## Usage
 ### Image Annotation conversion
 ```python
-from clarifai_utils import Image_Annotations
+from clarifai_utils import ImageAnnotations
 #import from folder
-coco_dataset = Image_Annotations.import_from(path='folder_path',format= 'coco_detection')
+coco_dataset = ImageAnnotations.import_from(path='folder_path',format= 'coco_detection')
 
 #clarifai dataset loader object
-coco_dataset.clarifai_loader()
+coco_dataset.dataloader
 
 
 #info about loaded dataset
diff --git a/clarifai_utils/__init__.py b/clarifai_utils/__init__.py
@@ -1,3 +1,3 @@
-from clarifai_utils.image.annotation_conversion.annotations import Image_Annotations
+from clarifai_utils.image.annotation_conversion.annotations import ImageAnnotations
 
-__all__ = ['Image_Annotations']
+__all__ = ['ImageAnnotations']
diff --git a/clarifai_utils/image/annotation_conversion/README.md b/clarifai_utils/image/annotation_conversion/README.md
@@ -7,12 +7,12 @@ A framework to load, export and analyze different annotated datasets.
 
 ### Features
 ```python
-from clarifai_utils import Image_Annotations
+from clarifai_utils import ImageAnnotations
 #import from folder
-coco_dataset = Image_Annotations.import_from(path='folder_path',format= 'coco_detection')
+coco_dataset = ImageAnnotations.import_from(path='folder_path',format= 'coco_detection')
 
 #clarifai dataset loader object
-coco_dataset.clarifai_loader()
+coco_dataset.dataloader
 
 
 #info about loaded dataset
@@ -26,14 +26,14 @@ coco_dataset.export_to('voc_detection')
 
 ### With Clarifai Python SDK
 ```python
-from clarifai_utils import Image_Annotations
-coco_dataset = Image_Annotations.import_from(path='folder_path',format= 'coco_detection')
+from clarifai_utils import ImageAnnotations
+coco_dataset = ImageAnnotations.import_from(path='folder_path',format= 'coco_detection')
 
 #clarifai SDK
 #export CLARIFAI_PAT={your personal access token}  # set PAT as env variable
 from clarifai.client.dataset import Dataset
 dataset = Dataset(user_id="user_id", app_id="app_id", dataset_id="dataset_id")
-dataset.upload_dataset(dataloader=coco_dataset.clarifai_loader())
+dataset.upload_dataset(dataloader=coco_dataset.dataloader)
 
 ```
 
diff --git a/clarifai_utils/image/annotation_conversion/annotations.py b/clarifai_utils/image/annotation_conversion/annotations.py
@@ -9,12 +9,12 @@
                                                   IMAGE_FORMAT_MAP)
 from clarifai_utils.errors import AnnotationsDatasetError, AnnotationsFormatError
 from clarifai_utils.image.annotation_conversion.base import ClarifaiDataLoader
-from clarifai_utils.image.annotation_conversion.clarifai_loaders import (ClassificationDataLoader,
-                                                                         DetectionDataLoader,
-                                                                         SegmentationDataLoader)
+from clarifai_utils.image.annotation_conversion.loaders import (ClassificationDataLoader,
+                                                                DetectionDataLoader,
+                                                                SegmentationDataLoader)
 
 
-class Image_Annotations():
+class ImageAnnotations():
   """Annotaions is a class that provides image annotation utilities."""
 
   def __init__(
@@ -47,8 +47,8 @@ def import_from(cls, path: str, format: str) -> Dataset:
             A dataset object.
 
         Example:
-            >>> from clarifai_utils import Image_Annotations
-            >>> format = Image_Annotations.import_from(path=folder_path, format = 'coco_detection')
+            >>> from clarifai_utils import ImageAnnotations
+            >>> format = ImageAnnotations.import_from(path=folder_path, format = 'coco_detection')
         """
     if format not in IMAGE_ANNOTATION_FORMATS:
       raise AnnotationsFormatError(
@@ -62,7 +62,7 @@ def import_from(cls, path: str, format: str) -> Dataset:
     except (DatasetError, DatasetImportError, DatasetNotFoundError) as ex:
       raise AnnotationsDatasetError(ex)
 
-    return Image_Annotations(dataset, format, task)
+    return ImageAnnotations(dataset, format, task)
 
   def get_info(self,) -> Dict[str, Any]:
     """Gets information about a dataset.
@@ -71,8 +71,8 @@ def get_info(self,) -> Dict[str, Any]:
             A dictionary containing the information about the dataset.
 
         Example:
-            >>> from clarifai_utils import Image_Annotations
-            >>> format = Image_Annotations.import_from(path=folder_path, format = 'coco_detection')
+            >>> from clarifai_utils import ImageAnnotations
+            >>> format = ImageAnnotations.import_from(path=folder_path, format = 'coco_detection')
             >>> info = format.get_info()
         """
     return {
@@ -92,8 +92,8 @@ def export_to(self, path: str, format: str) -> None:
             format (str): The format of the dataset.
 
         Example:
-            >>> from clarifai_utils import Image_Annotations
-            >>> format = Image_Annotations.import_from(path=folder_path, format = 'coco_detection')
+            >>> from clarifai_utils import ImageAnnotations
+            >>> format = ImageAnnotations.import_from(path=folder_path, format = 'coco_detection')
             >>> format.export_to(path=output_folder_path, format = 'voc_detection')
         """
     if format not in IMAGE_ANNOTATION_FORMATS:
@@ -116,8 +116,8 @@ def detect_format(path: str) -> str:
             The format of the dataset.
 
         Example:
-            >>> from clarifai_utils import Image_Annotations
-            >>> format = Image_Annotations.detect_format(path=folder_path)
+            >>> from clarifai_utils import ImageAnnotations
+            >>> format = ImageAnnotations.detect_format(path=folder_path)
         """
     try:
       dataset_format = Dataset.detect(path)
@@ -130,16 +130,17 @@ def detect_format(path: str) -> str:
       raise AnnotationsFormatError('Given folder does not contain a supported dataset format')
     return dataset_format
 
-  def clarifai_loader(self,) -> ClarifaiDataLoader:
+  @property
+  def dataloader(self) -> ClarifaiDataLoader:
     """Returns a Clarifai Dataloader Object to pass to SDK Dataset Upload Functionality.
 
         Returns:
             A ClarifaiDataloader object.
 
         Example:
-            >>> from clarifai_utils import Image_Annotations
-            >>> format = Image_Annotations.import_from(path=folder_path, format = 'coco_detection')
-            >>> clarifai_dataset_loader = format.clarifai_loader()
+            >>> from clarifai_utils import ImageAnnotations
+            >>> format = ImageAnnotations.import_from(path=folder_path, format = 'coco_detection')
+            >>> clarifai_dataset_loader = format.dataloader
         """
     if self.task == 'visual_classification':
       return ClassificationDataLoader(self._dataset)
diff --git a/clarifai_utils/image/annotation_conversion/base.py b/clarifai_utils/image/annotation_conversion/base.py
@@ -1,7 +1,7 @@
 from typing import TypeVar, Union
 
-from .clarifai_features import (VisualClassificationFeatures, VisualDetectionFeatures,
-                                VisualSegmentationFeatures)
+from .features import (VisualClassificationFeatures, VisualDetectionFeatures,
+                       VisualSegmentationFeatures)
 
 DATASET_UPLOAD_TASKS = ["visual_classification", "visual_detection", "visual_segmentation"]
 
diff --git a/clarifai_utils/image/annotation_conversion/features.py b/clarifai_utils/image/annotation_conversion/features.py
diff --git a/clarifai_utils/image/annotation_conversion/loaders.py b/clarifai_utils/image/annotation_conversion/loaders.py
@@ -7,8 +7,8 @@
 from datumaro.components.media import ImageFromNumpy
 
 from .base import ClarifaiDataLoader
-from .clarifai_features import (VisualClassificationFeatures, VisualDetectionFeatures,
-                                VisualSegmentationFeatures)
+from .features import (VisualClassificationFeatures, VisualDetectionFeatures,
+                       VisualSegmentationFeatures)
 
 delimiters = [",", "|", ";", "/", "\\", ":", " "]
 
diff --git a/tests/annotations/test_clarifai_loader.py b/tests/annotations/test_clarifai_loader.py
@@ -1,4 +1,4 @@
-from clarifai_utils import Image_Annotations
+from clarifai_utils import ImageAnnotations
 from tests.utils.annotations import get_asset_path
 
 IMAGENET_PATH = get_asset_path('imagenet_dataset')
@@ -25,121 +25,121 @@ class Testclarifailoader:
   """
 
   def test_imagenet_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=IMAGENET_PATH, format='imagenet')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert len(clarifai_loader) == 3
-    assert clarifai_loader.task == 'visual_classification'
-    assert clarifai_loader[0].labels[0] in ['label_0', 'label_1']
-    assert clarifai_loader[0].id == '1'
+    annotation_object = ImageAnnotations.import_from(path=IMAGENET_PATH, format='imagenet')
+    dataloader = annotation_object.dataloader
+    assert len(dataloader) == 3
+    assert dataloader.task == 'visual_classification'
+    assert dataloader[0].labels[0] in ['label_0', 'label_1']
+    assert dataloader[0].id == '1'
 
   def test_cifar_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=CIFAR_PATH, format='cifar')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_classification'
-    assert len(clarifai_loader) == 5
-    assert clarifai_loader[0].labels[0] in ['airplane', 'automobile']
+    annotation_object = ImageAnnotations.import_from(path=CIFAR_PATH, format='cifar')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_classification'
+    assert len(dataloader) == 5
+    assert dataloader[0].labels[0] in ['airplane', 'automobile']
 
   def test_mnist_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=MNIST_PATH, format='mnist')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_classification'
-    assert len(clarifai_loader) == 5
+    annotation_object = ImageAnnotations.import_from(path=MNIST_PATH, format='mnist')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_classification'
+    assert len(dataloader) == 5
 
   def test_vgg_face2_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=VGG_PATH, format='vgg_face2')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_classification'
-    assert len(clarifai_loader) == 4
+    annotation_object = ImageAnnotations.import_from(path=VGG_PATH, format='vgg_face2')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_classification'
+    assert len(dataloader) == 4
 
   def test_lfw_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=LFW_PATH, format='lfw')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_classification'
-    assert len(clarifai_loader) == 3
-    assert clarifai_loader[0].labels == ['name1']
-    assert clarifai_loader[0].id == '0001'
+    annotation_object = ImageAnnotations.import_from(path=LFW_PATH, format='lfw')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_classification'
+    assert len(dataloader) == 3
+    assert dataloader[0].labels == ['name1']
+    assert dataloader[0].id == '0001'
 
   def test_voc_detection_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=VOC_PATH, format='voc_detection')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_detection'
-    assert len(clarifai_loader) == 1
-    assert clarifai_loader[0].labels == ['cat']
-    assert clarifai_loader[0].id == '000001'
-    assert isinstance(clarifai_loader[0].image_bytes, bytes)
+    annotation_object = ImageAnnotations.import_from(path=VOC_PATH, format='voc_detection')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_detection'
+    assert len(dataloader) == 1
+    assert dataloader[0].labels == ['cat']
+    assert dataloader[0].id == '000001'
+    assert isinstance(dataloader[0].image_bytes, bytes)
 
   def test_yolo_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=YOLO_PATH, format='yolo')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_detection'
-    assert len(clarifai_loader) == 1
-    assert clarifai_loader[0].labels == ['label_2', 'label_4']
-    assert clarifai_loader[0].id == '1'
-    assert isinstance(clarifai_loader[0].image_bytes, bytes)
+    annotation_object = ImageAnnotations.import_from(path=YOLO_PATH, format='yolo')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_detection'
+    assert len(dataloader) == 1
+    assert dataloader[0].labels == ['label_2', 'label_4']
+    assert dataloader[0].id == '1'
+    assert isinstance(dataloader[0].image_bytes, bytes)
 
   def test_coco_detection_loader(self,):
-    annotation_object = Image_Annotations.import_from(
+    annotation_object = ImageAnnotations.import_from(
         path=COCO_DETECTION_PATH, format='coco_detection')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_detection'
-    assert len(clarifai_loader) == 2
-    assert clarifai_loader[0].labels == ['b']
-    assert clarifai_loader[0].id == 'a'
-    assert isinstance(clarifai_loader[0].image_bytes, bytes)
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_detection'
+    assert len(dataloader) == 2
+    assert dataloader[0].labels == ['b']
+    assert dataloader[0].id == 'a'
+    assert isinstance(dataloader[0].image_bytes, bytes)
 
   def test_cvat_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=CVAT_PATH, format='cvat')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_detection'
-    assert len(clarifai_loader) == 8
-    assert clarifai_loader[0].labels == ['label1']
-    assert isinstance(clarifai_loader[0].image_bytes, bytes)
+    annotation_object = ImageAnnotations.import_from(path=CVAT_PATH, format='cvat')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_detection'
+    assert len(dataloader) == 8
+    assert dataloader[0].labels == ['label1']
+    assert isinstance(dataloader[0].image_bytes, bytes)
 
   def test_kitti_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=KITTI_PATH, format='kitti')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_detection'
-    assert len(clarifai_loader) == 2
-    assert clarifai_loader[0].labels == ['truck', 'van']
-    assert clarifai_loader[0].id == '10'
-    assert isinstance(clarifai_loader[0].image_bytes, bytes)
+    annotation_object = ImageAnnotations.import_from(path=KITTI_PATH, format='kitti')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_detection'
+    assert len(dataloader) == 2
+    assert dataloader[0].labels == ['truck', 'van']
+    assert dataloader[0].id == '10'
+    assert isinstance(dataloader[0].image_bytes, bytes)
 
   def test_label_me_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=LABEL_ME_PATH, format='label_me')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_detection'
-    assert len(clarifai_loader) == 1
-    assert clarifai_loader[0].labels == ['b1']
-    assert clarifai_loader[0].id == 'img1'
-    assert isinstance(clarifai_loader[0].image_bytes, bytes)
+    annotation_object = ImageAnnotations.import_from(path=LABEL_ME_PATH, format='label_me')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_detection'
+    assert len(dataloader) == 1
+    assert dataloader[0].labels == ['b1']
+    assert dataloader[0].id == 'img1'
+    assert isinstance(dataloader[0].image_bytes, bytes)
 
   def test_open_images_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=OPEN_IMAGES_PATH, format='open_images')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_detection'
-    assert len(clarifai_loader) == 2
-    assert clarifai_loader[1].id == 'aa'
-    assert isinstance(clarifai_loader[0].image_bytes, bytes)
+    annotation_object = ImageAnnotations.import_from(path=OPEN_IMAGES_PATH, format='open_images')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_detection'
+    assert len(dataloader) == 2
+    assert dataloader[1].id == 'aa'
+    assert isinstance(dataloader[0].image_bytes, bytes)
 
   def test_coco_segmentation_loader(self,):
-    annotation_object = Image_Annotations.import_from(
+    annotation_object = ImageAnnotations.import_from(
         path=COCO_SEGMENTATION_PATH, format='coco_segmentation')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_segmentation'
-    assert len(clarifai_loader) == 2
-    assert isinstance(clarifai_loader[0].image_bytes, bytes)
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_segmentation'
+    assert len(dataloader) == 2
+    assert isinstance(dataloader[0].image_bytes, bytes)
 
   def test_cityscapes_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=CITYSCAPES_PATH, format='cityscapes')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_segmentation'
-    assert len(clarifai_loader) == 4
-    assert isinstance(clarifai_loader[0].image_bytes, bytes)
+    annotation_object = ImageAnnotations.import_from(path=CITYSCAPES_PATH, format='cityscapes')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_segmentation'
+    assert len(dataloader) == 4
+    assert isinstance(dataloader[0].image_bytes, bytes)
 
   def test_ade20k2017_loader(self,):
-    annotation_object = Image_Annotations.import_from(path=ADE_PATH, format='ade20k2017')
-    clarifai_loader = annotation_object.clarifai_loader()
-    assert clarifai_loader.task == 'visual_segmentation'
-    assert len(clarifai_loader) == 2
-    assert clarifai_loader[0].id == '1'
-    assert isinstance(clarifai_loader[0].image_bytes, bytes)
+    annotation_object = ImageAnnotations.import_from(path=ADE_PATH, format='ade20k2017')
+    dataloader = annotation_object.dataloader
+    assert dataloader.task == 'visual_segmentation'
+    assert len(dataloader) == 2
+    assert dataloader[0].id == '1'
+    assert isinstance(dataloader[0].image_bytes, bytes)
diff --git a/tests/annotations/test_import_formats.py b/tests/annotations/test_import_formats.py
