Code cleanup

Author: hovnatan

superannotate/__init__.py

@@ -38,7 +38,6 @@ def consensus(*args, **kwargs):
     delete_annotation_class, download_annotation_classes_json,
     get_annotation_class_metadata, search_annotation_classes
 )
-from .db.clone_project import clone_project
 from .db.exports import (
     download_export, get_export_metadata, get_exports, prepare_export
 )
@@ -61,13 +60,12 @@ def consensus(*args, **kwargs):
     assign_images, copy_image, copy_images, delete_images, move_image,
     move_images, pin_image, upload_image_to_project
 )
-from .db.project_metadata import get_project_metadata
 from .db.projects import (
-    create_project, create_project_from_metadata, delete_project,
+    clone_project, create_project, create_project_from_metadata, delete_project,
     get_project_default_image_quality_in_editor, get_project_image_count,
-    get_project_settings, get_project_workflow, rename_project,
-    set_project_default_image_quality_in_editor, set_project_settings,
-    set_project_workflow, share_project, unshare_project,
+    get_project_metadata, get_project_settings, get_project_workflow,
+    rename_project, set_project_default_image_quality_in_editor,
+    set_project_settings, set_project_workflow, share_project, unshare_project,
     upload_annotations_from_folder_to_project,
     upload_images_from_azure_blob_to_project,
     upload_images_from_folder_to_project,

superannotate/db/clone_project.py

@@ -19,7 +19,6 @@
 )
 from ..api import API
 from ..exceptions import SABaseException
-from ..parameter_decorators import project_metadata
 from .annotation_classes import (
     fill_class_and_attribute_ids, fill_class_and_attribute_names,
     get_annotation_classes_id_to_name, get_annotation_classes_name_to_id,

superannotate/db/images.py

@@ -35,7 +35,8 @@
 )
 from .images import get_image_metadata, search_images
 from .project_api import (
-    get_project_and_folder_metadata, get_project_metadata_bare
+    get_project_and_folder_metadata, get_project_metadata_bare,
+    get_project_metadata_with_users
 )
 from .users import get_team_contributor_metadata
 
@@ -1962,3 +1963,98 @@ def get_project_default_image_quality_in_editor(project):
             0,
             "Image quality in editor should be 'compressed', 'original' or None for project settings value"
         )
+
+
+def get_project_metadata(
+    project,
+    include_annotation_classes=False,
+    include_settings=False,
+    include_workflow=False,
+    include_contributors=False,
+    include_complete_image_count=False
+):
+    """Returns project metadata
+
+    :param project: project name or project metadata from previous calls
+    :type project: str or dict
+    :param include_annotation_classes: enables project annotation classes output under
+                                       the key "annotation_classes"
+    :type include_annotation_classes: bool
+    :param include_settings: enables project settings output under
+                             the key "settings"
+    :type include_settings: bool
+    :param include_workflow: enables project workflow output under
+                             the key "workflow"
+    :type include_workflow: bool
+    :param include_contributors: enables project contributors output under
+                             the key "contributors"
+    :type include_contributors: bool
+
+    :return: metadata of project
+    :rtype: dict
+    """
+    if not isinstance(project, dict):
+        project = get_project_metadata_bare(
+            project, include_complete_image_count
+        )
+    result = copy.deepcopy(project)
+    if include_annotation_classes:
+        result["annotation_classes"] = search_annotation_classes(project)
+    if include_contributors:
+        result["contributors"] = get_project_metadata_with_users(project
+                                                                )["users"]
+    if include_settings:
+        result["settings"] = get_project_settings(project)
+    if include_workflow:
+        result["workflow"] = get_project_workflow(project)
+    return result
+
+
+def clone_project(
+    project_name,
+    from_project,
+    project_description=None,
+    copy_annotation_classes=True,
+    copy_settings=True,
+    copy_workflow=True,
+    copy_contributors=False
+):
+    """Create a new project in the team using annotation classes and settings from from_project.
+
+    :param project_name: new project's name
+    :type project_name: str
+    :param from_project: the name of the project being used for duplication
+    :type from_project: str
+    :param project_description: the new project's description. If None, from_project's
+                                description will be used
+    :type project_description: str
+    :param copy_annotation_classes: enables copying annotation classes
+    :type copy_annotation_classes: bool
+    :param copy_settings: enables copying project settings
+    :type copy_settings: bool
+    :param copy_workflow: enables copying project workflow
+    :type copy_workflow: bool
+    :param copy_contributors: enables copying project contributors
+    :type copy_contributors: bool
+
+    :return: dict object metadata of the new project
+    :rtype: dict
+    """
+    try:
+        get_project_metadata_bare(project_name)
+    except SANonExistingProjectNameException:
+        pass
+    else:
+        raise SAExistingProjectNameException(
+            0, "Project with name " + project_name +
+            " already exists. Please use unique names for projects to use with SDK."
+        )
+    metadata = get_project_metadata(
+        from_project, copy_annotation_classes, copy_settings, copy_workflow,
+        copy_contributors
+    )
+    metadata["name"] = project_name
+    if project_description is not None:
+        metadata["description"] = project_description
+
+    return create_project_from_metadata(metadata)

superannotate/db/project_metadata.py

@@ -8,7 +8,8 @@
 from .common import upload_project
 
 PROJECT_NAME_VECTOR = 'ML Functionality Test Vector'
-PROJECT_NAME_PIXEL = 'ML Functionality Test Pixel'
+PROJECT_NAME_PIXEL_PREDICTION = 'ML Functionality Test Pixel Prediction'
+PROJECT_NAME_PIXEL_SEGMENTATION = 'ML Functionality Test Pixel Segmentation'
 PROJECT_DESCRIPTION = 'testing ml functionality through SDK'
 PROJECT_PATH_PIXEL = "./tests/sample_project_pixel_for_ml_functionality"
 PROJECT_PATH_VECTOR = "./tests/sample_project_vector_for_ml_functionality"
@@ -28,7 +29,7 @@ def test_run_prediction():
     )
 
     upload_project(
-        Path(PROJECT_PATH_PIXEL), PROJECT_NAME_PIXEL,
+        Path(PROJECT_PATH_PIXEL), PROJECT_NAME_PIXEL_PREDICTION,
         "Test for ml functionality", "Pixel"
     )
 
@@ -42,15 +43,15 @@ def test_run_prediction():
     #Tests that the argument 'project' is valid
     with pytest.raises(SABaseException) as e:
         sa.run_prediction(
-            [PROJECT_NAME_VECTOR, PROJECT_NAME_PIXEL], ["DoesntMatter.jpg"],
-            MODEL_NAME
+            [PROJECT_NAME_VECTOR, PROJECT_NAME_PIXEL_PREDICTION],
+            ["DoesntMatter.jpg"], MODEL_NAME
         )
         assert str(
             e
         ) == "smart prediction cannot be run on images from different projects simultaneously"
 
     #Tests if prediction on all available images gets run
-    image_names_pixel = sa.search_images(PROJECT_NAME_PIXEL)
+    image_names_pixel = sa.search_images(PROJECT_NAME_PIXEL_PREDICTION)
     image_names_vector = sa.search_images(PROJECT_NAME_VECTOR)
 
     succeded_imgs, failed_imgs = sa.run_prediction(
@@ -59,12 +60,13 @@ def test_run_prediction():
     assert (len(succeded_imgs) + len(failed_imgs)) == 4
 
     succeded_imgs, failed_imgs = sa.run_prediction(
-        PROJECT_NAME_PIXEL, image_names_pixel[:4], MODEL_NAME
+        PROJECT_NAME_PIXEL_PREDICTION, image_names_pixel[:4], MODEL_NAME
     )
     assert (len(succeded_imgs) + len(failed_imgs)) == 4
 
     succeded_imgs, failed_imgs = sa.run_prediction(
-        PROJECT_NAME_PIXEL, image_names_pixel[:4] + ["NA.jpg"], MODEL_NAME
+        PROJECT_NAME_PIXEL_PREDICTION, image_names_pixel[:4] + ["NA.jpg"],
+        MODEL_NAME
     )
     assert (len(succeded_imgs) + len(failed_imgs)) == 4
 
@@ -84,35 +86,39 @@ def test_run_segmentation():
     model_generic = 'generic'
 
     upload_project(
-        Path(PROJECT_PATH_PIXEL), PROJECT_NAME_PIXEL,
+        Path(PROJECT_PATH_PIXEL), PROJECT_NAME_PIXEL_SEGMENTATION,
         "Test for ml functionality", "Pixel"
     )
 
-    image_names_pixel = sa.search_images(PROJECT_NAME_PIXEL)
+    image_names_pixel = sa.search_images(PROJECT_NAME_PIXEL_SEGMENTATION)
     with pytest.raises(SABaseException) as e:
         res = sa.run_segmentation(
             PROJECT_NAME_VECTOR, image_names_pixel, model_auto
         )
         assert str(e) == "Operation not supported for given project type"
     with pytest.raises(SABaseException) as e:
         sa.run_segmentation(
-            PROJECT_NAME_PIXEL, image_names_pixel[:2], "NonExistantModel"
+            PROJECT_NAME_PIXEL_SEGMENTATION, image_names_pixel[:2],
+            "NonExistantModel"
         )
         assert str(e) == "Model Does not exist"
 
     with pytest.raises(SABaseException) as e:
         sa.run_segmentation(
-            PROJECT_NAME_PIXEL, ["NonExistantImage.jpg"], MODEL_NAME
+            PROJECT_NAME_PIXEL_SEGMENTATION, ["NonExistantImage.jpg"],
+            MODEL_NAME
         )
         assert str(e) == "No valid image names were provided"
 
     succeded_imgs, failed_imgs = sa.run_segmentation(
-        PROJECT_NAME_PIXEL, image_names_pixel[:4] + ["NA.jpg"], model_generic
+        PROJECT_NAME_PIXEL_SEGMENTATION, image_names_pixel[:4] + ["NA.jpg"],
+        model_generic
     )
     assert (len(succeded_imgs) + len(failed_imgs)) == 4
 
     succeded_imgs, failed_imgs = sa.run_segmentation(
-        PROJECT_NAME_PIXEL, image_names_pixel[:4] + ["NA.jpg"], model_auto
+        PROJECT_NAME_PIXEL_SEGMENTATION, image_names_pixel[:4] + ["NA.jpg"],
+        model_auto
     )
 
     assert (len(succeded_imgs) + len(failed_imgs)) == 4