Merge branch 'bitbucket' into github

Author: jenkins

examples/detection.ipynb

@@ -80,6 +80,13 @@
     "to your proxy server and port before launching Python or Jupyter."
    ]
   },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "source": "!pip install torchvision",
+   "outputs": [],
+   "execution_count": null
+  },
   {
    "cell_type": "code",
    "metadata": {},
@@ -133,6 +140,13 @@
     "files and run inference with the Torchvision model:"
    ]
   },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "source": "!pip install tqdm torch",
+   "outputs": [],
+   "execution_count": null
+  },
   {
    "cell_type": "code",
    "metadata": {},

pyproject.toml

@@ -7,11 +7,11 @@ name = "thetis"
 description = "Solution for AI system analysis regarding performance, uncertainty consistency (calibration), fairness, and other aspects relevant for regulatory compliance."
 requires-python = ">=3.10"
 authors = [
-    { email = "fabian.kueppers@efs-techhub.com" },
+    { email = "thetis@efs-techhub.com" },
     { name = "e:fs TechHub GmbH" }
 ]
 maintainers = [
-    { email = "fabian.kueppers@efs-techhub.com" },
+    { email = "thetis@efs-techhub.com" },
     { name = "e:fs TechHub GmbH" }
 ]
 

requirements.txt

@@ -1 +1 @@
-thetiscore==0.2.3
+thetiscore==0.2.4

thetis/__init__.py

@@ -24,4 +24,4 @@
 from .mlflow import thetis_mlflow
 
 name = "thetis"
-__version__ = "0.2.3"
+__version__ = "0.2.4"

thetis/mlflow.py

@@ -18,7 +18,7 @@ def thetis_mlflow(
         annotations: Union[pd.DataFrame, Dict[str, pd.DataFrame]],
         description: Dict[str, str] = None,
         mlflow_step: Optional[int] = None,
-        predictions_perturbations: None = None,
+        robustness_predictions: Optional[Dict[str, Union[pd.DataFrame, Dict[str, pd.DataFrame]]]] = None,
         license_file_path: Union[str, os.PathLike] = None,
         license_xml_str: str = None,
         license_key_and_signature: Tuple[str, str] = None,
@@ -148,15 +148,16 @@ def thetis_mlflow(
             coordinates and optionally sensitive attributes. The bounding box columns must correspond to the format
             specified in the user configuration. Must also include a "__meta__" key with image metadata.
             **Regression:** DataFrame with columns "target" and optionally sensitive attributes.
-         description: dict containing a description of your AI solution required for creating a technical documentation
+        description: dict containing a description of your AI solution required for creating a technical documentation
             in accordance with Article 11 and Annex IV of the AI Act. The data entered here includes the title,
             provider, contact person (intern), contact person (extern), purpose, requirements, forms of distribution,
             hardware details and a UI description. These details cannot be automatically filled out and must be provided
             manually to ensure the documentation's completeness and transparency. If certain fields in the descriptions
             are not filled in, they also remain empty in the technical documentation.
         mlflow_step: Optional integer with the current step count to be passed to MLflow's "log_param" function.
-        predictions_perturbations: AI predictions for each configured perturbation type.
-            The perturbation type is the key of the dictionary, and each value must have the same format as the "predictions" parameter.
+        robustness_predictions: Dict with AI predictions for each configured corruption type and intensity.
+            The dict keys correspond to the directory names of the robustness data directories as created by
+            create_robustness_images. Each value must have the same format as the "predictions" parameter.
         license_file_path: Path to an XML license file to run the application.
         license_xml_str: String representation of an XML license file to run the application.
         license_key_and_signature: Tuple of license key and signature strings.
@@ -258,7 +259,7 @@ def thetis_mlflow(
         annotations=annotations,
         description=description,
         mlflow_step=mlflow_step,
-        predictions_perturbations=predictions_perturbations,
+        robustness_predictions=robustness_predictions,
         license_file_path=license_file_path,
         license_xml_str=license_xml_str,
         license_key_and_signature=license_key_and_signature,

thetis/service.py

@@ -18,7 +18,7 @@ def thetis(
         annotations: Union[pd.DataFrame, Dict[str, pd.DataFrame]],
         description: Dict[str, str] = None,
         output_dir: Optional[str] = None,
-        predictions_perturbations: None = None,
+        robustness_predictions: Optional[Dict[str, Union[pd.DataFrame, Dict[str, pd.DataFrame]]]] = None,
         license_file_path: Union[str, os.PathLike] = None,
         license_xml_str: str = None,
         license_key_and_signature: Tuple[str, str] = None,
@@ -53,7 +53,9 @@ def thetis(
             manually to ensure the documentation's completeness and transparency. If certain fields in the descriptions
             are not filled in, they also remain empty in the technical documentation.
         output_dir: Path to the output directory where the PDF report will be stored. Default is None.
-        predictions_perturbations: AI predictions for each configured perturbation type.
+        robustness_predictions: Dict with AI predictions for each configured corruption type and intensity.
+            The dict keys correspond to the directory names of the robustness data directories as created by
+            create_robustness_images. Each value must have the same format as the "predictions" parameter.
         license_file_path: Path to an XML license file to run the application.
         license_xml_str: String representation of an XML license file to run the application.
         license_key_and_signature: Tuple of license key and signature strings.
@@ -158,7 +160,7 @@ def thetis(
         annotations=annotations,
         description=description,
         output_dir=output_dir,
-        predictions_perturbations=predictions_perturbations,
+        robustness_predictions=robustness_predictions,
         license_file_path=license_file_path,
         license_xml_str=license_xml_str,
         license_key_and_signature=license_key_and_signature,