update docs and rename variables.

iliauniiccocrevaluation.py

@@ -42,17 +42,17 @@ Args:
     predictions: list of OCR detections in FiftyOne dataset format.
     references: list of OCR detections in FiftyOne dataset format.
 Returns:
-    evaluation_results: dictionary containing multiple metrics
+    evaluation_results: list of dictionaries containing multiple metrics
 Examples:
     Examples should be written in doctest format, and should illustrate how
     to use the function.
 
     >>> dataset = load_dataset("anz2/iliauni_icc_georgian_ocr", use_auth_token="<auth token here>")
     >>> sample = dataset['test'][0]
-    >>> ocr_evaluator = evaluate.load("iliauniiccocrevaluation")
-    >>> results = ocr_evaluator.compute(references=[sample], predictions=[0, 1])
-    >>> print(results)
-    {'accuracy': 1.0}
+    >>> ocr_evaluator = evaluate.load("anz2/iliauniiccocrevaluation")
+    >>> results = ocr_evaluator._compute(predictions=[sample], references=[sample])
+    >>> print(results[0].keys())
+    dict_keys(['accuracy', 'precision', 'recall', 'f1', 'levenstein_distances_stats', 'levenstein_similarities_stats', 'iou_stats', 'edit_operations_stats'])
 """
 
 
@@ -117,9 +117,7 @@ class IliauniIccOCREvaluation(evaluate.Metric):
                                 ),
                                 "image": datasets.Image()
                             }
-                        ),
-                        length=-1,
-                        id=None
+                        )
                     ),
                     "references": datasets.Sequence(
                         feature=datasets.Features(
@@ -167,17 +165,15 @@ class IliauniIccOCREvaluation(evaluate.Metric):
                                 ),
                                 "image": datasets.Image()
                             }
-                        ),
-                        length=-1,
-                        id=None
-                    ),
+                        )
+                    )
                 }
             ),
             # Homepage of the module for documentation
-            homepage="http://module.homepage",
+            homepage="",
             # Additional links to the codebase or references
-            codebase_urls=["http://github.com/path/to/codebase/of/new_module"],
-            reference_urls=["http://path.to.reference.url/new_module"]
+            codebase_urls=["https://github.com/IliaUni-ICC/ocr_evaluation"],
+            reference_urls=[]
         )
 
     def _download_and_prepare(self, dl_manager):
@@ -189,12 +185,12 @@ class IliauniIccOCREvaluation(evaluate.Metric):
         """Returns the scores"""
 
         assert len(predictions) == len(references)
-        eval_results = []
+        results = []
         for prediction, reference in zip(predictions, references):
             prediction_df = FiftyOneOcr(data=prediction).get_word_annotations(convert_bbox=True)
             reference_df = FiftyOneOcr(data=reference).get_word_annotations(convert_bbox=True)
 
-            eval_result = evaluate_by_words(prediction_df, reference_df, pref1="Pred_", pref2="Tar_")
-            eval_results.append(eval_result)
+            result = evaluate_by_words(prediction_df, reference_df, pref1="Pred_", pref2="Tar_")
+            results.append(result)
 
-        return eval_results
+        return results