implemented unit test for benchmark

Author: ero1311

tests/consensus_benchmark/test_benchmark.py

@@ -0,0 +1,50 @@
+from pathlib import Path
+import superannotate as sa
+
+sa.init(Path.home() / ".superannotate" / "config.json")
+
+test_root = Path().resolve() / 'tests'
+
+
+def test_benchmark():
+    annot_types = ['polygon', 'bbox', 'point']
+    gt_project_name = 'consensus_1'
+    project_names = ['consensus_2', 'consensus_3']
+    df_column_names = [
+        'creatorEmail', 'imageName', 'instanceId', 'area', 'className',
+        'attributes', 'projectName', 'score'
+    ]
+    export_path = test_root / 'consensus_benchmark'
+    for annot_type in annot_types:
+        res_df = sa.benchmark(
+            gt_project_name,
+            project_names,
+            export_root=export_path,
+            annot_type=annot_type
+        )
+        #test content of projectName column
+        assert sorted(res_df['projectName'].unique()) == project_names
+
+        #test structure of resulting DataFrame
+        assert sorted(res_df.columns) == sorted(df_column_names)
+
+        #test lower bound of the score
+        assert (res_df['score'] >= 0).all()
+
+        #test upper bound of the score
+        assert (res_df['score'] <= 1).all()
+
+    image_names = [
+        'bonn_000000_000019_leftImg8bit.png',
+        'bielefeld_000000_000321_leftImg8bit.png'
+    ]
+
+    #test filtering images with given image names list
+    res_images = sa.benchmark(
+        gt_project_name,
+        project_names,
+        export_root=export_path,
+        image_list=image_names
+    )
+
+    assert sorted(res_images['imageName'].unique()) == sorted(image_names)