diff --git a/superannotate/analytics/common.py b/superannotate/analytics/common.py index 2b06b007e..c087be247 100644 --- a/superannotate/analytics/common.py +++ b/superannotate/analytics/common.py @@ -153,7 +153,8 @@ def aggregate_annotations_as_df( include_classes_wo_annotations=False, include_comments=False, include_tags=False, - verbose=True + verbose=True, + folder_names=None ): """Aggregate annotations as pandas dataframe from project root. @@ -166,6 +167,8 @@ def aggregate_annotations_as_df( :type include_comments: bool :param include_tags: enables inclusion of tags info as tag column :type include_tags: bool + :param folder_names: Aggregate the specified folders from project_root. If None aggregate all folders in the project_root. + :type folder_names: (list of str) :return: DataFrame on annotations with columns: "imageName", "instanceId", "className", "attributeGroupName", "attributeName", "type", "error", "locked", @@ -173,7 +176,7 @@ def aggregate_annotations_as_df( "meta" (geometry information as string), "commentResolved", "classColor", "groupId", "imageWidth", "imageHeight", "imageStatus", "imagePinned", "createdAt", "creatorRole", "creationType", "creatorEmail", "updatedAt", - "updatorRole", "updatorEmail", "tag" + "updatorRole", "updatorEmail", "tag", "folderName" :rtype: pandas DataFrame """ @@ -208,7 +211,8 @@ def aggregate_annotations_as_df( "creatorEmail": [], "updatedAt": [], "updatorRole": [], - "updatorEmail": [] + "updatorEmail": [], + "folderName": [] } if include_comments: @@ -283,15 +287,25 @@ def __get_user_metadata(annotation): annotations_paths = [] - for path in Path(project_root).glob('*.json'): - annotations_paths.append(path) + if folder_names is None: + project_dir_content = Path(project_root).glob('*') + for entry in project_dir_content: + if entry.is_file() and entry.suffix == '.json': + annotations_paths.append(entry) + elif entry.is_dir() and entry.name != "classes": + annotations_paths.extend(list(entry.rglob('*.json'))) + else: + for folder_name in folder_names: + annotations_paths.extend( + list((Path(project_root) / folder_name).rglob('*.json')) + ) if not annotations_paths: logger.warning( "No annotations found in project export root %s", project_root ) - type_postfix = "___objects.json" if glob.glob( - "{}/*___objects.json".format(project_root) + type_postfix = "___objects.json" if annotations_paths[0].match( + "*___objects.json" ) else "___pixel.json" for annotation_path in annotations_paths: annotation_json = json.load(open(annotation_path)) @@ -359,6 +373,9 @@ def __get_user_metadata(annotation): annotation_point_labels = annotation.get("pointLabels") attributes = annotation.get("attributes") user_metadata = __get_user_metadata(annotation) + folder_name = None + if annotation_path.parent != Path(project_root): + folder_name = annotation_path.parent.name num_added = 0 if not attributes: annotation_dict = { @@ -375,6 +392,7 @@ def __get_user_metadata(annotation): "pointLabels": annotation_point_labels, "classColor": annotation_class_color, "groupId": annotation_group_id, + "folderName": folder_name, } annotation_dict.update(user_metadata) annotation_dict.update(image_metadata) @@ -414,6 +432,7 @@ def __get_user_metadata(annotation): "pointLabels": annotation_point_labels, "classColor": annotation_class_color, "groupId": annotation_group_id, + "folderName": folder_name, } annotation_dict.update(user_metadata) annotation_dict.update(image_metadata) diff --git a/superannotate/consensus_benchmark/benchmark.py b/superannotate/consensus_benchmark/benchmark.py index 99d9f6111..4ed3e26b4 100644 --- a/superannotate/consensus_benchmark/benchmark.py +++ b/superannotate/consensus_benchmark/benchmark.py @@ -14,19 +14,22 @@ def benchmark( - gt_project_name, - project_names, + project, + gt_folder, + folder_names, export_root=None, image_list=None, annot_type='bbox', show_plots=False ): - """Computes benchmark score for each instance of given images that are present both gt_project_name project and projects in project_names list: + """Computes benchmark score for each instance of given images that are present both gt_project_name project and projects in folder_names list: - :param gt_project_name: Project name that contains the ground truth annotations - :type gt_project_name: str - :param project_names: list of project names to aggregate through - :type project_names: list of str + :param project: project name or metadata of the project + :type project: str or dict + :param gt_folder: project folder name that contains the ground truth annotations + :type gt_folder: str + :param folder_names: list of folder names in the project for which the scores will be computed + :type folder_names: list of str :param export_root: root export path of the projects :type export_root: Pathlike (str or Path) :param image_list: List of image names from the projects list that must be used. If None, then all images from the projects list will be used. Default: None @@ -36,6 +39,8 @@ def benchmark( :param show_plots: If True, show plots based on results of consensus computation. Default: False :type show_plots: bool + :return: Pandas DateFrame with columns (creatorEmail, QA, imageName, instanceId, className, area, attribute, folderName, score) + :rtype: pandas DataFrame """ def aggregate_attributes(instance_df): def attribute_to_list(attribute_df): @@ -61,7 +66,7 @@ def attribute_to_list(attribute_df): ["attributeGroupName", "attributeName"], axis=1, inplace=True ) instance_df.drop_duplicates( - subset=["imageName", "instanceId", "project"], inplace=True + subset=["imageName", "instanceId", "folderName"], inplace=True ) instance_df["attributes"] = [attributes] return instance_df @@ -72,27 +77,18 @@ def attribute_to_list(attribute_df): if export_root is None: with tempfile.TemporaryDirectory() as export_dir: - gt_project_meta = prepare_export(gt_project_name) - download_export(gt_project_name, gt_project_meta, export_dir) - gt_project_df = aggregate_annotations_as_df(export_dir) + proj_export_meta = prepare_export(project_name) + download_export(project_name, proj_export_meta, export_dir) + project_df = aggregate_annotations_as_df(export_dir) else: - export_dir = Path(export_root) / gt_project_name - gt_project_df = aggregate_annotations_as_df(export_dir) - gt_project_df["project"] = gt_project_name + project_df = aggregate_annotations_as_df(export_root) - benchmark_dfs = [] - for project_name in project_names: - if export_root is None: - with tempfile.TemporaryDirectory() as export_dir: - proj_export_meta = prepare_export(project_name) - download_export(project_name, proj_export_meta, export_dir) - project_df = aggregate_annotations_as_df(export_dir) - else: - export_dir = Path(export_root) / project_name - project_df = aggregate_annotations_as_df(export_dir) + gt_project_df = project_df[project_df["folderName"] == gt_folder] - project_df["project"] = project_name - project_gt_df = pd.concat([project_df, gt_project_df]) + benchmark_dfs = [] + for folder_name in folder_names: + folder_df = project_df[project_df["folderName"] == folder_name] + project_gt_df = pd.concat([folder_df, gt_project_df]) project_gt_df = project_gt_df[project_gt_df["instanceId"].notna()] if image_list is not None: @@ -102,7 +98,7 @@ def attribute_to_list(attribute_df): project_gt_df.query("type == '" + annot_type + "'", inplace=True) project_gt_df = project_gt_df.groupby( - ["imageName", "instanceId", "project"] + ["imageName", "instanceId", "folderName"] ) project_gt_df = project_gt_df.apply(aggregate_attributes).reset_index( drop=True @@ -115,13 +111,13 @@ def attribute_to_list(attribute_df): benchmark_project_df = pd.concat(all_benchmark_data, ignore_index=True) benchmark_project_df = benchmark_project_df[ - benchmark_project_df["projectName"] == project_name] + benchmark_project_df["folderName"] == folder_name] benchmark_dfs.append(benchmark_project_df) benchmark_df = pd.concat(benchmark_dfs, ignore_index=True) if show_plots: - consensus_plot(benchmark_df, project_names) + consensus_plot(benchmark_df, folder_names) return benchmark_df \ No newline at end of file diff --git a/superannotate/consensus_benchmark/consensus.py b/superannotate/consensus_benchmark/consensus.py index 3a6370016..0c297f7fb 100644 --- a/superannotate/consensus_benchmark/consensus.py +++ b/superannotate/consensus_benchmark/consensus.py @@ -14,7 +14,8 @@ def consensus( - project_names, + project, + folder_names, export_root=None, image_list=None, annot_type='bbox', @@ -22,8 +23,10 @@ def consensus( ): """Computes consensus score for each instance of given images that are present in at least 2 of the given projects: - :param project_names: list of project names to aggregate through - :type project_names: list of str + :param project: project name or metadata of the project + :type project: str or dict + :param folder_names: list of folder names in the project for which the scores will be computed + :type folder_names: list of str :param export_root: root export path of the projects :type export_root: Pathlike (str or Path) :param image_list: List of image names from the projects list that must be used. If None, then all images from the projects list will be used. Default: None @@ -33,26 +36,24 @@ def consensus( :param show_plots: If True, show plots based on results of consensus computation. Default: False :type show_plots: bool + :return: Pandas DateFrame with columns (creatorEmail, QA, imageName, instanceId, className, area, attribute, folderName, score) + :rtype: pandas DataFrame """ supported_types = ['polygon', 'bbox', 'point'] if annot_type not in supported_types: raise NotImplementedError - project_dfs = [] - for project_name in project_names: - if export_root is None: - with tempfile.TemporaryDirectory() as export_dir: - proj_export_meta = prepare_export(project_name) - download_export(project_name, proj_export_meta, export_dir) - project_df = aggregate_annotations_as_df(export_dir) - else: - export_dir = Path(export_root) / project_name + if export_root is None: + with tempfile.TemporaryDirectory() as export_dir: + proj_export_meta = prepare_export(project) + download_export(project, proj_export_meta, export_dir) project_df = aggregate_annotations_as_df(export_dir) - project_df["project"] = project_name - project_dfs.append(project_df) + else: + project_df = aggregate_annotations_as_df(export_root) - all_projects_df = pd.concat(project_dfs) - all_projects_df = all_projects_df[all_projects_df["instanceId"].notna()] + all_projects_df = project_df[project_df["instanceId"].notna()] + all_projects_df = all_projects_df.loc[ + all_projects_df["folderName"].isin(folder_names)] if image_list is not None: all_projects_df = all_projects_df.loc[ @@ -84,13 +85,13 @@ def attribute_to_list(attribute_df): ["attributeGroupName", "attributeName"], axis=1, inplace=True ) instance_df.drop_duplicates( - subset=["imageName", "instanceId", "project"], inplace=True + subset=["imageName", "instanceId", "folderName"], inplace=True ) instance_df["attributes"] = [attributes] return instance_df all_projects_df = all_projects_df.groupby( - ["imageName", "instanceId", "project"] + ["imageName", "instanceId", "folderName"] ) all_projects_df = all_projects_df.apply(aggregate_attributes).reset_index( drop=True @@ -105,6 +106,6 @@ def attribute_to_list(attribute_df): consensus_df = pd.concat(all_consensus_data, ignore_index=True) if show_plots: - consensus_plot(consensus_df, project_names) + consensus_plot(consensus_df, folder_names) return consensus_df \ No newline at end of file diff --git a/superannotate/consensus_benchmark/helpers.py b/superannotate/consensus_benchmark/helpers.py index b9a9894ee..4de1508b5 100644 --- a/superannotate/consensus_benchmark/helpers.py +++ b/superannotate/consensus_benchmark/helpers.py @@ -39,10 +39,10 @@ def image_consensus(df, image_name, annot_type): """ image_df = df[df["imageName"] == image_name] - all_projects = list(set(df["project"])) + all_projects = list(set(df["folderName"])) column_names = [ "creatorEmail", "imageName", "instanceId", "area", "className", - "attributes", "projectName", "score" + "attributes", "folderName", "score" ] instance_id = 0 image_data = {} @@ -52,8 +52,8 @@ def image_consensus(df, image_name, annot_type): projects_shaply_objs = {} # generate shapely objects of instances for _, row in image_df.iterrows(): - if row["project"] not in projects_shaply_objs: - projects_shaply_objs[row["project"]] = [] + if row["folderName"] not in projects_shaply_objs: + projects_shaply_objs[row["folderName"]] = [] inst_data = row["meta"] if annot_type == 'bbox': inst_coords = inst_data["points"] @@ -69,7 +69,7 @@ def image_consensus(df, image_name, annot_type): elif annot_type == 'point': inst = Point(inst_data["x"], inst_data["y"]) if inst.is_valid: - projects_shaply_objs[row["project"]].append( + projects_shaply_objs[row["folderName"]].append( ( inst, row["className"], row["creatorEmail"], row["attributes"] @@ -113,7 +113,7 @@ def image_consensus(df, image_name, annot_type): image_data["imageName"].append(image_name) image_data["instanceId"].append(instance_id) image_data["className"].append(max_instances[0][2]) - image_data["projectName"].append(max_instances[0][0]) + image_data["folderName"].append(max_instances[0][0]) image_data["score"].append(0) else: for curr_match_data in max_instances: @@ -130,7 +130,7 @@ def image_consensus(df, image_name, annot_type): image_data["imageName"].append(image_name) image_data["instanceId"].append(instance_id) image_data["className"].append(curr_match_data[2]) - image_data["projectName"].append(curr_match_data[0]) + image_data["folderName"].append(curr_match_data[0]) image_data["score"].append( proj_cons / (len(all_projects) - 1) ) @@ -156,10 +156,10 @@ def consensus_plot(consensus_df, projects): #project-wise boxplot project_box_fig = px.box( plot_data, - x="projectName", + x="folderName", y="score", points="all", - color="projectName", + color="folderName", color_discrete_sequence=px.colors.qualitative.Dark24 ) project_box_fig.show() @@ -171,12 +171,12 @@ def consensus_plot(consensus_df, projects): y="score", color="className", symbol="creatorEmail", - facet_col="projectName", + facet_col="folderName", color_discrete_sequence=px.colors.qualitative.Dark24, hover_data={ "className": False, "imageName": True, - "projectName": False, + "folderName": False, "area": False, "score": False }, diff --git a/tests/consensus_benchmark/consensus_1/berlin_000000_000019_leftImg8bit.png___objects.json b/tests/consensus_benchmark/consensus_1/berlin_000000_000019_leftImg8bit.png___objects.json deleted file mode 100644 index 3bdd1034e..000000000 --- a/tests/consensus_benchmark/consensus_1/berlin_000000_000019_leftImg8bit.png___objects.json +++ /dev/null @@ -1,788 +0,0 @@ -{ - "metadata": { - "name": "berlin_000000_000019_leftImg8bit.png", - "width": 2048, - "height": 1024, - "status": "Completed", - "pinned": false, - "isPredicted": null, - "projectId": null, - "annotatorEmail": null, - "qaEmail": null - }, - "instances": [ - { - "type": "bbox", - "classId": 113975, - "probability": 100, - "points": { - "x1": 1378.09, - "x2": 1399.48, - "y1": 421.93, - "y2": 471.05 - }, - "groupId": 0, - "pointLabels": {}, - "locked": false, - "visible": true, - "attributes": [], - "trackingId": null, - "error": null, - "createdAt": "2020-10-23T12:28:02.767Z", - "createdBy": { - "email": "user3@mail.com", - "role": "Annotator" - }, - "creationType": "Manual", - "updatedAt": "2020-10-23T12:28:08.609Z", - "updatedBy": { - "email": "user3@mail.com", - "role": "Annotator" - }, - "className": "person" - }, - { - "type": "polygon", - "classId": 113975, - "probability": 100, - "points": [ - 1338.48, - 421.14, - 1342.44, - 423.52, - 1349.57, - 433.03, - 1345.61, - 440.95, - 1345.61, - 443.32, - 1344.81, - 443.32, - 1340.06, - 462.34, - 1338.48, - 453.62, - 1334.52, - 451.25, - 1332.93, - 444.91, - 1329.76, - 444.91, - 1331.35, - 432.23, - 1337.68, - 421.93 - ], - "groupId": 0, - "pointLabels": {}, - "locked": false, - "visible": true, - "attributes": [], - "trackingId": null, - "error": null, - "createdAt": "2020-10-23T12:27:14.272Z", - "createdBy": { - "email": "user2@mail.com", - "role": "Annotator" - }, - "creationType": "Manual", - "updatedAt": "2020-10-23T12:27:40.004Z", - "updatedBy": { - "email": "user2@mail.com", - "role": "Annotator" - }, - "className": "person" - }, - { - "type": "point", - "classId": 113975, - "probability": 100, - "x": 1640.14, - "y": 441.85, - "groupId": 0, - "pointLabels": {}, - "locked": false, - "visible": true, - "attributes": [], - "trackingId": null, - "error": null, - "createdAt": "2020-10-23T12:23:55.471Z", - "createdBy": { - "email": "user1@mail.com", - "role": "Annotator" - }, - "creationType": "Manual", - "updatedAt": "2020-10-23T12:23:58.830Z", - "updatedBy": { - "email": "user1@mail.com", - "role": "Annotator" - }, - "className": "person" - }, - { - "type": "bbox", - "classId": 113976, - "probability": 100, - "points": { - "x1": 0, - "x2": 243.84, - "y1": 289.93, - "y2": 519.26 - }, - "groupId": 0, - "pointLabels": {}, - "locked": false, - "visible": true, - "attributes": [], - "trackingId": null, - "error": null, - "createdAt": "2020-10-27T14:57:16.319Z", - "createdBy": { - "email": "user2@mail.com", - "role": "Annotator" - }, - "creationType": "Manual", - "updatedAt": "2020-10-27T14:57:28.986Z", - "updatedBy": { - "email": "user2@mail.com", - "role": "Annotator" - }, - "className": "car" - }, - { - "type": "polygon", - "classId": 113976, - "probability": 100, - "points": [ - 956.29, - 425.86, - 1000.65, - 425.07, - 1011.75, - 452.79, - 1013.33, - 492.4, - 1006.99, - 492.4, - 1003.82, - 482.9, - 968.17, - 484.48, - 947.58, - 441.7, - 954.71, - 425.07 - ], - "groupId": 0, - "pointLabels": {}, - "locked": false, - "visible": true, - "attributes": [], - "trackingId": null, - "error": null, - "createdAt": "2020-10-23T12:26:00.773Z", - "createdBy": { - "email": "user2@mail.com", - "role": "Annotator" - }, - "creationType": "Manual", - "updatedAt": "2020-10-23T12:26:32.274Z", - "updatedBy": { - "email": "user2@mail.com", - "role": "Annotator" - }, - "className": "car" - }, - { - "type": "polygon", - "classId": 113976, - "probability": 100, - "points": [ - 332.81, - 440.12, - 293.2, - 475.77, - 292.41, - 502.7, - 383.51, - 499.53, - 442.14, - 493.99, - 433.42, - 453.59, - 412.03, - 433.78, - 332.02, - 437.74 - ], - "groupId": 0, - "pointLabels": {}, - "locked": false, - "visible": true, - "attributes": [], - "trackingId": null, - "error": null, - "createdAt": "2020-10-23T12:24:57.599Z", - "createdBy": { - "email": "user3@mail.com", - "role": "Annotator" - }, - "creationType": "Manual", - "updatedAt": "2020-10-23T12:25:19.520Z", - "updatedBy": { - "email": "user3@mail.com", - "role": "Annotator" - }, - "className": "car" - }, - { - "type": "polygon", - "classId": 113976, - "probability": 100, - "points": [ - 834.53, - 525.74, - 853.33, - 527.19, - 870.69, - 518.51, - 873.58, - 509.83, - 934.33, - 509.83, - 940.11, - 519.96, - 969.04, - 517.07, - 966.15, - 475.12, - 941.56, - 423.05, - 862.01, - 423.05, - 851.89, - 433.18, - 837.42, - 466.44, - 831.64, - 521.4 - ], - "groupId": 0, - "pointLabels": {}, - "locked": false, - "visible": true, - "attributes": [ - { - "id": 276068, - "groupId": 67247, - "name": "yellow", - "groupName": "color" - } - ], - "trackingId": null, - "error": null, - "createdAt": "2020-10-23T12:24:11.204Z", - "createdBy": { - "email": "user1@mail.com", - "role": "Annotator" - }, - "creationType": "Manual", - "updatedAt": "2020-10-27T14:55:23.938Z", - "updatedBy": { - "email": "user1@mail.com", - "role": "Annotator" - }, - "className": "car" - }, - { - "type": "bbox", - "classId": 113976, - "probability": 100, - "points": { - "x1": 1356.66, - "x2": 1375.46, - "y1": 343.5, - "y2": 386.89 - }, - "groupId": 0, - "pointLabels": {}, - "locked": false, - "visible": true, - "attributes": [], - "trackingId": null, - "error": null, - "createdAt": "2020-10-23T12:21:40.139Z", - "createdBy": { - "email": "user1@mail.com", - "role": "Annotator" - }, - "creationType": "Manual", - "updatedAt": "2020-10-23T12:23:04.139Z", - "updatedBy": { - "email": "user1@mail.com", - "role": "Annotator" - }, - "className": "car" - }, - { - "type": "bbox", - "classId": 113976, - "probability": 100, - "points": { - "x1": 914.08, - "x2": 928.54, - "y1": 252.38, - "y2": 294.33 - }, - "groupId": 0, - "pointLabels": {}, - "locked": false, - "visible": true, - "attributes": [], - "trackingId": null, - "error": null, - "createdAt": "2020-10-23T12:21:59.421Z", - "createdBy": { - "email": "user1@mail.com", - "role": "Annotator" - }, - "creationType": "Manual", - "updatedAt": "2020-10-23T12:23:04.139Z", - "updatedBy": { - "email": "user1@mail.com", - "role": "Annotator" - }, - "className": "car" - }, - { - "type": "point", - "classId": 113976, - "probability": 100, - "x": 1994.49, - "y": 423.05, - "groupId": 0, - "pointLabels": {}, - "locked": false, - "visible": true, - "attributes": [], - "trackingId": null, - "error": null, - "createdAt": "2020-10-23T12:22:25.842Z", - "createdBy": { - "email": "user1@mail.com", - "role": "Annotator" - }, - "creationType": "Manual", - "updatedAt": "2020-10-23T12:23:04.139Z", - "updatedBy": { - "email": "user1@mail.com", - "role": 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\ No newline at end of file diff --git a/tests/consensus_benchmark/test_benchmark.py b/tests/consensus_benchmark/test_benchmark.py index 67240adf1..8caadfd10 100644 --- a/tests/consensus_benchmark/test_benchmark.py +++ b/tests/consensus_benchmark/test_benchmark.py @@ -3,26 +3,28 @@ import superannotate as sa test_root = Path().resolve() / 'tests' +project_name = "consensus_enhanced" def test_benchmark(): annot_types = ['polygon', 'bbox', 'point'] - gt_project_name = 'consensus_1' - project_names = ['consensus_2', 'consensus_3'] + gt_folder_name = 'consensus_1' + folder_names = ['consensus_2', 'consensus_3'] df_column_names = [ 'creatorEmail', 'imageName', 'instanceId', 'area', 'className', - 'attributes', 'projectName', 'score' + 'attributes', 'folderName', 'score' ] - export_path = test_root / 'consensus_benchmark' + export_path = test_root / 'consensus_benchmark' / 'consensus_test_data' for annot_type in annot_types: res_df = sa.benchmark( - gt_project_name, - project_names, + project_name, + gt_folder_name, + folder_names, export_root=export_path, annot_type=annot_type ) #test content of projectName column - assert sorted(res_df['projectName'].unique()) == project_names + assert sorted(res_df['folderName'].unique()) == folder_names #test structure of resulting DataFrame assert sorted(res_df.columns) == sorted(df_column_names) @@ -40,8 +42,9 @@ def test_benchmark(): #test filtering images with given image names list res_images = sa.benchmark( - gt_project_name, - project_names, + project_name, + gt_folder_name, + folder_names, export_root=export_path, image_list=image_names ) diff --git a/tests/consensus_benchmark/test_consensus.py b/tests/consensus_benchmark/test_consensus.py index 30c129e84..a21a90098 100644 --- a/tests/consensus_benchmark/test_consensus.py +++ b/tests/consensus_benchmark/test_consensus.py @@ -3,22 +3,26 @@ import superannotate as sa test_root = Path().resolve() / 'tests' +project_name = "consensus_enhanced" def test_consensus(): annot_types = ['polygon', 'bbox', 'point'] - project_names = ['consensus_1', 'consensus_2', 'consensus_3'] + folder_names = ['consensus_1', 'consensus_2', 'consensus_3'] df_column_names = [ 'creatorEmail', 'imageName', 'instanceId', 'area', 'className', - 'attributes', 'projectName', 'score' + 'attributes', 'folderName', 'score' ] - export_path = test_root / 'consensus_benchmark' + export_path = test_root / 'consensus_benchmark' / 'consensus_test_data' for annot_type in annot_types: res_df = sa.consensus( - project_names, export_root=export_path, annot_type=annot_type + project_name, + folder_names, + export_root=export_path, + annot_type=annot_type ) #test content of projectName column - assert sorted(res_df['projectName'].unique()) == project_names + assert sorted(res_df['folderName'].unique()) == folder_names #test structure of resulting DataFrame assert sorted(res_df.columns) == sorted(df_column_names) @@ -36,7 +40,10 @@ def test_consensus(): #test filtering images with given image names list res_images = sa.consensus( - project_names, export_root=export_path, image_list=image_names + project_name, + folder_names, + export_root=export_path, + image_list=image_names ) assert sorted(res_images['imageName'].unique()) == sorted(image_names)