--- a
+++ b/.dev/gather_benchmark_evaluation_results.py
@@ -0,0 +1,91 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+import argparse
+import glob
+import os.path as osp
+
+import mmcv
+from mmcv import Config
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(
+        description='Gather benchmarked model evaluation results')
+    parser.add_argument('config', help='test config file path')
+    parser.add_argument(
+        'root',
+        type=str,
+        help='root path of benchmarked models to be gathered')
+    parser.add_argument(
+        '--out',
+        type=str,
+        default='benchmark_evaluation_info.json',
+        help='output path of gathered metrics and compared '
+        'results to be stored')
+
+    args = parser.parse_args()
+    return args
+
+
+if __name__ == '__main__':
+    args = parse_args()
+
+    root_path = args.root
+    metrics_out = args.out
+    result_dict = {}
+
+    cfg = Config.fromfile(args.config)
+
+    for model_key in cfg:
+        model_infos = cfg[model_key]
+        if not isinstance(model_infos, list):
+            model_infos = [model_infos]
+        for model_info in model_infos:
+            previous_metrics = model_info['metric']
+            config = model_info['config'].strip()
+            fname, _ = osp.splitext(osp.basename(config))
+
+            # Load benchmark evaluation json
+            metric_json_dir = osp.join(root_path, fname)
+            if not osp.exists(metric_json_dir):
+                print(f'{metric_json_dir} not existed.')
+                continue
+
+            json_list = glob.glob(osp.join(metric_json_dir, '*.json'))
+            if len(json_list) == 0:
+                print(f'There is no eval json in {metric_json_dir}.')
+                continue
+
+            log_json_path = list(sorted(json_list))[-1]
+            metric = mmcv.load(log_json_path)
+            if config not in metric.get('config', {}):
+                print(f'{config} not included in {log_json_path}')
+                continue
+
+            # Compare between new benchmark results and previous metrics
+            differential_results = dict()
+            new_metrics = dict()
+            for record_metric_key in previous_metrics:
+                if record_metric_key not in metric['metric']:
+                    raise KeyError('record_metric_key not exist, please '
+                                   'check your config')
+                old_metric = previous_metrics[record_metric_key]
+                new_metric = round(metric['metric'][record_metric_key] * 100,
+                                   2)
+
+                differential = new_metric - old_metric
+                flag = '+' if differential > 0 else '-'
+                differential_results[
+                    record_metric_key] = f'{flag}{abs(differential):.2f}'
+                new_metrics[record_metric_key] = new_metric
+
+            result_dict[config] = dict(
+                differential=differential_results,
+                previous=previous_metrics,
+                new=new_metrics)
+
+    if metrics_out:
+        mmcv.dump(result_dict, metrics_out, indent=4)
+    print('===================================')
+    for config_name, metrics in result_dict.items():
+        print(config_name, metrics)
+    print('===================================')