[Refactor] Refactor some of the functionality of `dataset_analysis` (#294)

* Refactor some of the functionality of data_analysis

* Remove redundant code in dataset_analysis.py

* Update tools/analysis_tools/dataset_analysis.py

Co-authored-by: Haian Huang(深度眸) <1286304229@qq.com>

* simplified code

* add docstring and simplify code

Co-authored-by: Haian Huang(深度眸) <1286304229@qq.com>

tools/analysis_tools/dataset_analysis.py

@@ -7,7 +7,6 @@ import matplotlib.patches as mpatches
 import matplotlib.pyplot as plt
 import numpy as np
 from mmengine.config import Config
-from mmengine.dataset.dataset_wrapper import ConcatDataset
 from mmengine.utils import ProgressBar
 from prettytable import PrettyTable
 
@@ -378,21 +377,36 @@ def main():
     # register all modules in mmdet into the registries
     register_all_modules()
 
+    def replace_pipeline_to_none(cfg):
+        """Recursively iterate over all dataset(or datasets) and set their
+        pipelines to none.Datasets are mean ConcatDataset.
+
+        Recursively terminates only when all dataset(or datasets) have been
+        traversed
+        """
+
+        if cfg.get('dataset', None) is None and cfg.get('datasets',
+                                                        None) is None:
+            return
+        dataset = cfg.dataset if cfg.get('dataset', None) else cfg.datasets
+        if isinstance(dataset, list):
+            for item in dataset:
+                item.pipeline = None
+        elif dataset.get('pipeline', None):
+            dataset.pipeline = None
+        else:
+            replace_pipeline_to_none(dataset)
+
     # 1.Build Dataset
     if args.val_dataset is False:
+        replace_pipeline_to_none(cfg.train_dataloader)
         dataset = DATASETS.build(cfg.train_dataloader.dataset)
-    elif args.val_dataset is True:
+    else:
+        replace_pipeline_to_none(cfg.val_dataloader)
         dataset = DATASETS.build(cfg.val_dataloader.dataset)
 
-    # Determine whether the dataset is ConcatDataset
-    if isinstance(dataset, ConcatDataset):
-        datasets = dataset.datasets
-        data_list = []
-        for idx in range(len(datasets)):
-            datasets_list = datasets[idx].load_data_list()
-            data_list += datasets_list
-    else:
-        data_list = dataset.load_data_list()
+    # Build  lists to store data for all raw data
+    data_list = dataset
 
     # 2.Prepare data
     # Drawing settings