mmscan-devkit v1

mmscan/evaluator/metrics/lang_metric.py

@@ -119,6 +119,11 @@ def em_evaluation(batch_input):
 
 
 class simcse_evaluator:
+    """A class for calculating the simcse similarity score.
+
+    Args:
+        model_path: path to the simcse pretrained model.
+    """
 
     def __init__(self, model_path, eval_bs=500) -> None:
         self.eval_bs = eval_bs
@@ -208,6 +213,11 @@ def evaluation(self, batch_input):
 
 
 class sbert_evaluator:
+    """A class for calculating the sbert similarity score.
+
+    Args:
+        model_path: path to the sbert pretrained model.
+    """
 
     def __init__(self, model_path, eval_bs=500) -> None:
         self.eval_bs = eval_bs

mmscan/evaluator/qa_evaluation.py

@@ -57,6 +57,7 @@ def __init__(self, model_config={}, max_length=256, verbose=True) -> None:
         self.reset()
 
     def reset(self):
+        """Reset the evaluator, clear the buffer and records."""
         self.metric_record = {}
         self.save_results = {}
         self.save_buffer = []

mmscan/evaluator/vg_evaluation.py

@@ -45,6 +45,7 @@ def __init__(self, verbose=True) -> None:
         self.reset()
 
     def reset(self):
+        """Reset the evaluator, clear the buffer and records."""
         self.save_buffer = []
         self.records = []
         self.category_records = {}

mmscan/utils/box_utils.py

@@ -247,6 +247,14 @@ def euler_iou3d_bbox(center1, size1, rot1, center2, size2, rot2):
 
 
 def box_num(box):
+    """Return the number of boxes in a grounp.
+
+    Args:
+        box (list/tuple, tensor): boxes in a grounp.
+
+    Returns:
+        int : the number
+    """
     if isinstance(box, (list, tuple)):
         return box[0].shape[0]
     else:
@@ -261,6 +269,15 @@ def index_box(boxes, indices):
 
 
 def to_9dof_box(box):
+    """Convert a grounp of bounding boxes represented in [center, size, rot]
+    format to 9 DoF format.
+
+    Args:
+        box (list/tuple, tensor): boxes in a grounp.
+
+    Returns:
+        Tensor : 9 DoF format. (num,9)
+    """
     if isinstance(box, (list, tuple)):
         center, size, rotmat = box
         euler = matrix_to_euler_angles(rotmat, 'ZXY')

mmscan/utils/data_io.py

@@ -168,6 +168,14 @@ def reverse_dict(mapping):
         self.mp3d_mapping_trans = reverse_dict(self.mp3d_mapping)
 
     def forward(self, scan_name):
+        """map forward the original scan names to the new names.
+
+        Args:
+            scan_name (str): the original scan name.
+        Returns:
+            str: the new name.
+        """
+
         if 'matterport3d/' in scan_name:
             scan_, region_ = (
                 self.mp3d_mapping[scan_name.split('/')[1]],
@@ -182,6 +190,13 @@ def forward(self, scan_name):
             raise ValueError(f'{scan_name} is not a scan name')
 
     def backward(self, scan_name):
+        """map backward the new names to the original scan names.
+
+        Args:
+            scan_name (str): the new name.
+        Returns:
+            str: the original scan name.
+        """
         if '1mp3d' in scan_name:
             scene1, scene2, region = scan_name.split('_')
             return ('matterport3d/' +

mmscan/utils/lang_utils.py

@@ -71,6 +71,13 @@ def clean_answer(data):
 
 
 def normalize_answer(s):
+    """Help to 'normalize' the answer.
+
+    Args:
+        s (str): the raw answer.
+    Returns:
+        str : the processed sentence.
+    """
 
     def remove_articles(text):
         return re.sub(r'\b(a|an|the)\b', ' ', text)
@@ -207,6 +214,13 @@ def qa_prompt_define():
 
 
 def qa_metric_map(eval_type):
+    """Map the class type to the corresponding Abbrev.
+
+    Args:
+        eval_type (str): the class name.
+    Returns:
+        str : the corresponding Abbrev.
+    """
     if 'Attribute_OO' in eval_type:
         target = 'OOa'
     elif 'Space_OO' in eval_type: