Relax requirement for frame number

movement/io/load_bboxes.py

@@ -321,7 +321,9 @@ def from_via_tracks_file(
     logger.debug(f"Validated VIA tracks .csv file {via_file.path}.")
 
     # Create an xarray.Dataset from the data
-    bboxes_arrays = _numpy_arrays_from_via_tracks_file(via_file.path)
+    bboxes_arrays = _numpy_arrays_from_via_tracks_file(
+        via_file.path, via_file.frame_regexp
+    )
     ds = from_numpy(
         position_array=bboxes_arrays["position_array"],
         shape_array=bboxes_arrays["shape_array"],
@@ -347,7 +349,9 @@ def from_via_tracks_file(
     return ds
 
 
-def _numpy_arrays_from_via_tracks_file(file_path: Path) -> dict:
+def _numpy_arrays_from_via_tracks_file(
+    file_path: Path, frame_regexp: str
+) -> dict:
     """Extract numpy arrays from the input VIA tracks .csv file.
 
     The extracted numpy arrays are returned in a dictionary with the following
@@ -370,6 +374,12 @@ def _numpy_arrays_from_via_tracks_file(file_path: Path) -> dict:
     file_path : pathlib.Path
         Path to the VIA tracks .csv file containing the bounding boxes' tracks.
 
+    frame_regexp : str
+        Regular expression pattern to extract the frame number from the
+        filename. The frame number is expected to be encoded in the filename
+        as an integer number led by at least one zero, followed by the file
+        extension.
+
     Returns
     -------
     dict
@@ -379,7 +389,7 @@ def _numpy_arrays_from_via_tracks_file(file_path: Path) -> dict:
     # Extract 2D dataframe from input data
     # (sort data by ID and frame number, and
     # fill empty frame-ID pairs with nans)
-    df = _df_from_via_tracks_file(file_path)
+    df = _df_from_via_tracks_file(file_path, frame_regexp)
 
     # Compute indices of the rows where the IDs switch
     bool_id_diff_from_prev = df["ID"].ne(df["ID"].shift())  # pandas series
@@ -417,7 +427,9 @@ def _numpy_arrays_from_via_tracks_file(file_path: Path) -> dict:
     return array_dict
 
 
-def _df_from_via_tracks_file(file_path: Path) -> pd.DataFrame:
+def _df_from_via_tracks_file(
+    file_path: Path, frame_regexp: str
+) -> pd.DataFrame:
     """Load VIA tracks .csv file as a dataframe.
 
     Read the VIA tracks .csv file as a pandas dataframe with columns:
@@ -433,6 +445,10 @@ def _df_from_via_tracks_file(file_path: Path) -> pd.DataFrame:
     empty frames are filled in with NaNs. The coordinates of the bboxes
     are assumed to be in the image coordinate system (i.e., the top-left
     corner of a bbox is its corner with minimum x and y coordinates).
+
+    The frame number is extracted from the filename using the provided
+    regexp if it is not defined as a 'file_attribute' in the VIA tracks .csv
+    file.
     """
     # Read VIA tracks .csv file as a pandas dataframe
     df_file = pd.read_csv(file_path, sep=",", header=0)
@@ -443,7 +459,9 @@ def _df_from_via_tracks_file(file_path: Path) -> pd.DataFrame:
             "ID": _via_attribute_column_to_numpy(
                 df_file, "region_attributes", ["track"], int
             ),
-            "frame_number": _extract_frame_number_from_via_tracks_df(df_file),
+            "frame_number": _extract_frame_number_from_via_tracks_df(
+                df_file, frame_regexp
+            ),
             "x": _via_attribute_column_to_numpy(
                 df_file, "region_shape_attributes", ["x"], float
             ),
@@ -508,7 +526,7 @@ def _extract_confidence_from_via_tracks_df(df) -> np.ndarray:
     return bbox_confidence
 
 
-def _extract_frame_number_from_via_tracks_df(df) -> np.ndarray:
+def _extract_frame_number_from_via_tracks_df(df, frame_regexp) -> np.ndarray:
     """Extract frame numbers from the VIA tracks input dataframe.
 
     Parameters
@@ -517,14 +535,20 @@ def _extract_frame_number_from_via_tracks_df(df) -> np.ndarray:
         The VIA tracks input dataframe is the one obtained from
         ``df = pd.read_csv(file_path, sep=",", header=0)``.
 
+    frame_regexp : str
+        Regular expression pattern to extract the frame number from the
+        filename. The frame number is expected to be encoded in the filename
+        as an integer number led by at least one zero, followed by the file
+        extension.
+
     Returns
     -------
     np.ndarray
         A numpy array of size (n_frames, ) containing the frame numbers.
         In the VIA tracks .csv file, the frame number is expected to be
         defined as a 'file_attribute' , or encoded in the filename as an
-        integer number led by at least one zero, between "_" and ".", followed
-        by the file extension.
+        integer number led by at least one zero, followed by the file
+        extension.
 
     """
     # Extract frame number from file_attributes if exists
@@ -538,10 +562,9 @@ def _extract_frame_number_from_via_tracks_df(df) -> np.ndarray:
         )
     # Else extract from filename
     else:
-        pattern = r"_(0\d*)\.\w+$"
         list_frame_numbers = [
-            int(re.search(pattern, f).group(1))  # type: ignore
-            if re.search(pattern, f)
+            int(re.search(frame_regexp, f).group(1))  # type: ignore
+            if re.search(frame_regexp, f)
             else np.nan
             for f in df["filename"]
         ]

movement/validators/files.py

@@ -234,6 +234,11 @@ class ValidVIATracksCSV:
     ----------
     path : pathlib.Path
         Path to the VIA tracks .csv file.
+    frame_regexp : str
+        Regular expression pattern to extract the frame number from the
+        filename. By default, the frame number is expected to be encoded in
+        the filename as an integer number led by at least one zero, followed
+        by the file extension.
 
     Raises
     ------
@@ -243,6 +248,7 @@ class ValidVIATracksCSV:
     """
 
     path: Path = field(validator=validators.instance_of(Path))
+    frame_regexp: str = r"(0\d*)\.\w+$"
 
     @path.validator
     def _file_contains_valid_header(self, attribute, value):
@@ -281,8 +287,8 @@ def _file_contains_valid_frame_numbers(self, attribute, value):
           files.
 
         If the frame number is included as part of the image file name, then
-        it is expected as an integer led by at least one zero, between "_" and
-        ".", followed by the file extension.
+        it is expected as an integer led by at least one zero, followed by the
+        file extension.
 
         """
         df = pd.read_csv(value, sep=",", header=0)
@@ -309,10 +315,8 @@ def _file_contains_valid_frame_numbers(self, attribute, value):
 
         # else: extract frame number from filename.
         else:
-            pattern = r"_(0\d*)\.\w+$"
-
             for f_i, f in enumerate(df["filename"]):
-                regex_match = re.search(pattern, f)
+                regex_match = re.search(self.frame_regexp, f)
                 if regex_match:  # if there is a pattern match
                     list_frame_numbers.append(
                         int(regex_match.group(1))  # type: ignore