Read videos from HIM project files

data/hands.py

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+import os.path
+from collections import OrderedDict
+from glob import glob
+from typing import Generator, Union, Tuple
+
+import cv2
+import numpy as np
+import pandas as pd
+
+HandMask = np.ndarray
+HandMaskMaybeWithFileName = Union[HandMask, Tuple[HandMask, str]]
+
+_CSV_FILE_NAME = 'data.csv'
+_CSV_COLUMNS = OrderedDict([('frame_number', int),
+                            ('hand_id', int),
+                            ('x', float),
+                            ('y', float),
+                            ('direction_x', float),
+                            ('direction_y', float),
+                            ('distance', float),
+                            ('detected', bool),
+                            ('frames_without_detection', int)])
+
+_HAND_MASK_FILE_GLOB = 'hand_labels_*.png'
+
+
+def load_coordinates(data_csv_path: str) -> pd.DataFrame:
+    data_csv_path = os.path.abspath(data_csv_path)
+    hand_data = pd.read_csv(data_csv_path,
+                            sep=',',
+                            header=None,
+                            names=_CSV_COLUMNS.keys(),
+                            dtype=_CSV_COLUMNS)
+
+    return hand_data
+
+
+def load_hand_masks(data_dir_path: str,
+                    return_file_names: bool = False) -> Generator[HandMaskMaybeWithFileName, None, None]:
+    data_dir_path = os.path.abspath(data_dir_path)
+
+    mask_files = glob(os.path.join(data_dir_path, _HAND_MASK_FILE_GLOB))
+    mask_files = sorted(mask_files)
+
+    for mf in mask_files:
+        hand_mask = cv2.imread(mf, cv2.IMREAD_UNCHANGED)
+
+        if return_file_names:
+            yield hand_mask, mf
+        else:
+            yield hand_mask
+
+
+class RecordingHandTracking:
+    def __init__(self, path: str):
+        self._path = os.path.abspath(path)
+
+    def hand_coordinates(self) -> pd.DataFrame:
+        return load_coordinates(os.path.join(self._path, _CSV_FILE_NAME))
+
+    def hand_mask_sequence(self, return_file_names: bool = False) -> Generator[HandMaskMaybeWithFileName, None, None]:
+        return load_hand_masks(self._path, return_file_names)
+
+
+        for mf in mask_files:
+            hand_mask = cv2.imread(mf, cv2.IMREAD_UNCHANGED)
+
+            if return_file_names:
+                yield hand_mask, mf
+            else:
+                yield hand_mask