create api module for opendbm movement api

opendbm/api_lib/movement/api.py

@@ -0,0 +1,105 @@
+import os
+import shutil
+import tempfile
+from collections import OrderedDict
+
+from opendbm.api_lib.model import VideoModel
+from opendbm.api_lib.util import check_isfile
+from opendbm.dbm_lib.controller import process_feature as pf
+
+from ._eye_blink import EyeBlink
+from ._eye_gaze import EyeGaze
+from ._facial_tremor import FacialTremor
+from ._head_movement import HeadMovement
+from ._vocal_tremor import VocalTremor
+
+
+class Movement(VideoModel):
+    def __init__(self):
+        super().__init__()
+        self._eye_blink = EyeBlink()
+        self._eye_gaze = EyeGaze()
+        self._facial_tremor = FacialTremor()
+        self._head_movement = HeadMovement()
+        self._vocal_tremor = VocalTremor()
+
+        self._models = OrderedDict(
+            {
+                "eye_blink": self._eye_blink,
+                "eye_gaze": self._eye_gaze,
+                "facial_tremor": self._facial_tremor,
+                "head_movement": self._head_movement,
+                "vocal_tremor": self._vocal_tremor,
+            }
+        )
+
+    def fit(self, path):
+        """Fit a file in filepath to OpenFace Model. Make sure to set the Docker to be active first.
+        For installation, see https://teebid.github.io/aicure_opendbm/docs/openface-docker-installation
+
+        Parameters
+        ----------
+        path : string,
+            File Path of MP4/MOV file.
+
+        """
+        check_isfile(path)
+        result_path, result_path_lmk, bn = super()._fit(path, "movement")
+        wav_path = pf.audio_to_wav(path, tmp=True)
+
+        for k, v in self._models.items():
+            if k in ["eye_gaze", "head_movement"]:
+                v._df = v._fit_transform(result_path)
+            elif k == "facial_tremor":
+                v._df = v._fit_transform(result_path_lmk)
+            elif k == "vocal_tremor":
+                v._df = v._fit_transform(wav_path)
+            else:
+                v._df = v._fit_transform(path)
+        shutil.rmtree(f"{tempfile.gettempdir()}/{bn}/")
+        shutil.rmtree(f"{tempfile.gettempdir()}/{bn}_landmark_output/")
+        os.remove(wav_path)
+
+    def get_eye_blink(self):
+        """
+        Get the model object of Eye Blink
+        Returns:
+        self: object
+        """
+        return self._eye_blink
+
+    def get_eye_gaze(self):
+        """
+        Get the model object of Eye Gaze
+        Returns:
+        self: object
+            Model Object
+        """
+        return self._eye_gaze
+
+    def get_facial_tremor(self):
+        """
+        Get the model object of Facial Tremor
+        Returns:
+        self: object
+            Model Object
+        """
+        return self._facial_tremor
+
+    def get_head_movement(self):
+        """
+        Get the model object of Head Movement
+        Returns:
+        self: object
+            Model Object
+        """
+        return self._head_movement
+
+    def get_vocal_tremor(self):
+        """
+        Get the model object of Vocal Tremor
+        Returns:
+        self: object
+            Model Object
+        """
+        return self._vocal_tremor