Update prpy to 0.2.12

README.md

@@ -118,7 +118,7 @@ The estimation results are returned as a `list`. It contains a `dict` for each d
     <same structure for face 2 if present>
   },
   ...
-  ]
+]
 ```
 
 If the video is long enough and `estimate_running_vitals=True`, the results additionally contain running vitals:

pyproject.toml

@@ -22,7 +22,7 @@ dependencies = [
     "importlib_resources",
     "numpy",
     "onnxruntime",
-    "prpy[ffmpeg,numpy_min]==0.2.10",
+    "prpy[ffmpeg,numpy_min]==0.2.12",
     "python-dotenv",
     "pyyaml",
     "requests",

vitallens/methods/simple_rppg_method.py

@@ -54,7 +54,7 @@ def pulse_filter(self,
     pass
   def __call__(
       self,
-      frames: Union[np.ndarray, str],
+      frames: Union[np.ndarray, str], # TODO: Rename to `video`
       faces: np.ndarray,
       fps: float,
       override_fps_target: float = None,
@@ -63,7 +63,8 @@ def __call__(
     """Estimate pulse signal from video frames using the subclass algorithm.
 
     Args:
-      frames: The video frames. Shape (n_frames, h, w, c)
+      frames: The video to analyze. Either a np.ndarray of shape (n_frames, h, w, 3)
+        in unscaled uint8 RGB format, or a path to a video file.
       faces: The face detection boxes as np.int64. Shape (n_frames, 4) in form (x0, y0, x1, y1)
       fps: The rate at which video was sampled.
       override_fps_target: Override the method's default inference fps (optional).
@@ -73,7 +74,7 @@ def __call__(
       unit: A dictionary with the units of the estimated vital signs.
       conf: A dictionary with the confidences of the estimated vital signs.
       note: A dictionary with notes on the estimated vital signs.
-      live: Dummy live confidence estimation (set to always 1). Shape (1, n_frames)
+      live: Dummy live confidence estimation (set to always 1). Shape (n_frames,)
     """
     # Compute temporal union of ROIs
     u_roi = merge_faces(faces)

vitallens/utils.py

@@ -138,7 +138,7 @@ def parse_video_inputs(
       try:
         fps_, n, w_, h_, _, _, r, i = probe_video(video)
         if fps is None: fps = fps_
-        if roi is not None: roi = (int(roi[0]), int(roi[1]), int(roi[2]-roi[0]), int(roi[3]-roi[1]))
+        if roi is not None: roi = (int(roi[0]), int(roi[1]), int(roi[2]), int(roi[3]))
         if isinstance(target_size, tuple): target_size = (target_size[1], target_size[0])
         if abs(r) == 90: h = w_; w = h_
         else: h = h_; w = w_