inputs_shape and fps args now required for running face detection

tests/conftest.py

@@ -45,13 +45,20 @@ def test_video_fps():
   fps, *_ = probe_video(TEST_VIDEO_PATH)
   return fps
 
+@pytest.fixture(scope='session')
+def test_video_shape():
+  _, n, w, h, _, _, _ = probe_video(TEST_VIDEO_PATH)
+  return (n, h, w, 3)
+
 @pytest.fixture(scope='session')
 def test_video_faces(request):
   det = FaceDetector(
     max_faces=1, fs=1.0, iou_threshold=0.45, score_threshold=0.9)
   test_video_ndarray = request.getfixturevalue('test_video_ndarray')
   test_video_fps = request.getfixturevalue('test_video_fps')
-  boxes, _ = det(test_video_ndarray, fps=test_video_fps)
+  boxes, _ = det(test_video_ndarray,
+                 inputs_shape=test_video_ndarray.shape,
+                 fps=test_video_fps)
   boxes = (boxes * [test_video_ndarray.shape[2], test_video_ndarray.shape[1], test_video_ndarray.shape[2], test_video_ndarray.shape[1]]).astype(int)
   return boxes[:,0].astype(np.int64)
 

tests/test_ssd.py

@@ -19,6 +19,7 @@
 # SOFTWARE.
 
 import numpy as np
+from prpy.ffmpeg.probe import probe_video
 import pytest
 
 import sys
@@ -138,11 +139,17 @@ def test_FaceDetector(request, file):
     max_faces=2, fs=1.0, iou_threshold=0.45, score_threshold=0.9)
   if file:
     test_video_path = request.getfixturevalue('test_video_path')
-    boxes, info = det(test_video_path)
+    test_video_shape = request.getfixturevalue('test_video_shape')
+    test_video_fps = request.getfixturevalue('test_video_fps')
+    boxes, info = det(inputs=test_video_path,
+                      inputs_shape=test_video_shape,
+                      fps=test_video_fps)
   else:
     test_video_ndarray = request.getfixturevalue('test_video_ndarray')
     test_video_fps = request.getfixturevalue('test_video_fps')
-    boxes, info = det(test_video_ndarray, fps=test_video_fps)
+    boxes, info = det(inputs=test_video_ndarray,
+                      inputs_shape=test_video_ndarray.shape,
+                      fps=test_video_fps)
   assert boxes.shape == (360, 1, 4)
   assert info.shape == (360, 1, 5)
   np.testing.assert_allclose(boxes[0,0],

vitallens/ssd.py

@@ -219,15 +219,15 @@ def __call__(
       self,
       inputs: Tuple[np.ndarray, str],
       inputs_shape: Tuple[tuple, float],
-      fps: float = None
+      fps: float
     ) -> Tuple[np.ndarray, np.ndarray]:
     """Run inference.
 
     Args:
       inputs: The video to analyze. Either a np.ndarray of shape (n_frames, h, w, 3)
         with a sequence of frames in unscaled uint8 RGB format, or a path to a video file.
       inputs_shape: The shape of the input video as (n_frames, h, w, 3)
-      fps: Sampling frequency of the input video. Required if type(video) == np.ndarray.
+      fps: Sampling frequency of the input video.
     Returns:
       boxes: Detected face boxes in relative flat point form (n_frames, n_faces, 4)
       info: Tuple (idx, scanned, scan_found_face, interp_valid, confidence) (n_frames, n_faces, 5)