Make motion detection less sensitive by ignoring minor (<5%) changes.

frigate/motion/improved_motion.py

@@ -121,13 +121,13 @@ class ImprovedMotionDetector(MotionDetector):
         if self.save_images:
             contrasted_saved = resized_frame.copy()
 
+        resized_frame = gaussian_filter(resized_frame, sigma=1, radius=self.blur_radius)
+
         # mask frame
-        # this has to come after contrast improvement
+        # this has to come after contrast improvement and masking to avoid the mask bleeding into non-masked area.
         # Setting masked pixels to zero, to match the average frame at startup
         resized_frame[self.mask] = [0]
 
-        resized_frame = gaussian_filter(resized_frame, sigma=1, radius=self.blur_radius)
-
         if self.save_images:
             blurred_saved = resized_frame.copy()
 
@@ -194,10 +194,11 @@ class ImprovedMotionDetector(MotionDetector):
 
         # once the motion is less than 5% and the number of contours is < 4, assume its calibrated
         if pct_motion < 0.05 and len(motion_boxes) <= 4:
+            motion_boxes = []  # ignore small movements
             self.calibrating = False
 
         # if calibrating or the motion contours are > 80% of the image area (lightning, ir, ptz) recalibrate
-        if self.calibrating or pct_motion > self.config.lightning_threshold:
+        if not self.calibrating and pct_motion > self.config.lightning_threshold:
             self.calibrating = True
 
         if self.save_images:

frigate/test/test_motion.py

@@ -51,6 +51,9 @@ class TestMotion(unittest.TestCase):
                 default_motion_config,
                 [[190, 307]],
             ),
+            TestMotionVideo(
+                "testdata/test_motion_video-3.mp4", default_mask, default_motion_config
+            ),
         ]
 
     def get_motion_detector(self, test_clip):