added self.img filter

src/orisys/sensor.py

@@ -70,6 +70,7 @@ class Sensor:
             ret, frame = self.cap.read()
             if not ret:
                 time.sleep(1)
+            raise RuntimeError("Could not open video source")
         if self.verbose:
             print("Video source connected.")
         
@@ -85,6 +86,7 @@ class Sensor:
         self.n_boxes = None
         self.stitch_calibration = []
         self.img = self.flow = self.normal = self.shear = self.force = self.depth = None
+        self.img_filtered = None  # For temporal noise reduction
         self.fnormal=self.fshearx=self.fsheary=self.ftor=0.0
         self.imgupdate = self.vupdate = False
         self.pos_default = [(260, 56), (577, 62), (897, 69), (1214, 75), (1530, 81), (256, 391), (570, 397), (889, 403), (1208, 409), (1523, 416), (248, 724), (563, 730), (882, 738), (1201, 743), (1516, 751)]
@@ -131,7 +133,21 @@ class Sensor:
         self.__stitcher.get_stitch_unit(gray_frame)
         self.__get_tiles(gray_frame)
         img = np.ascontiguousarray(self.__stitcher.stitch_rt_optimized())
-        self.img = cv2.resize(img, (400, 400), interpolation=cv2.INTER_CUBIC)
+        
+        img_resized = cv2.resize(img, (400, 400), interpolation=cv2.INTER_CUBIC)
+        
+        # Apply temporal noise reduction using exponential moving average
+        # Blend current frame with previous filtered frame to reduce temporal noise
+        alpha = 0.7  # Weight for current frame (0.7 = 70% current, 30% previous)
+        if self.img_filtered is None:
+            # First frame: no previous frame to blend with
+            self.img_filtered = img_resized.astype(np.float32)
+        else:
+            # Temporal filtering: blend current frame with previous filtered frame
+            self.img_filtered = alpha * img_resized.astype(np.float32) + (1 - alpha) * self.img_filtered
+        
+        # Convert back to uint8
+        self.img = self.img_filtered.astype(np.uint8)
         self.imgupdate = True
         return self.img