Merge branch 'master' into dev

example1_basic_pipeline.py

@@ -32,6 +32,9 @@ def main():
         # 步骤 2.1: 获取并拼接图像 (必要步骤)
         sensor.get_img() 
         print("img_size_raw:", sensor.img_size_raw)
+        if sensor.detect_motion():
+            print("motion detected")
+            break
         # 步骤 2.2: 计算形变场 (必要步骤)
         sensor.compute_deformation()
         # 步骤 2.3: 计算触碰点 

src/orisys/sensor.py

@@ -96,6 +96,7 @@ class Sensor:
         self.img = None
         self.img_size_raw = None
         self.img_filtered = None
+        self.prev_img = None
         self.flow = None
         self.vnormal = None
         self.vshear = None
@@ -185,23 +186,37 @@ class Sensor:
         # Resize
         img = cv2.resize(img, tuple(self._config_resolution_stitch), interpolation=cv2.INTER_CUBIC)
         
-        # Temporal filtering (noise reduction)
+        # # Temporal filtering (noise reduction)
-        alpha = 0.7
+        # alpha = 0.7
-        if self.img_filtered is None:
+        # if self.img_filtered is None:
-            self.img_filtered = img.astype(np.float32)
+        #     self.img_filtered = img.astype(np.float32)
-        else:
+        # else:
-            self.img_filtered = alpha * img + (1 - alpha) * self.img_filtered
+        #     self.img_filtered = alpha * img + (1 - alpha) * self.img_filtered
-        
+        # Update previous image
-        self.img = self.img_filtered.astype(np.uint8)
+        if self.mirror:
+            img = cv2.flip(img, 1)
+
+        if self.img is not None:
+            self.prev_img = self.img.copy()
+
+        self.img = img.astype(np.uint8)
+
+        if self.prev_img is None:
+            self.prev_img = img.copy()
 
         if log_timing:
             timings['total'] = (time.perf_counter() - t_start) * 1000
             self._print_timings("get_img", timings)
-        if self.mirror:
+
-            self.img = cv2.flip(self.img, 1)
             
         return self.img.copy()
 
+    def detect_motion(self, threshold=10):
+        if self.prev_img is None:
+            return False
+        diff = cv2.absdiff(self.img, self.prev_img)
+        return diff.mean() > threshold
+
     def compute_deformation(self):
         """
         Compute optical flow and decompose into force components.