display without edge + depth map smoothing

demo.py

@@ -4,7 +4,7 @@ import cv2
 import numpy as np
 from orisys import Sensor
 
-def draw_arrows_fade(img, flow, depth, depth_scale=0.5, grid_spacing=40, arrow_scale=1.0, threshold=5.0):
+def draw_arrows_fade(img, flow, depth, depth_scale=0.5, grid_spacing=20, arrow_scale=1.0, threshold=5.0):
     """
     Draw optical flow arrows on image with transparency based on magnitude.
     
@@ -18,10 +18,11 @@ def draw_arrows_fade(img, flow, depth, depth_scale=0.5, grid_spacing=40, arrow_s
     Returns:
         Image with arrows drawn, blended with original image
     """
-    
+
     depth_img = cv2.applyColorMap(((depth+1)*depth_scale* 255.0).astype('uint8'), cv2.COLORMAP_HOT)
     # Make a copy of the image
     img_copy = depth_img.copy()
+
     
     # Convert grayscale to BGR if needed
     if len(img_copy.shape) == 2 or img_copy.shape[2] == 1:
@@ -132,9 +133,9 @@ def main():
     global start_time
     
     # 打开视频
-    sensor1 = Sensor("./s1.mp4",isstitch=True,cuda = True,verbose = True)
+    # sensor1 = Sensor("./s1.mp4",isstitch=True,cuda = True,verbose = True)
     # 打开摄像头
-    # sensor1 = Sensor(0,isstitch=True,cuda = True,verbose = True)
+    sensor1 = Sensor(0,isstitch=True,cuda = True,verbose = True)
     while True:
         sensor1.get_img() # 提取并拼接复眼图像
         sensor1.compute_deformation() # 计算形变和分解
@@ -145,7 +146,20 @@ def main():
         fps, fn, fx, fy, flow, depth = sensor1.read_info(sensor1.info.FPS, sensor1.info.FNORMAL, sensor1.info.FSHEARX, sensor1.info.FSHEARY, sensor1.info.VRAW, sensor1.info.DEPTH)
         arrows = draw_arrows_fade(sensor1.img, flow, depth)
         print(fps,np.min(depth),np.mean(depth))
-        cv2.imshow("Deformation", arrows)
+        
+        # Crop edges (15 pixels from each side) - only if image is large enough
+        h, w = arrows.shape[:2]
+        if h > 30 and w > 30:
+            cv2.imshow("Deformation", arrows[15:-15, 15:-15, :])
+        else:
+            cv2.imshow("Deformation", arrows)
+
+        # Crop raw image edges if large enough
+        h_raw, w_raw = sensor1.img.shape[:2]
+        if h_raw > 30 and w_raw > 30:
+            cv2.imshow("raw", sensor1.img[15:-15, 15:-15])
+        else:
+            cv2.imshow("raw", sensor1.img)
 
         key = cv2.waitKey(1)
         if key & 0xFF == ord("q"):