fixed new sample cannot detect boxes due to filter

src/orisys/Stitcher.py

@@ -8,9 +8,14 @@ class Stitcher:
 
     def __init__(self,isstitch=False, n=[3,3], index=np.array([1,2,3,6,7,8,11,12,13])):
 
-            # Settings
+        # Settings
         self.isstitch = isstitch
 
+        # Find Boxes Related
+        self.min_area_frac = 0.01
+        self.max_area_frac = 0.05
+        self.max_aspect_ratio = 100
+
         # stitch related
         self.stitch_valid = False
         self.boxes = self.units = None
@@ -21,6 +26,7 @@ class Stitcher:
         self.nominal_ov_pos=100 
         self.margin=10
         self.bound=self.nominal_ov_pos - self.margin
+        
         # for sensor 1
         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)]
  
@@ -542,7 +548,7 @@ class Stitcher:
     
     
     
-    def __filter_boxes_by_size(self, boxes, img_shape, min_area_frac=0.018, max_area_frac=0.035):
+    def __filter_boxes_by_size(self, boxes, img_shape):
         """
         Remove boxes that are too small or too large relative to the image.
         - boxes: list of (x,y,w,h)
@@ -552,12 +558,12 @@ class Stitcher:
         """
         h, w = img_shape
         img_area = h * w
-        min_area = img_area * float(min_area_frac)
-        max_area = img_area * float(max_area_frac)
+        min_area = img_area * float(self.min_area_frac)
+        max_area = img_area * float(self.max_area_frac)
         filtered = []
         for (x,y,ww,hh) in boxes:
             area = ww * hh
-            if area < min_area or area > max_area or (abs(ww - hh) > 20):
+            if area < min_area or area > max_area or (abs(ww - hh) > self.max_aspect_ratio):
                 continue
             filtered.append((x,y,ww,hh))
         return filtered