fix: tweak

matcher.py

@@ -121,7 +121,7 @@ class label loss is evaled by loss_conf
                 matches[near_index] = Box(gt_box, gt_label)
                 pos += 1
 
-        indicies = self.extract_highest_indicies(pred_confs, pos*3)
+        indicies = self.extract_highest_indicies(pred_confs, pos*5)
 
         for i in indicies:
             if matches[i] is None and classes-1 != np.argmax(pred_confs[i]):

model/computation.py

@@ -5,6 +5,7 @@
 author: arabian9ts
 """
 
+import numpy as np
 
 def intersection(rect1, rect2):
     """
@@ -49,7 +50,7 @@ def corner2center(rect):
     center_x = (2 * rect[0] + rect[2]) * 0.5
     center_y = (2 * rect[1] + rect[3]) * 0.5
 
-    return [center_x, center_y, abs(rect[2]), abs(rect[3])]
+    return np.array([center_x, center_y, abs(rect[2]), abs(rect[3])])
 
 
 def center2corner(rect):
@@ -59,7 +60,7 @@ def center2corner(rect):
     corner_x = rect[0] - rect[2] * 0.5
     corner_y = rect[1] - rect[3] * 0.5
 
-    return [corner_x, corner_y, abs(rect[2]), abs(rect[3])]
+    return np.array([corner_x, corner_y, abs(rect[2]), abs(rect[3])])
 
 
 def convert2diagonal_points(rect):
@@ -73,7 +74,7 @@ def convert2diagonal_points(rect):
         output format is...
         [ top_left_x, top_left_y, bottom_right_x, bottom_right_y ]
     """
-    return [rect[0], rect[1], rect[0]+rect[2], rect[1]+rect[3]]
+    return np.array([rect[0], rect[1], rect[0]+rect[2], rect[1]+rect[3]])
 
 
 def convert2wh(rect):
@@ -87,4 +88,4 @@ def convert2wh(rect):
         output format is...
         [ top_left_x, top_left_y, width, height ]
     """
-    return [rect[0], rect[1], rect[2]-rect[0], rect[3]-rect[1]]
+    return np.array([rect[0], rect[1], rect[2]-rect[0], rect[3]-rect[1]])

model/default_box.py

@@ -65,7 +65,7 @@ def generate_boxes(fmap_shapes):
                 for i, ratio in enumerate(ratios):
                     s = s_k
 
-                    if 0 == i:
+                    if 1.0 == s:
                         s = np.sqrt(s_k*s_k1)
 
                     box_width = s * np.sqrt(ratio)

model/policy.py

@@ -10,15 +10,15 @@
 classes = 21
 
 # the number of boxes per feature map
-boxes = [6, 3, 6, 3, 6, 3,]
+boxes = [4, 6, 6, 6, 6, 6,]
 
 # default box ratios
 # each length should be matches boxes[index]
 box_ratios = [
+    [1.0, 1.0, 2.0, 1.0/2.0],
+    [1.0, 1.0, 2.0, 1.0/2.0, 3.0, 1.0/3.0],
+    [1.0, 1.0, 2.0, 1.0/2.0, 3.0, 1.0/3.0],
     [1.0, 1.0, 2.0, 1.0/2.0, 3.0, 1.0/3.0],
-    [1.0, 2.0, 1.0/2.0],
     [1.0, 1.0, 2.0, 1.0/2.0, 3.0, 1.0/3.0],
-    [1.0, 2.0, 1.0/2.0],
     [1.0, 1.0, 2.0, 1.0/2.0, 3.0, 1.0/3.0],
-    [1.0, 2.0, 1.0/2.0],
 ]