Add pull request arabian9ts#20 from original repo

model/computation.py

@@ -7,41 +7,26 @@
 
 import numpy as np
 
-def intersection(rect1, rect2):
-    """
-    intersecton of units
-    compute boarder line top, left, right and bottom.
-    rect is defined as [ top_left_x, top_left_y, width, height ]
-    """
-    top = max(rect1[1], rect2[1])
-    left = max(rect1[0], rect2[0])
-    right = min(rect1[0] + rect1[2], rect2[0] + rect2[2])
-    bottom = min(rect1[1] + rect1[3], rect2[1] + rect2[3])
-
-    if bottom > top and right > left:
-        return (bottom-top)*(right-left)
-
-    return 0
-
-
 def jaccard(rect1, rect2):
     """
     Jaccard index.
     Jaccard index is defined as #(A∧B) / #(A∨B)
     """
-    rect1_ = [x if x >= 0 else 0 for x in rect1]
-    rect2_ = [x if x >= 0 else 0 for x in rect2]
-    s = rect1_[2]*rect1_[3] + rect2_[2]*rect2_[3]
-
-    # rect1 and rect2 => A∧B
-    intersect = intersection(rect1_, rect2_)
-
-    # rect1 or rect2 => A∨B
-    union = s - intersect
-
-    # A∧B / A∨B
-    return intersect / union
-
+    # determine the (x, y)-coordinates of the intersection rectangle
+    xA = max(rect1[0], rect2[0])
+    yA = max(rect1[1], rect2[1])
+    xB = min(rect1[2], rect2[2])
+    yB = min(rect1[3], rect2[3])
+    # compute the area of intersection rectangle
+    interArea = max(0, xB - xA + 1) * max(0, yB - yA + 1)
+    # compute the area of both the prediction and ground-truth
+    # rectangles
+    boxAArea = (rect1[2] - rect1[0] + 1) * (rect1[3] - rect1[1] + 1)
+    boxBArea = (rect2[2] - rect2[0] + 1) * (rect2[3] - rect2[1] + 1)
+    # return the intersection over union by taking the intersection
+    # area and dividing it by the sum of prediction + ground-truth
+    # areas - the intersection area
+    return interArea / float(boxAArea + boxBArea - interArea)
 
 def corner2center(rect):
     """
@@ -88,4 +73,4 @@ def convert2wh(rect):
         output format is...
         [ top_left_x, top_left_y, width, height ]
     """
-    return np.array([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]])