Copy-Paste augmentation for YOLOv5 (#3845)

* Copy-paste augmentation initial commit

* if any segments

* Add obscuration rejection

* Add copy_paste hyperparameter

* Update comments

utils/metrics.py

@@ -1,9 +1,9 @@
 # Model validation metrics
 
-import math
 import warnings
 from pathlib import Path
 
+import math
 import matplotlib.pyplot as plt
 import numpy as np
 import torch
@@ -253,6 +253,30 @@ def box_iou(box1, box2):
     return inter / (area1[:, None] + area2 - inter)  # iou = inter / (area1 + area2 - inter)
 
 
+def bbox_ioa(box1, box2, eps=1E-7):
+    """ Returns the intersection over box2 area given box1, box2. Boxes are x1y1x2y2
+    box1:       np.array of shape(4)
+    box2:       np.array of shape(nx4)
+    returns:    np.array of shape(n)
+    """
+
+    box2 = box2.transpose()
+
+    # Get the coordinates of bounding boxes
+    b1_x1, b1_y1, b1_x2, b1_y2 = box1[0], box1[1], box1[2], box1[3]
+    b2_x1, b2_y1, b2_x2, b2_y2 = box2[0], box2[1], box2[2], box2[3]
+
+    # Intersection area
+    inter_area = (np.minimum(b1_x2, b2_x2) - np.maximum(b1_x1, b2_x1)).clip(0) * \
+                 (np.minimum(b1_y2, b2_y2) - np.maximum(b1_y1, b2_y1)).clip(0)
+
+    # box2 area
+    box2_area = (b2_x2 - b2_x1) * (b2_y2 - b2_y1) + eps
+
+    # Intersection over box2 area
+    return inter_area / box2_area
+
+
 def wh_iou(wh1, wh2):
     # Returns the nxm IoU matrix. wh1 is nx2, wh2 is mx2
     wh1 = wh1[:, None]  # [N,1,2]