Upload box_overlaps.py (#9)

- Upload box_overlaps.py (f517391923c50393890bb70ffc73b6d4f8cc2b93)


Co-authored-by: Hongyang Wei <hongywei@users.noreply.huggingface.co>

widerface_evaluate/box_overlaps.py

@@ -0,0 +1,41 @@
+import numpy as np
+
+def bbox_overlaps(boxes, query_boxes):
+    """
+    Parameters
+    ----------
+    boxes: (N, 4) ndarray of float
+    query_boxes: (K, 4) ndarray of float
+    Returns
+    -------
+    overlaps: (N, K) ndarray of overlap between boxes and query_boxes
+    """
+    N = boxes.shape[0]
+    K = query_boxes.shape[0]
+    overlaps = np.zeros((N, K), dtype=np.float)
+    
+    box_area = (
+        (query_boxes[:, 2] - query_boxes[:, 0] + 1) *
+        (query_boxes[:, 3] - query_boxes[:, 1] + 1)
+    )
+    
+    for n in range(N):
+        iw = (
+            np.maximum(0, np.minimum(boxes[n, 2], query_boxes[:, 2]) -
+                       np.maximum(boxes[n, 0], query_boxes[:, 0]) + 1)
+        )
+        
+        ih = (
+            np.maximum(0, np.minimum(boxes[n, 3], query_boxes[:, 3]) -
+                       np.maximum(boxes[n, 1], query_boxes[:, 1]) + 1)
+        )
+        
+        ua = (
+            (boxes[n, 2] - boxes[n, 0] + 1) *
+            (boxes[n, 3] - boxes[n, 1] + 1) +
+            box_area - iw * ih
+        )
+        
+        overlaps[n, :] = np.where((iw > 0) & (ih > 0), iw * ih / ua, 0)
+    
+    return overlaps