refine repo structure

detection/RetinaFace/rcnn/processing/nms.py

@@ -0,0 +1,67 @@
+import numpy as np
+from ..cython.cpu_nms import cpu_nms
+try:
+    from ..cython.gpu_nms import gpu_nms
+except ImportError:
+    gpu_nms = None
+
+
+def py_nms_wrapper(thresh):
+    def _nms(dets):
+        return nms(dets, thresh)
+
+    return _nms
+
+
+def cpu_nms_wrapper(thresh):
+    def _nms(dets):
+        return cpu_nms(dets, thresh)
+
+    return _nms
+
+
+def gpu_nms_wrapper(thresh, device_id):
+    def _nms(dets):
+        return gpu_nms(dets, thresh, device_id)
+
+    if gpu_nms is not None:
+        return _nms
+    else:
+        return cpu_nms_wrapper(thresh)
+
+
+def nms(dets, thresh):
+    """
+    greedily select boxes with high confidence and overlap with current maximum <= thresh
+    rule out overlap >= thresh
+    :param dets: [[x1, y1, x2, y2 score]]
+    :param thresh: retain overlap < thresh
+    :return: indexes to keep
+    """
+    x1 = dets[:, 0]
+    y1 = dets[:, 1]
+    x2 = dets[:, 2]
+    y2 = dets[:, 3]
+    scores = dets[:, 4]
+
+    areas = (x2 - x1 + 1) * (y2 - y1 + 1)
+    order = scores.argsort()[::-1]
+
+    keep = []
+    while order.size > 0:
+        i = order[0]
+        keep.append(i)
+        xx1 = np.maximum(x1[i], x1[order[1:]])
+        yy1 = np.maximum(y1[i], y1[order[1:]])
+        xx2 = np.minimum(x2[i], x2[order[1:]])
+        yy2 = np.minimum(y2[i], y2[order[1:]])
+
+        w = np.maximum(0.0, xx2 - xx1 + 1)
+        h = np.maximum(0.0, yy2 - yy1 + 1)
+        inter = w * h
+        ovr = inter / (areas[i] + areas[order[1:]] - inter)
+
+        inds = np.where(ovr <= thresh)[0]
+        order = order[inds + 1]
+
+    return keep