def py_nms(boxes, scores, max_boxes=50, iou_thresh=0.5):
    """
    Pure Python NMS baseline.

    Arguments: boxes: shape of [-1, 4], the value of '-1' means that dont know the
                      exact number of boxes
               scores: shape of [-1,]
               max_boxes: representing the maximum of boxes to be selected by non_max_suppression
               iou_thresh: representing iou_threshold for deciding to keep boxes
    """
    assert boxes.shape[1] == 4 and len(scores.shape) == 1

    x1 = boxes[:, 0]
    y1 = boxes[:, 1]
    x2 = boxes[:, 2]
    y2 = boxes[:, 3]

    areas = (x2 - x1) * (y2 - y1)
    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 <= iou_thresh)[0]
        order = order[inds + 1]

    return keep[:max_boxes]
Pure Python NMS baseline.

Arguments: boxes: shape of [-1, 4], the value of '-1' means that dont know the
exact number of boxes
scores: shape of [-1,]
max_boxes: representing the maximum of boxes to be selected by non_max_suppression
iou_thresh: representing iou_threshold for deciding to keep boxes
ptstructure/layout/ptppyolov2/utils.py