parameters: (dets, thresh)
return_statement: return keep
docstring: Pure Python NMS baseline.
docstring_summary: Pure Python NMS baseline.
docstring_tokens: Pure Python NMS baseline .
function: def py_cpu_nms(dets, thresh):
      """Pure Python NMS baseline."""
      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
function_tokens: def py_cpu_nms ( dets , thresh ) : 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