Cuspatial version

[stansf]

Hello! What version of the cuspatial package are you actually using?

In instruction Docker image rapidsai/rapidsai:cuda11.5-runtime-ubuntu20.04-py3.8 is used which has rapids of version 23.04. But, probably, in this version the API of cuspatial.point_in_polygon was changed and test.py fails:

TypeError: point_in_polygon() got an unexpected keyword argument 'poly_points_x'

[LucBourrat1]

Hello @stansf ,

I have same problems, it looks like arguments of the function cuspatial.point_in_polygon() are not correct, according to the documentation: https://docs.rapids.ai/api/cuspatial/nightly/api_docs/spatial/#cuspatial.point_in_polygon

The signature is: cuspatial.point_in_polygon(points: GeoSeries, polygons: GeoSeries)

I use cuspatial 23.8.1.

I managed to make it work with a workaround:

• Import "sPoint" and "sPolygon" from shapely: To add at begining of plane_evaluation.py script. I used the "s" (for Shapely) prefix for sPoint and sPolygon because Polygon already exists:

  from shapely import Polygon as sPolygon
  from shapely import Point as sPoint

• Conversion of the points into cuspatial.Geoseries: To add in plane_evaluation.py script, just before the cuspatial.point_in_polygon() call (l.182):

  points = cs.GeoSeries([sPoint(p_x[idx], p_y[idx]) for idx in range(len(p_x))])

• Add a function make_polygons(): (add it wherever in the script, for example at the end).

  def make_polygons(poly_x, poly_y):
  polygons = []
  sx, sy = poly_x[0], poly_y[0]
  p = [(sx, sy)]
  nb_points = len(poly_x)
  flag = False
  for i, (x, y) in enumerate(zip(poly_x, poly_y)):
      if i!=0:
          p.append((x, y))
          if (x==sx) and (y==sy):
              if flag:
                  flag = False
              else:
                  polygons.append(sPolygon(p))
                  p = []
                  if i != nb_points-1:
                      sx, sy = poly_x[i+1], poly_y[i+1]
                      flag = True
  return polygons

• Conversion of the polygons into a cuspatial.GeoSeries: To add in plane_evaluation.py script, just before the cuspatial.point_in_polygon() call (l.182):

  p_x = list(self.points_x.to_numpy())
  p_y = list(self.points_y.to_numpy())
  poly_x = list(poly_dict['poly_points_x'].to_numpy())
  poly_y = list(poly_dict['poly_points_y'].to_numpy())
  polygons = cs.GeoSeries(make_polygons(poly_x, poly_y))

• Replace the cuspatial.point_in_polygon() call to one with correct arguments: To add in plane_evaluation.py script l.182:

  
  # mask_frame = cs.point_in_polygon(self.points_x, self.points_y, **poly_dict) # old call is commented
  mask_frame = cs.point_in_polygon(points ,polygons)

This workaround worked for me, but inference time is a bit long and I think it is due to this function call, I get around 5s/image on a Nvidia P100 GPU, and I don't know how fast it should be.

Tell me if that works for you

[DavidGillsjo]

Thanks for reporting the issue. I'll adapt the project to the latest cuspatial docker and lock down the version.

If I run into problems I'll lock to an older cuspatial docker.

[baudcode]

@DavidGillsjo Did you manage to update the docker? Can't get this to work at all on my machine.

[DavidGillsjo]

I did manage to get the code running with the newer cu-spatial version. See this branch.

Unfortunately I did not get the same performance with the old model weights, so there might be a bug or possibly a need to retrain the model using the new functions.

I'm afraid I don't have the time or resources to retrain the model, but if I find some time I will continue with the debugging.

[ebrahimkhalilabbasi]

Hello @DavidGillsjo, Have you made any progress in improving the results (weights) for the inference_issues branch?