Modifications to support Python 3.12

Author: ruoning-ng

python-sdk/nuscenes/map_expansion/map_api.py

@@ -29,7 +29,7 @@
 from nuscenes.utils.geometry_utils import view_points
 
 # Recommended style to use as the plots will show grids.
-plt.style.use('seaborn-whitegrid')
+plt.style.use('seaborn-v0_8-whitegrid')
 
 # Define a map geometry type for polygons and lines.
 Geometry = Union[Polygon, LineString]
@@ -1820,8 +1820,8 @@ def mask_for_polygons(polygons: MultiPolygon, mask: np.ndarray) -> np.ndarray:
         def int_coords(x):
             # function to round and convert to int
             return np.array(x).round().astype(np.int32)
-        exteriors = [int_coords(poly.exterior.coords) for poly in polygons]
-        interiors = [int_coords(pi.coords) for poly in polygons for pi in poly.interiors]
+        exteriors = [int_coords(poly.exterior.coords) for poly in polygons.geoms]
+        interiors = [int_coords(pi.coords) for poly in polygons.geoms for pi in poly.interiors]
         cv2.fillPoly(mask, exteriors, 1)
         cv2.fillPoly(mask, interiors, 0)
         return mask
@@ -1885,7 +1885,7 @@ def _polygon_geom_to_mask(self,
                                                         [1.0, 0.0, 0.0, 1.0, trans_x, trans_y])
                 new_polygon = affinity.scale(new_polygon, xfact=scale_width, yfact=scale_height, origin=(0, 0))
 
-                if new_polygon.geom_type is 'Polygon':
+                if new_polygon.geom_type == 'Polygon':
                     new_polygon = MultiPolygon([new_polygon])
                 map_mask = self.mask_for_polygons(new_polygon, map_mask)
 
@@ -1922,7 +1922,7 @@ def _line_geom_to_mask(self,
 
         map_mask = np.zeros(canvas_size, np.uint8)
 
-        if layer_name is 'traffic_light':
+        if layer_name == 'traffic_light':
             return None
 
         for line in layer_geom:
@@ -1968,7 +1968,7 @@ def _get_layer_polygon(self,
                                                       origin=(patch_x, patch_y), use_radians=False)
                         new_polygon = affinity.affine_transform(new_polygon,
                                                                 [1.0, 0.0, 0.0, 1.0, -patch_x, -patch_y])
-                        if new_polygon.geom_type is 'Polygon':
+                        if new_polygon.geom_type == 'Polygon':
                             new_polygon = MultiPolygon([new_polygon])
                         polygon_list.append(new_polygon)
 
@@ -1983,7 +1983,7 @@ def _get_layer_polygon(self,
                                                       origin=(patch_x, patch_y), use_radians=False)
                         new_polygon = affinity.affine_transform(new_polygon,
                                                                 [1.0, 0.0, 0.0, 1.0, -patch_x, -patch_y])
-                        if new_polygon.geom_type is 'Polygon':
+                        if new_polygon.geom_type == 'Polygon':
                             new_polygon = MultiPolygon([new_polygon])
                         polygon_list.append(new_polygon)
 
@@ -2003,7 +2003,7 @@ def _get_layer_line(self,
         if layer_name not in self.map_api.non_geometric_line_layers:
             raise ValueError("{} is not a line layer".format(layer_name))
 
-        if layer_name is 'traffic_light':
+        if layer_name == 'traffic_light':
             return None
 
         patch_x = patch_box[0]

python-sdk/nuscenes/prediction/input_representation/agents.py

@@ -193,7 +193,7 @@ def draw_agent_boxes(center_agent_annotation: Dict[str, Any],
             if num_points > 1:
                 color = fade_color(color, i, num_points - 1)
 
-            cv2.fillPoly(base_image, pts=[np.int0(box)], color=color)
+            cv2.fillPoly(base_image, pts=[np.intp(box)], color=color)
 
 
 class AgentBoxesWithFadedHistory(AgentRepresentation):

python-sdk/nuscenes/prediction/input_representation/tests/test_agents.py

@@ -153,9 +153,9 @@ def get_colors(name):
         agent_1_ts_0 = cv2.boxPoints(((300, 350), (30, 30), -90))
         agent_1_ts_1 = cv2.boxPoints(((300, 300), (30, 30), -90))
 
-        answer = cv2.fillPoly(answer, pts=[np.int0(agent_0_ts_0)], color=(102, 0, 0))
-        answer = cv2.fillPoly(answer, pts=[np.int0(angent_0_ts_1)], color=(255, 0, 0))
-        answer = cv2.fillPoly(answer, pts=[np.int0(agent_1_ts_0)], color=(102, 102, 0))
-        answer = cv2.fillPoly(answer, pts=[np.int0(agent_1_ts_1)], color=(255, 255, 0))
+        answer = cv2.fillPoly(answer, pts=[np.intp(agent_0_ts_0)], color=(102, 0, 0))
+        answer = cv2.fillPoly(answer, pts=[np.intp(angent_0_ts_1)], color=(255, 0, 0))
+        answer = cv2.fillPoly(answer, pts=[np.intp(agent_1_ts_0)], color=(102, 102, 0))
+        answer = cv2.fillPoly(answer, pts=[np.intp(agent_1_ts_1)], color=(255, 255, 0))
 
         np.testing.assert_allclose(answer, img)

python-sdk/nuscenes/prediction/input_representation/tests/test_combinators.py

@@ -15,18 +15,18 @@ def test(self):
 
         layer_1 = np.zeros((100, 100, 3))
         box_1 = cv2.boxPoints(((50, 50), (20, 20), 0))
-        layer_1 = cv2.fillPoly(layer_1, pts=[np.int0(box_1)], color=(255, 255, 255))
+        layer_1 = cv2.fillPoly(layer_1, pts=[np.intp(box_1)], color=(255, 255, 255))
 
         layer_2 = np.zeros((100, 100, 3))
         box_2 = cv2.boxPoints(((70, 30), (10, 10), 0))
-        layer_2 = cv2.fillPoly(layer_2, pts=[np.int0(box_2)], color=(0, 0, 255))
+        layer_2 = cv2.fillPoly(layer_2, pts=[np.intp(box_2)], color=(0, 0, 255))
 
         rasterizer = Rasterizer()
         image = rasterizer.combine([layer_1.astype('uint8'), layer_2.astype('uint8')])
 
         answer = np.zeros((100, 100, 3))
-        answer = cv2.fillPoly(answer, pts=[np.int0(box_1)], color=(255, 255, 255))
-        answer = cv2.fillPoly(answer, pts=[np.int0(box_2)], color=(0, 0, 255))
+        answer = cv2.fillPoly(answer, pts=[np.intp(box_1)], color=(255, 255, 255))
+        answer = cv2.fillPoly(answer, pts=[np.intp(box_2)], color=(0, 0, 255))
         answer = answer.astype('uint8')
 
         np.testing.assert_allclose(answer, image)

python-sdk/nuscenes/prediction/input_representation/tests/test_static_layers.py

@@ -20,7 +20,7 @@ def get_layer_mocks():
 
         layer_1 = np.zeros((100, 100, 3))
         box = cv2.boxPoints(((50, 50), (20, 10), -90))
-        layer_1 = cv2.fillPoly(layer_1, pts=[np.int0(box)], color=(1, 1, 1))
+        layer_1 = cv2.fillPoly(layer_1, pts=[np.intp(box)], color=(1, 1, 1))
         layer_1 = layer_1[::-1, :, 0]
 
         layer_2 = np.zeros((100, 100, 3))
@@ -56,7 +56,7 @@ def test_make_rasterization(self, mock_draw_lanes, mock_load_maps):
 
         lanes = np.zeros((100, 100, 3)).astype('uint8')
         lane_box = cv2.boxPoints(((25, 75), (5, 5), -90))
-        lanes = cv2.fillPoly(lanes, pts=[np.int0(lane_box)], color=(255, 0, 0))
+        lanes = cv2.fillPoly(lanes, pts=[np.intp(lane_box)], color=(255, 0, 0))
         mock_draw_lanes.return_value = lanes
 
         layers = self.get_layer_mocks()
@@ -81,8 +81,8 @@ def test_make_rasterization(self, mock_draw_lanes, mock_load_maps):
 
         answer = np.zeros((100, 100, 3))
         box = cv2.boxPoints(((50, 50), (20, 10), -90))
-        answer = cv2.fillPoly(answer, pts=[np.int0(box)], color=(255, 255, 255))
+        answer = cv2.fillPoly(answer, pts=[np.intp(box)], color=(255, 255, 255))
         answer = cv2.line(answer, (50, 50), (50, 40), color=(255, 0, 0), thickness=2)
-        answer = cv2.fillPoly(answer, pts=[np.int0(lane_box)], color=(255, 0, 0))
+        answer = cv2.fillPoly(answer, pts=[np.intp(lane_box)], color=(255, 0, 0))
 
         np.testing.assert_allclose(answer, image)

python-sdk/nuscenes/scripts/export_pointclouds_as_obj.py

@@ -119,7 +119,7 @@ def pointcloud_color_from_image(nusc: NuScenes,
     :param nusc: NuScenes instance.
     :param pointsensor_token: Lidar/radar sample_data token.
     :param camera_token: Camera sample data token.
-    :return (coloring <np.float: 3, n>, mask <np.bool: m>). Returns the colors for n points that reproject into the
+    :return (coloring <np.float: 3, n>, mask <bool: m>). Returns the colors for n points that reproject into the
         image out of m total points. The mask indicates which points are selected.
     """
 

python-sdk/nuscenes/utils/geometry_utils.py

@@ -118,7 +118,7 @@ def points_in_box(box: 'Box', points: np.ndarray, wlh_factor: float = 1.0):
     :param box: <Box>.
     :param points: <np.float: 3, n>.
     :param wlh_factor: Inflates or deflates the box.
-    :return: <np.bool: n, >.
+    :return: <bool: n, >.
     """
     corners = box.corners(wlh_factor=wlh_factor)
 

python-sdk/nuscenes/utils/map_mask.py

@@ -57,11 +57,11 @@ def is_on_mask(self, x: Any, y: Any, dilation: float = 0) -> np.array:
         :param x: Global x coordinates. Can be a scalar, list or a numpy array of x coordinates.
         :param y: Global y coordinates. Can be a scalar, list or a numpy array of x coordinates.
         :param dilation: Optional dilation of map mask.
-        :return: <np.bool: x.shape>. Whether the points are on the mask.
+        :return: <bool: x.shape>. Whether the points are on the mask.
         """
         px, py = self.to_pixel_coords(x, y)
 
-        on_mask = np.ones(px.size, dtype=np.bool)
+        on_mask = np.ones(px.size, dtype=bool)
         this_mask = self.mask(dilation)
 
         on_mask[px < 0] = False

python-sdk/tutorials/map_expansion_tutorial.ipynb

@@ -197,7 +197,7 @@
    "source": [
     "# Init nuScenes. Requires the dataset to be stored on disk.\n",
     "from nuscenes.nuscenes import NuScenes\n",
-    "nusc = NuScenes(version='v1.0-mini', verbose=False)\n",
+    "nusc = NuScenes(version='v1.0-mini', dataroot='/data/sets/nuscenes', verbose=False)\n",
     "\n",
     "# Pick a sample and render the front camera image.\n",
     "sample_token = nusc.sample[9]['token']\n",
@@ -222,7 +222,7 @@
    "source": [
     "# Init NuScenes. Requires the dataset to be stored on disk.\n",
     "from nuscenes.nuscenes import NuScenes\n",
-    "nusc = NuScenes(version='v1.0-mini', verbose=False)\n",
+    "nusc = NuScenes(version='v1.0-mini', dataroot='/data/sets/nuscenes', verbose=False)\n",
     "\n",
     "# Render ego poses.\n",
     "nusc_map_bos = NuScenesMap(dataroot='/data/sets/nuscenes', map_name='boston-seaport')\n",