Mesh 3D function added

Author: BalazsSzekeres

1_frame_information.ipynb

@@ -82,14 +82,14 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/opt/anaconda3/envs/mp-iv/lib/python3.7/site-packages/traittypes/traittypes.py:101: UserWarning: Given trait value dtype \"float64\" does not match required type \"float32\". A coerced copy has been created.\n",
+      "/opt/anaconda3/envs/view-of-delft-env/lib/python3.7/site-packages/traittypes/traittypes.py:101: UserWarning: Given trait value dtype \"float64\" does not match required type \"float32\". A coerced copy has been created.\n",
       "  np.dtype(self.dtype).name))\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "dccc0e1a192f4b15825e8c5bc8dc20bd",
+       "model_id": "ed098796e3fb4f01b9cbbba80966be90",
        "version_major": 2,
        "version_minor": 0
       },
@@ -149,13 +149,14 @@
     }
    },
    "source": [
-    "The class contains the homogenous transform matrices as properties, with the following convention: `t_target_origin`:\n",
-    "- t_camera_lidar: homogeneous transform matrix from the lidar frame, to the camera frame.\n",
-    "- t_camera_radar homogeneous transform matrix from the radar frame, to the camera frame.\n",
-    "- t_lidar_camera: homogeneous transform matrix from the camera frame, to the lidar frame.\n",
-    "- t_radar_camera: homogeneous transform matrix from the camera frame, to the radar frame.\n",
-    "- t_lidar_radar: homogeneous transform matrix from the radar frame, to the lidar frame.\n",
-    "- t_radar_lidar: homogeneous transform matrix from the lidar frame, to the radar frame.\n",
+    "The class contains the homogenous transform matrices as properties, that takes a point cloud which is in the source frame, and transforms\n",
+    " it to the target frame: `t_target_source`:\n",
+    "- t_camera_lidar: from the lidar source frame, to the camera target frame.\n",
+    "- t_camera_radar: from the lidar source frame, to the camera target frame.\n",
+    "- t_lidar_camera: from the lidar source frame, to the camera target frame.\n",
+    "- t_radar_camera: from the lidar source frame, to the camera target frame.\n",
+    "- t_lidar_radar: from the lidar source frame, to the camera target frame.\n",
+    "- t_radar_lidar: from the lidar source frame, to the camera target frame.\n",
     "\n",
     "The camera projection matrix is also available using `camera_projection_matrix`."
    ]
@@ -191,12 +192,7 @@
      "name": "#%% md\n"
     }
    },
-   "source": [
-    "There are also a number of helper functions included, which can help the transformations:\n",
-    "- `homogeneous_coordinates`: Add description!\n",
-    "- `homogeneous_transformation`:\n",
-    "- `project_3d_to_2d`:"
-   ]
+   "source": []
   },
   {
    "cell_type": "code",
@@ -331,4 +327,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 1
-}
+}

2_frame_transformations.ipynb

@@ -270,4 +270,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 1
-}
+}

3_2d_visualization.ipynb

@@ -1,6 +1,5 @@
 import os
 
-
 class KittiLocations:
     """
     This class contains the information regarding the locations of data for the dataset.

example_output01201.png

@@ -192,6 +192,27 @@ def k3d_get_axes(hom_transform_matrix=np.eye(4, dtype=float), axis_length=1.0):
     return pose_axes
 
 
+def k3d_plot_mesh(plot, box_corners, color):
+    box_mesh_index = np.asarray([
+        [0, 1, 2],  # bottom
+        [0, 2, 3],  # bottom
+        [0, 1, 5],  # front
+        [0, 5, 4],  # front
+        [2, 3, 7],  # back
+        [2, 7, 6],  # back
+        [1, 2, 6],  # right
+        [1, 6, 5],  # right
+        [0, 3, 7],  # left
+        [0, 7, 4],  # left
+        [4, 5, 6],  # top
+        [4, 6, 7],  # top
+        [0, 1, 5],  # front twice to be darker when opaque
+        [0, 5, 4],  # front
+    ], dtype=np.uint32)
+
+    plot += k3d.mesh(vertices=box_corners[:, 0:3], indices=box_mesh_index, color=color, opacity=0.25)
+
+
 def k3d_plot_box(plot, box_corners, color, width):
     lines = [[0, 1, 2, 3, 0], [4, 5, 6, 7, 4], [0, 4], [1, 5], [3, 7], [2, 6]]
 

vod/configuration/file_locations.py

@@ -1,7 +1,7 @@
 import k3d
 import numpy as np
 from .helpers import k3d_get_axes, get_transformed_3d_label_corners, k3d_plot_box, \
-    get_radar_velocity_vectors, get_default_camera
+    get_radar_velocity_vectors, get_default_camera, k3d_plot_mesh
 from vod.frame import FrameDataLoader, FrameTransformMatrix, FrameLabels, transform_pcl
 from .settings import *
 
@@ -180,12 +180,14 @@ def plot_annotations(self, class_colors=label_color_palette_3d, class_width=labe
         for box in bboxes:
             object_class = box['label_class']
 
-            object_class_color = class_colors[object_class]
-            object_class_width = class_width[object_class]
+            if object_class in class_colors:
+                object_class_color = class_colors[object_class]
+            else:
+                object_class_color = 0xAAAAAA
 
             corners_object = box['corners_3d_transformed']
 
-            k3d_plot_box(self.plot, corners_object, object_class_color, object_class_width)
+            k3d_plot_mesh(self.plot, corners_object, object_class_color)
 
     def draw_plot(self,
                   radar_origin_plot: bool = False,
@@ -250,4 +252,3 @@ def draw_plot(self,
 
             with open(f'{html_name}.html', 'w') as f:
                 f.write(data)
-