Visualize point cloud in reflectivity or color by points or voxels；
Visualize contiguous frames' colored point clouds and storing them as video
Visualize point clouds by reflectivity
Visualize colored point clouds in voxels
main package : open3d 0.9.0 opencv-python mayavi
python draw_pc.py ; any environment with mayavi
python draw_pc_colored.py; any environment with open3d0.9.0
# Visualize point clouds by reflectivity
import draw_pc
# point clouds path
raw_velo_path = 'data/185/原始点云000185.bin'
non_ground_path = 'data/185/non_ground_000185.npy'
# Load point clouds
raw_vel_pc = np.fromfile(raw_velo_path,dtype=np.float32) # # bin type
raw_vel_pc = raw_vel.reshape((-1,4))
non_ground_pc = np.load(non_ground_path) # npy type
# Visualization
draw_pc.visualize_pts(raw_vel_pc)
draw_pc.visualize_pts(non_ground_pc)
#Visualize colored point clouds
import draw_pc_colored.Plot as Plot
########Visualize colored point clouds in one frame######
# Load point clouds
non_ground_color_path = 'data/185/滤出地面的着色点云000185.npy'
non_ground_color_pc = np.load(non_ground_color_path)
# Visualize colored point clouds
Plot.draw_pc(non_ground_color_pc)
# if savefig=True will automatically save the image, 'name' is to save the path
# The para.json file holds the required camera perspective
Plot.draw_pc(non_ground_color_pc,savefig=True,name='test.png')
########Visualize the continuous frame point cloud and save it to video######
# the continuous frame point cloud's path
imgs_path = 'result/kitti_tracking/'
seq = ['0020']
for s in seq:
imgs_path_seq = imgs_path + s +'/out_ps/'
# stored video
# If ps=False, the original image is directly stored into video, and ps=True, the brightness and contrast saturation of the image will be automatically adjusted, and the adjusted point cloud will be stored into video
imgs2video(imgs_path_seq,ps=False)
######################################Visualize Voxel's point cloud################################
# Load
non_ground_color_path = 'data/185/滤出地面的着色点云000185.npy'
non_ground_color_pc = np.load(non_ground_color_path)
# Voxel is visualized and fills with color automatically
Plot.draw_voxel(non_ground_color_pc)