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import os
import cv2
import imageio
import numpy as np
import open3d as o3d
import os.path as osp
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
def render_frames(o3d_geometry, camera_all, output_dir, save_video=True, save_camera=True):
# Create off-screen renderer
render = o3d.visualization.rendering.OffscreenRenderer(
width=camera_all[0].intrinsic.width,
height=camera_all[0].intrinsic.height
)
render_frame_path = os.path.join(output_dir, 'render_frames')
render_camera_path = os.path.join(output_dir, 'render_cameras')
os.makedirs(render_frame_path, exist_ok=True)
os.makedirs(render_camera_path, exist_ok=True)
video_path = os.path.join(output_dir, 'render_frame.mp4')
if save_video:
writer = imageio.get_writer(video_path, fps=10)
material = o3d.visualization.rendering.MaterialRecord()
material.shader = 'defaultUnlit' # Use unlit shader for point clouds
material.point_size = 1.0 # Match original point size
material.base_color = [1.0, 1.0, 1.0, 1.0]
for i, camera_params in enumerate(camera_all):
if camera_params is None:
continue
# Set camera view
render.setup_camera(
camera_params.intrinsic.intrinsic_matrix,
camera_params.extrinsic,
camera_params.intrinsic.width,
camera_params.intrinsic.height
)
if save_camera:
o3d.io.write_pinhole_camera_parameters(
os.path.join(render_camera_path, f'camera_{i:03d}.json'),
camera_params
)
# Render
render.scene.add_geometry("points", o3d_geometry, material)
img = render.render_to_image()
render.scene.remove_geometry("points")
# Save frame
image_uint8 = (np.asarray(img) * 255).astype(np.uint8)
frame_filename = f'frame_{i:03d}.png'
imageio.imwrite(osp.join(render_frame_path, frame_filename), image_uint8)
if save_video:
writer.append_data(image_uint8)
if save_video:
writer.close()
return video_path
def find_render_cam(pcd, width=1920, height=1080):
# For headless servers, we'll need to pre-define camera parameters
# This creates a default viewing angle looking at the center of the point cloud
# Calculate point cloud center and scale
center = pcd.get_center()
scale = np.max(pcd.get_max_bound() - pcd.get_min_bound())
# Create default camera parameters
camera_params = o3d.camera.PinholeCameraParameters()
# Set intrinsic parameters
intrinsic = o3d.camera.PinholeCameraIntrinsic()
intrinsic.set_intrinsics(
width=width,
height=height,
fx=width,
fy=width,
cx=width/2,
cy=height/2
)
camera_params.intrinsic = intrinsic
# Set extrinsic parameters (looking at center from a 45-degree angle)
camera_params.extrinsic = np.array([
[1, 0, 0, 0],
[0, np.cos(np.pi/4), -np.sin(np.pi/4), 0],
[0, np.sin(np.pi/4), np.cos(np.pi/4), 2*scale],
[0, 0, 0, 1]
])
return camera_params
def vis_pred_and_imgs(pts_all, save_path, images_all=None, conf_all=None, save_video=True):
# Set matplotlib backend to non-interactive
plt.switch_backend('Agg')
# Normalization
min_val = pts_all.min(axis=(0, 1, 2), keepdims=True)
max_val = pts_all.max(axis=(0, 1, 2), keepdims=True)
pts_all = (pts_all - min_val) / (max_val - min_val)
pts_save_path = osp.join(save_path, 'pts')
os.makedirs(pts_save_path, exist_ok=True)
if images_all is not None:
images_save_path = osp.join(save_path, 'imgs')
os.makedirs(images_save_path, exist_ok=True)
if conf_all is not None:
conf_save_path = osp.join(save_path, 'confs')
os.makedirs(conf_save_path, exist_ok=True)
if save_video:
pts_video_path = osp.join(save_path, 'pts.mp4')
pts_writer = imageio.get_writer(pts_video_path, fps=10)
if images_all is not None:
imgs_video_path = osp.join(save_path, 'imgs.mp4')
imgs_writer = imageio.get_writer(imgs_video_path, fps=10)
if conf_all is not None:
conf_video_path = osp.join(save_path, 'confs.mp4')
conf_writer = imageio.get_writer(conf_video_path, fps=10)
for frame_id in range(pts_all.shape[0]):
# Points visualization
pt_vis = pts_all[frame_id].astype(np.float32)
pt_vis_rgb = mcolors.hsv_to_rgb(1-pt_vis)
pt_vis_rgb_uint8 = (pt_vis_rgb * 255).astype(np.uint8)
# Use matplotlib in non-interactive mode
fig, ax = plt.subplots()
ax.imshow(pt_vis_rgb_uint8)
plt.savefig(osp.join(pts_save_path, f'pts_{frame_id:04d}.png'))
plt.close(fig)
if save_video:
pts_writer.append_data(pt_vis_rgb_uint8)
if images_all is not None:
image = images_all[frame_id]
image_uint8 = (image * 255).astype(np.uint8)
imageio.imwrite(osp.join(images_save_path, f'img_{frame_id:04d}.png'), image_uint8)
if save_video:
imgs_writer.append_data(image_uint8)
if conf_all is not None:
fig, ax = plt.subplots()
conf_image = plt.cm.jet(conf_all[frame_id])
ax.imshow(conf_image)
plt.savefig(osp.join(conf_save_path, f'conf_{frame_id:04d}.png'))
plt.close(fig)
conf_image_uint8 = (conf_image * 255).astype(np.uint8)
if save_video:
conf_writer.append_data(conf_image_uint8)
if save_video:
pts_writer.close()
if images_all is not None:
imgs_writer.close()
if conf_all is not None:
conf_writer.close() |