Plotly를 이용한 multiple images 출력 import plotly.express as pxfrom plotly.subplots import make_subplotsimport plotly.graph_objects as go# Create a 2x2 subplot layoutfig = make_subplots(rows=2, cols=2)# Add each image as a heatmapfig.add_trace(go.Heatmap(z=label.squeeze().detach().to('cpu').numpy(), colorscale='gray', showscale=False), row=1, col=1)fig.add_trace(go.Heatmap(z=prediction.squeeze().detach().to.. 더보기 Improve noise estimation performance 🔹 1. Denoising with Confidence Estimation (Failed)The confidence might be inherently learned during the noise estimationTrain the noise estimator to also output a confidence map.Use this to weight how much noise to subtract:denoised = bev_feat - confidence * noiseHelps avoid over-subtraction in uncertain regions.🔹 2. Feature Consistency Loss : Alrady being appliedAdd a loss between clean BEV f.. 더보기 Project lidar point cloud into a camera image in nuScenes import osfrom NuscenesDataset.nuscenes import NuScenesfrom PIL import Imagefrom nuscenes.utils.data_classes import LidarPointCloudfrom pyquaternion import Quaternionimport numpy as npimport matplotlib.pyplot as pltnusc = NuScenes(version='v1.0-trainval', dataroot="/home/dooseop/DATASET/nuscenes/", verbose=False)my_sample = nusc.sample[10]# my_sample = nusc.sample[10]# nusc.render_pointcloud_in_i.. 더보기 이전 1 2 3 4 ··· 69 다음 목록 더보기