Cityscapes Image Pairs_datasets..zip2021-03-10201.69MB 文档 Cityscapes Image Pairs Semantic Segmentation for Improving Automated Driving Overview Cityscapes data contains labeled videos taken from vehicles driven in Germany. This version is a processed subsample created as part of the Pix2Pix paper. The...
天池实验室 数据集 公共数据集 正文 Cityscapes Image Pairs城市景观图像对 DQR2021-03-101237CC-BY-SA-NC 4.0 新建Notebook 内容 Notebook 评论 No Data 0
import caffe import numpy as np from PIL import Image import os import random class CityscapesSegDataLayer(caffe.Layer): """ Load (input image, label image) pairs from the SBDD extended labeling of PASCAL VOC for semantic segmentation one-at-a-time while reshaping the net to preserve dimensio...
Cityscapes Image Pairs城市景观图像对-数据集 Cityscapes数据包含从德国驾驶的车辆拍摄的带有标签的视频。该版本是经过处理的子样本,是Pix2Pix论文的一部分。数据集具有来自原始视频的静止图像,并且语义分割标签与原始图像一起显示在图像中。这是用于语义分割任务的最佳数据集之一。
stereo image pairs and corresponding annotations, our dataset includes vehicle odometry obtained from in-vehicle sensors, outside temperature, and GPS tracks. 2.2. Classes and annotations We provide coarse and fine annotations at pixel level in- ...
Evaluates pairs of prediction and ground truth # images which are passed as arguments.def evaluatePair(predictionImgFileName, groundTruthImgFileName, confMatrix, instanceStats, perImageStats, args): # Loading all resources for evaluation.