对于用于集成的两个模型,它们在初始化阶段的查询方面有所不同,分别设置为300和900。 对于判断是否戴头盔的分类模型,采用了在ImageNet预训练的ResNet-18 [8],并在AI City Challenge数据集上进行微调。输入分辨率为256×192,训练和测试数据集的比例为9:1。使用CosineAnealingLR的学习率衰减策略进行100个epochs的训练...
对于用于集成的两个模型,它们在初始化阶段的查询方面有所不同,分别设置为300和900。 对于判断是否戴头盔的分类模型,采用了在ImageNet预训练的ResNet-18 [8],并在AI City Challenge数据集上进行微调。输入分辨率为256×192,训练和测试数据集的比例为9:1。使用CosineAnealingLR的学习率衰减策略进行100个epochs的训练...
To account for rare tiles, assign some class to the tile and use the inverse probability of that class in the dataset to oversample them. Also change binary cross-entropy loss to multiclass cross-entropy (in our case 2 output channels) and take argmax instead of searching an optimal ...
3. Datasets The datasets for the 2019 AI City Challenge came from the following sources, CityFlow [37] and Iowa DOT [26], which we further describe in this section. 3.1. The CityFlow Dataset The CityFlow dataset has been curated specifically for Track 1 and Track 2 of the 2019 AI City ...
The format of inference should be similar with the A2 dataset, which is provided by 2022 AI City Challenge. The format of A2 dataset as follows: A2 user_id_* CAMERAVIEW_user_id_*.MP4 CAMERAVIEW_user_id_*.MP4 CAMERAVIEW_user_id_*.MP4 ...
3、dataset 实现数据增强及Dataset。 In [4] import paddle import paddleseg city_dataset_root = "/home/aistudio/data/cityscapes" ade_dataset_root = "/home/aistudio/data/ADEChallengeData2016" city_train_transforms = [ paddleseg.transforms.ResizeStepScaling(min_scale_factor=0.5, max_scale_factor=2....
发邮件申请:https://www.aicitychallenge.org/2022-data-access-instructions/ 下载后跟踪官方给的检测结果生成 json 格式数据集,或者自行标注。数据处理参考:x2coco.py 将生成后的标注和对应的数据,放到 dataset 目录下,比如:dataset/aicityIn [1] # 如果希望解压到其他目录 # 可选择其他路径(默认 /home/aistu...
trained on the 2023 NVIDIA AI City Challenge Track 5 dataset and employed genetic algorithms in selecting the optimal hyperparameters for training the model... E Soltanikazemi,A Aboah,E Arthur,... - 《Arxiv》 被引量: 0发表: 2023年 Traffic Speed Estimation from Surveillance Video Data: For ...
Vidana-Vila, E.; Duboc, L.; Alsina-Pages, R.M.; Polls, F.; Vargas, H. BCNDataset: Description and Analysis of an Annotated Night Urban Leisure Sound Dataset.Sustainability2020,12, 8140. [Google Scholar] [CrossRef] Vogiatzaki, M.; Zerefos, S.; Tania, M.H. Enhancing City Sustainabi...
NVIDIA Launches Cosmos World Foundation Model Platform for Developing Physical AI NVIDIA Cosmos™ is a platform comprising state-of-the-art generative world foundation models, advanced tokenizers, guardrails, and an accelerated video processing pipeline built to accelerate the development of physical AI...