Open Images是由谷歌发布的一个开源图片数据集,在2022年10月份发布了最新的V7版本。这个版本的数据集包含了900多万张图片,都有类别标记。其中190多万张图片有非常精细的标注:bounding boxes, object segmentations, visual relationships, localized narratives, point-level labels, and image-level labels. 具体来说,...
Google进一步扩展计算机视觉资料集Open Images，发布最新V7版本，加入被称为点标签（Point Labels）的新注解类型，另外，Open Images V7还加入了多合一视觉工具，供用户同时使用多注解资料，更好地探索资料集。Open Images计算机视觉资料集内置900万张图像，标签涵盖数千种对象类别，可让研究人员训练并且评估计算机视觉模型。
Name of dataset: OpenImages v7 URL of dataset: https://g.co/dataset/open-images License of dataset: licensed by Google Inc. under CC BY 4.0 license. The images are listed as having a CC BY 2.0 license. Short description of dataset and us...
dataset_dir: dataset/OpenImagesV7 allow_empty: true TestDataset: !ImageFolder anno_path: label_list.txt dataset_dir: dataset/OpenImagesV7 22 changes: 21 additions & 1 deletion 22 configs/yolov8/README.md Original file line numberDiff line numberDiff line change @@ -9,7 +9,7 @@ ## ...
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Open Images Dataset V7 and Extensions15,851,536 boxes on 600 classes2,785,498 instance segmentations on 350 classes3,284,280 relationship annotations on 1,466 relationships675,155 localized narratives66,391,027 point-level annotations on 5,827 classes...
Train Example PythonCLI from ultralytics import YOLO # Load a COCO-pretrained YOLO11n model model = YOLO("yolo11n.pt") # Train the model on the Open Images V7 dataset results = model.train(data="open-images-v7.yaml", epochs=100, imgsz=640) ...
- **mAP验证** 值适用于在[Open Image V7](https://docs.ultralytics.com/datasets/detect/open-images-v7/)数据集上的单模型单尺度。 通过 `yolo val detect data=open-images-v7.yaml device=0` 以复现。 - **速度** 在使用[Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/)实...
docker buildx create --use --name build --node build --driver-opt network=host docker buildx build -t snowdreamtech/openssh --platform=linux/386,linux/amd64,linux/arm/v6,linux/arm/v7,linux/arm64,linux/ppc64le,linux/riscv64,linux/s390x . --push Reference 使用buildx 构建多平台 Docker...