# 各类图像数据集下载地址

## 各类图像数据集下载地址

反代加速请参见另一篇

### COCO

#### Images

```
官网
https://cocodataset.org/#home 

2014 Train images [83K/13GB]:
http://images.cocodataset.org/zips/train2014.zip

2014 Val images [41K/6GB]:
http://images.cocodataset.org/zips/val2014.zip

2014 Test images [41K/6GB]:
http://images.cocodataset.org/zips/test2014.zip

2015 Test images [81K/12GB]:
http://images.cocodataset.org/zips/test2015.zip

2017 Train images [118K/18GB]:
http://images.cocodataset.org/zips/train2017.zip

2017 Val images [5K/1GB]:
http://images.cocodataset.org/zips/val2017.zip

2017 Test images [41K/6GB]:
http://images.cocodataset.org/zips/test2017.zip

2017 Unlabeled images [123K/19GB]:
http://images.cocodataset.org/zips/unlabeled2017.zip
```

#### Annotations

```
2014 Train/Val annotations [241MB]:
http://images.cocodataset.org/annotations/annotations_trainval2014.zip

2014 Testing Image info [1MB]:
http://images.cocodataset.org/annotations/image_info_test2014.zip

2015 Testing Image info [2MB]:
http://images.cocodataset.org/annotations/image_info_test2015.zip

2017 Train/Val annotations [241MB]:
http://images.cocodataset.org/annotations/annotations_trainval2017.zip

2017 Stuff Train/Val annotations [1.1GB]:
http://images.cocodataset.org/annotations/stuff_annotations_trainval2017.zip

2017 Panoptic Train/Val annotations [821MB]:
http://images.cocodataset.org/annotations/panoptic_annotations_trainval2017.zip

2017 Testing Image info [1MB]:
http://images.cocodataset.org/annotations/image_info_test2017.zip

2017 Unlabeled Image info [4MB]:
http://images.cocodataset.org/annotations/image_info_unlabeled2017.zip
```

### KITTI

```
官网
http://www.cvlibs.net/datasets/kitti/

left color images of object data set (12 GB):
https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_image_2.zip

right color images, if you want to use stereo information (12 GB):
https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_image_3.zip

Velodyne point clouds, if you want to use laser information (29 GB):
https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_velodyne.zip

training labels of object data set (5 MB):
https://s3.eu-central-1.amazonaws.com/avg-kitti/data_object_label_2.zip

(只截取部分，详细请前往
官网
或 https://s3.eu-central-1.amazonaws.com/avg-kitti/)
```

**MPII**

```
官网
http://human-pose.mpi-inf.mpg.de/#download

Images (12.9 GB)
https://datasets.d2.mpi-inf.mpg.de/andriluka14cvpr/mpii_human_pose_v1.tar.gz


Annotations (12.5 MB)
https://datasets.d2.mpi-inf.mpg.de/andriluka14cvpr/mpii_human_pose_v1_u12_2.zip
```


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://bendfunction.gitbook.io/dataset-download/master.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.