Support Objects365 pretrain and Adding the DINO++ model can achieve an accuracy of 63.4mAP at a model scale of 200M(Under the same scale, the accuracy is the best)
* add caltech, flower, mnist data source
* add det lvis data source
* add pose crowdPose data source
* add pose of OC Human data source
* add pose of mpii data source
* add Seg of voc data source
* add Seg of coco data source
* add Det of wider person datasource
* add Det of african wildlife datasource
* add Det of fruit datasource
* add Det of pet datasource
* add Det of artaxor and tiny person datasource
* add Det of wider face datasource
* add Det of crowd human datasource
* add Det of object365 datasource
* add Seg of coco stuff 10k and 164k datasource
Co-authored-by: Cathy0908 <30484308+Cathy0908@users.noreply.github.com>
* add data_source imagenet
* modify data_source imagenet and add unittest
* modify data_source imagenet and modify unittest
* modify voc data_source and modify voc unittest and download Part
* modify coco data_source and modify coco unittest and add download Part , modify voc data_source
* add dataset metadata Format specification
* add pose download data , modify coco.py and modiy download file function ,add test coco download a part
* modify download file function
* modify download of cifar10 and cifar100
* modify dataset_name to target_dir
* create download_util and modify function
* modify function
* modify function
* add test case , modify
* modify something
* modify something
* modify something
* modify something
* modify something
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* add wget
* add wget
* modify
* add new modify
* add new modify
* modify something
* modify something and add something
* modify something and add something
* modify something and add something
* modify something and add something
* modify something and add something
* modify test case
* modify test case
* modify test case
* modify test case
* modify test case
tuofeilun
gulou
Cathy0908
jiangnana.jnn
wenmeng.zwm