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Running
on
Zero
# Alpha-CLIP evaluation | |
## Zero-Shot Classification on ImageNet-S | |
1.prepare [imagenet-s](https://github.com/LUSSeg/ImageNet-S) dataset, only `validation` raw image is needed. | |
2.download [imagenet_919.json](https://download.openxlab.org.cn/models/SunzeY/AlphaCLIP/weight/imagenet_919.json) we provide as data annotation (generated from imagenet-s annotation). The folder should be structured like | |
``` | |
βββ imagenet_s_zs_test | |
β βββ data | |
β β βββ imagenet_919.json | |
β β βββ ImageNetS919 | |
β β βββ validation | |
``` | |
3.run test script. | |
``` | |
cd eval/imagenet_s_zs_test | |
python imagenet_s_zs_test.py | |
``` | |