[8, 4, 2, 1], **kwargs) return model def pvt_v2_b2_li(**kwargs): model = PyramidVisionTransformerV2( patch_size=4, embed_dims=[64, 128, 320, 512], num_heads=[1, 2, 5, 8], mlp_ratios=[8, 8, 4, 4], qkv_bias=True, norm_layer=partial(nn.LayerNorm, epsilon=1e-6...
具体来说,PVTv2-B5(注释:PVTv2有6个不同大小型号,从B0到B5)在ImageNet上产生83.8%的top-1错误,这明显优于Swin-B[21]和Twins-SVT-L[4],而PVTv2-B5的参数和gflop较少。此外,GFL[17](Generalized focal loss)与PVT-B2在COCO val2017上的记录值为50.2 AP,比与SWN-T[21]的记录值高2.6 AP,比与ResNet5...
To evaluate PVTv2-B2 + SemFPN on a single node with 8 gpus run: dist_test.sh configs/sem_fpn/PVT/fpn_pvtv2_b2_ade20k_40k.py /path/to/checkpoint_file 8 --out results.pkl --eval mIoU Training To train PVTv2-B2 + SemFPN on a single node with 8 gpus run: ...
pvt v2 b2 li 45M 0.829 0.964 pvt v2 b3 62M 0.834 0.967 pvt v2 b4 82M 0.835 0.966 pvt v2 b5 22M 0.819 0.960 In [ ] # pvt v2 b0 m = pvt_v2_b0() m.set_state_dict(paddle.load('/home/aistudio/data/data97429/pvt_v2_b0.pdparams')) # pvt v2 b1 m = pvt_v2_b1() m.set...