π― Timm Encoders#
Pytorch Image Models (a.k.a. timm) has a lot of pretrained models and interface which allows using these models as encoders in smp, however, not all models are supported
not all transformer models have
features_only
functionality implemented that is required for encodersome models have inappropriate strides
Below is a table of suitable encoders (for DeepLabV3, DeepLabV3+, and PAN dilation support is needed also)
Total number of encoders: 812 (593+219)
Note
To use following encoders you have to add prefix tu-
, e.g. tu-adv_inception_v3
Traditional-Style#
These models typically produce feature maps at the following downsampling scales relative to the input resolution: 1/2, 1/4, 1/8, 1/16, and 1/32
Encoder name |
Support dilation |
---|---|
bat_resnext26ts |
β |
botnet26t_256 |
β |
botnet50ts_256 |
β |
coatnet_0_224 |
|
coatnet_0_rw_224 |
|
coatnet_1_224 |
|
coatnet_1_rw_224 |
|
coatnet_2_224 |
|
coatnet_2_rw_224 |
|
coatnet_3_224 |
|
coatnet_3_rw_224 |
|
coatnet_4_224 |
|
coatnet_5_224 |
|
coatnet_bn_0_rw_224 |
|
coatnet_nano_cc_224 |
|
coatnet_nano_rw_224 |
|
coatnet_pico_rw_224 |
|
coatnet_rmlp_0_rw_224 |
|
coatnet_rmlp_1_rw2_224 |
|
coatnet_rmlp_1_rw_224 |
|
coatnet_rmlp_2_rw_224 |
|
coatnet_rmlp_2_rw_384 |
|
coatnet_rmlp_3_rw_224 |
|
coatnet_rmlp_nano_rw_224 |
|
coatnext_nano_rw_224 |
|
cs3darknet_focus_l |
β |
cs3darknet_focus_m |
β |
cs3darknet_focus_s |
β |
cs3darknet_focus_x |
β |
cs3darknet_l |
β |
cs3darknet_m |
β |
cs3darknet_s |
β |
cs3darknet_x |
β |
cs3edgenet_x |
β |
cs3se_edgenet_x |
β |
cs3sedarknet_l |
β |
cs3sedarknet_x |
β |
cs3sedarknet_xdw |
β |
cspdarknet53 |
β |
cspresnet50 |
β |
cspresnet50d |
β |
cspresnet50w |
β |
cspresnext50 |
β |
darknet17 |
β |
darknet21 |
β |
darknet53 |
β |
darknetaa53 |
β |
densenet121 |
|
densenet161 |
|
densenet169 |
|
densenet201 |
|
densenet264d |
|
densenetblur121d |
|
dla34 |
|
dla46_c |
|
dla46x_c |
|
dla60 |
|
dla60_res2net |
|
dla60_res2next |
|
dla60x |
|
dla60x_c |
|
dla102 |
|
dla102x |
|
dla102x2 |
|
dla169 |
|
dm_nfnet_f0 |
β |
dm_nfnet_f1 |
β |
dm_nfnet_f2 |
β |
dm_nfnet_f3 |
β |
dm_nfnet_f4 |
β |
dm_nfnet_f5 |
β |
dm_nfnet_f6 |
β |
dpn48b |
|
dpn68 |
|
dpn68b |
|
dpn92 |
|
dpn98 |
|
dpn107 |
|
dpn131 |
|
eca_botnext26ts_256 |
β |
eca_halonext26ts |
β |
eca_nfnet_l0 |
β |
eca_nfnet_l1 |
β |
eca_nfnet_l2 |
β |
eca_nfnet_l3 |
β |
eca_resnet33ts |
β |
eca_resnext26ts |
β |
eca_vovnet39b |
|
ecaresnet26t |
β |
ecaresnet50d |
β |
ecaresnet50d_pruned |
β |
ecaresnet50t |
β |
ecaresnet101d |
β |
ecaresnet101d_pruned |
β |
ecaresnet200d |
β |
ecaresnet269d |
β |
ecaresnetlight |
β |
ecaresnext26t_32x4d |
β |
ecaresnext50t_32x4d |
β |
efficientnet_b0 |
β |
efficientnet_b0_g8_gn |
β |
efficientnet_b0_g16_evos |
β |
efficientnet_b0_gn |
β |
efficientnet_b1 |
β |
efficientnet_b1_pruned |
β |
efficientnet_b2 |
β |
efficientnet_b2_pruned |
β |
efficientnet_b3 |
β |
efficientnet_b3_g8_gn |
β |
efficientnet_b3_gn |
β |
efficientnet_b3_pruned |
β |
efficientnet_b4 |
β |
efficientnet_b5 |
β |
efficientnet_b6 |
β |
efficientnet_b7 |
β |
efficientnet_b8 |
β |
efficientnet_blur_b0 |
β |
efficientnet_cc_b0_4e |
β |
efficientnet_cc_b0_8e |
β |
efficientnet_cc_b1_8e |
β |
efficientnet_el |
β |
efficientnet_el_pruned |
β |
efficientnet_em |
β |
efficientnet_es |
β |
efficientnet_es_pruned |
β |
efficientnet_l2 |
β |
efficientnet_lite0 |
β |
efficientnet_lite1 |
β |
efficientnet_lite2 |
β |
efficientnet_lite3 |
β |
efficientnet_lite4 |
β |
efficientnetv2_l |
β |
efficientnetv2_m |
β |
efficientnetv2_rw_m |
β |
efficientnetv2_rw_s |
β |
efficientnetv2_rw_t |
β |
efficientnetv2_s |
β |
efficientnetv2_xl |
β |
ese_vovnet19b_dw |
|
ese_vovnet19b_slim |
|
ese_vovnet19b_slim_dw |
|
ese_vovnet39b |
|
ese_vovnet39b_evos |
|
ese_vovnet57b |
|
ese_vovnet99b |
|
fbnetc_100 |
β |
fbnetv3_b |
β |
fbnetv3_d |
β |
fbnetv3_g |
β |
gc_efficientnetv2_rw_t |
β |
gcresnet33ts |
β |
gcresnet50t |
β |
gcresnext26ts |
β |
gcresnext50ts |
β |
gernet_l |
β |
gernet_m |
β |
gernet_s |
β |
ghostnet_050 |
|
ghostnet_100 |
|
ghostnet_130 |
|
ghostnetv2_100 |
|
ghostnetv2_130 |
|
ghostnetv2_160 |
|
halo2botnet50ts_256 |
β |
halonet26t |
β |
halonet50ts |
β |
halonet_h1 |
β |
haloregnetz_b |
β |
hardcorenas_a |
β |
hardcorenas_b |
β |
hardcorenas_c |
β |
hardcorenas_d |
β |
hardcorenas_e |
β |
hardcorenas_f |
β |
hrnet_w18 |
|
hrnet_w18_small |
|
hrnet_w18_small_v2 |
|
hrnet_w18_ssld |
|
hrnet_w30 |
|
hrnet_w32 |
|
hrnet_w40 |
|
hrnet_w44 |
|
hrnet_w48 |
|
hrnet_w48_ssld |
|
hrnet_w64 |
|
lambda_resnet26rpt_256 |
β |
lambda_resnet26t |
β |
lambda_resnet50ts |
β |
lamhalobotnet50ts_256 |
β |
lcnet_035 |
β |
lcnet_050 |
β |
lcnet_075 |
β |
lcnet_100 |
β |
lcnet_150 |
β |
legacy_senet154 |
|
legacy_seresnet18 |
|
legacy_seresnet34 |
|
legacy_seresnet50 |
|
legacy_seresnet101 |
|
legacy_seresnet152 |
|
legacy_seresnext26_32x4d |
|
legacy_seresnext50_32x4d |
|
legacy_seresnext101_32x4d |
|
maxvit_base_tf_224 |
|
maxvit_base_tf_384 |
|
maxvit_base_tf_512 |
|
maxvit_large_tf_224 |
|
maxvit_large_tf_384 |
|
maxvit_large_tf_512 |
|
maxvit_nano_rw_256 |
|
maxvit_pico_rw_256 |
|
maxvit_rmlp_base_rw_224 |
|
maxvit_rmlp_base_rw_384 |
|
maxvit_rmlp_nano_rw_256 |
|
maxvit_rmlp_pico_rw_256 |
|
maxvit_rmlp_small_rw_224 |
|
maxvit_rmlp_small_rw_256 |
|
maxvit_rmlp_tiny_rw_256 |
|
maxvit_small_tf_224 |
|
maxvit_small_tf_384 |
|
maxvit_small_tf_512 |
|
maxvit_tiny_pm_256 |
|
maxvit_tiny_rw_224 |
|
maxvit_tiny_rw_256 |
|
maxvit_tiny_tf_224 |
|
maxvit_tiny_tf_384 |
|
maxvit_tiny_tf_512 |
|
maxvit_xlarge_tf_224 |
|
maxvit_xlarge_tf_384 |
|
maxvit_xlarge_tf_512 |
|
maxxvit_rmlp_nano_rw_256 |
|
maxxvit_rmlp_small_rw_256 |
|
maxxvit_rmlp_tiny_rw_256 |
|
maxxvitv2_nano_rw_256 |
|
maxxvitv2_rmlp_base_rw_224 |
|
maxxvitv2_rmlp_base_rw_384 |
|
maxxvitv2_rmlp_large_rw_224 |
|
mixnet_l |
β |
mixnet_m |
β |
mixnet_s |
β |
mixnet_xl |
β |
mixnet_xxl |
β |
mnasnet_050 |
β |
mnasnet_075 |
β |
mnasnet_100 |
β |
mnasnet_140 |
β |
mnasnet_small |
β |
mobilenet_edgetpu_100 |
β |
mobilenet_edgetpu_v2_l |
β |
mobilenet_edgetpu_v2_m |
β |
mobilenet_edgetpu_v2_s |
β |
mobilenet_edgetpu_v2_xs |
β |
mobilenetv1_100 |
β |
mobilenetv1_100h |
β |
mobilenetv1_125 |
β |
mobilenetv2_035 |
β |
mobilenetv2_050 |
β |
mobilenetv2_075 |
β |
mobilenetv2_100 |
β |
mobilenetv2_110d |
β |
mobilenetv2_120d |
β |
mobilenetv2_140 |
β |
mobilenetv3_large_075 |
β |
mobilenetv3_large_100 |
β |
mobilenetv3_large_150d |
β |
mobilenetv3_rw |
β |
mobilenetv3_small_050 |
β |
mobilenetv3_small_075 |
β |
mobilenetv3_small_100 |
β |
mobilenetv4_conv_aa_large |
β |
mobilenetv4_conv_aa_medium |
β |
mobilenetv4_conv_blur_medium |
β |
mobilenetv4_conv_large |
β |
mobilenetv4_conv_medium |
β |
mobilenetv4_conv_small |
β |
mobilenetv4_conv_small_035 |
β |
mobilenetv4_conv_small_050 |
β |
mobilenetv4_hybrid_large |
β |
mobilenetv4_hybrid_large_075 |
β |
mobilenetv4_hybrid_medium |
β |
mobilenetv4_hybrid_medium_075 |
β |
mobileone_s0 |
β |
mobileone_s1 |
β |
mobileone_s2 |
β |
mobileone_s3 |
β |
mobileone_s4 |
β |
mobilevit_s |
β |
mobilevit_xs |
β |
mobilevit_xxs |
β |
mobilevitv2_050 |
β |
mobilevitv2_075 |
β |
mobilevitv2_100 |
β |
mobilevitv2_125 |
β |
mobilevitv2_150 |
β |
mobilevitv2_175 |
β |
mobilevitv2_200 |
β |
nf_ecaresnet26 |
β |
nf_ecaresnet50 |
β |
nf_ecaresnet101 |
β |
nf_regnet_b0 |
β |
nf_regnet_b1 |
β |
nf_regnet_b2 |
β |
nf_regnet_b3 |
β |
nf_regnet_b4 |
β |
nf_regnet_b5 |
β |
nf_resnet26 |
β |
nf_resnet50 |
β |
nf_resnet101 |
β |
nf_seresnet26 |
β |
nf_seresnet50 |
β |
nf_seresnet101 |
β |
nfnet_f0 |
β |
nfnet_f1 |
β |
nfnet_f2 |
β |
nfnet_f3 |
β |
nfnet_f4 |
β |
nfnet_f5 |
β |
nfnet_f6 |
β |
nfnet_f7 |
β |
nfnet_l0 |
β |
regnetv_040 |
β |
regnetv_064 |
β |
regnetx_002 |
β |
regnetx_004 |
β |
regnetx_004_tv |
β |
regnetx_006 |
β |
regnetx_008 |
β |
regnetx_016 |
β |
regnetx_032 |
β |
regnetx_040 |
β |
regnetx_064 |
β |
regnetx_080 |
β |
regnetx_120 |
β |
regnetx_160 |
β |
regnetx_320 |
β |
regnety_002 |
β |
regnety_004 |
β |
regnety_006 |
β |
regnety_008 |
β |
regnety_008_tv |
β |
regnety_016 |
β |
regnety_032 |
β |
regnety_040 |
β |
regnety_040_sgn |
β |
regnety_064 |
β |
regnety_080 |
β |
regnety_080_tv |
β |
regnety_120 |
β |
regnety_160 |
β |
regnety_320 |
β |
regnety_640 |
β |
regnety_1280 |
β |
regnety_2560 |
β |
regnetz_005 |
β |
regnetz_040 |
β |
regnetz_040_h |
β |
regnetz_b16 |
β |
regnetz_b16_evos |
β |
regnetz_c16 |
β |
regnetz_c16_evos |
β |
regnetz_d8 |
β |
regnetz_d8_evos |
β |
regnetz_d32 |
β |
regnetz_e8 |
β |
repghostnet_050 |
|
repghostnet_058 |
|
repghostnet_080 |
|
repghostnet_100 |
|
repghostnet_111 |
|
repghostnet_130 |
|
repghostnet_150 |
|
repghostnet_200 |
|
repvgg_a0 |
β |
repvgg_a1 |
β |
repvgg_a2 |
β |
repvgg_b0 |
β |
repvgg_b1 |
β |
repvgg_b1g4 |
β |
repvgg_b2 |
β |
repvgg_b2g4 |
β |
repvgg_b3 |
β |
repvgg_b3g4 |
β |
repvgg_d2se |
β |
res2net50_14w_8s |
β |
res2net50_26w_4s |
β |
res2net50_26w_6s |
β |
res2net50_26w_8s |
β |
res2net50_48w_2s |
β |
res2net50d |
β |
res2net101_26w_4s |
β |
res2net101d |
β |
res2next50 |
β |
resnest14d |
β |
resnest26d |
β |
resnest50d |
β |
resnest50d_1s4x24d |
β |
resnest50d_4s2x40d |
β |
resnest101e |
β |
resnest200e |
β |
resnest269e |
β |
resnet10t |
β |
resnet14t |
β |
resnet18 |
β |
resnet18d |
β |
resnet26 |
β |
resnet26d |
β |
resnet26t |
β |
resnet32ts |
β |
resnet33ts |
β |
resnet34 |
β |
resnet34d |
β |
resnet50 |
β |
resnet50_clip |
β |
resnet50_clip_gap |
β |
resnet50_gn |
β |
resnet50_mlp |
β |
resnet50c |
β |
resnet50d |
β |
resnet50s |
β |
resnet50t |
β |
resnet50x4_clip |
β |
resnet50x4_clip_gap |
β |
resnet50x16_clip |
β |
resnet50x16_clip_gap |
β |
resnet50x64_clip |
β |
resnet50x64_clip_gap |
β |
resnet51q |
β |
resnet61q |
β |
resnet101 |
β |
resnet101_clip |
β |
resnet101_clip_gap |
β |
resnet101c |
β |
resnet101d |
β |
resnet101s |
β |
resnet152 |
β |
resnet152c |
β |
resnet152d |
β |
resnet152s |
β |
resnet200 |
β |
resnet200d |
β |
resnetaa34d |
β |
resnetaa50 |
β |
resnetaa50d |
β |
resnetaa101d |
β |
resnetblur18 |
β |
resnetblur50 |
β |
resnetblur50d |
β |
resnetblur101d |
β |
resnetrs50 |
β |
resnetrs101 |
β |
resnetrs152 |
β |
resnetrs200 |
β |
resnetrs270 |
β |
resnetrs350 |
β |
resnetrs420 |
β |
resnetv2_18 |
β |
resnetv2_18d |
β |
resnetv2_34 |
β |
resnetv2_34d |
β |
resnetv2_50 |
β |
resnetv2_50d |
β |
resnetv2_50d_evos |
β |
resnetv2_50d_frn |
β |
resnetv2_50d_gn |
β |
resnetv2_50t |
β |
resnetv2_50x1_bit |
β |
resnetv2_50x3_bit |
β |
resnetv2_101 |
β |
resnetv2_101d |
β |
resnetv2_101x1_bit |
β |
resnetv2_101x3_bit |
β |
resnetv2_152 |
β |
resnetv2_152d |
β |
resnetv2_152x2_bit |
β |
resnetv2_152x4_bit |
β |
resnext26ts |
β |
resnext50_32x4d |
β |
resnext50d_32x4d |
β |
resnext101_32x4d |
β |
resnext101_32x8d |
β |
resnext101_32x16d |
β |
resnext101_32x32d |
β |
resnext101_64x4d |
β |
rexnet_100 |
β |
rexnet_130 |
β |
rexnet_150 |
β |
rexnet_200 |
β |
rexnet_300 |
β |
rexnetr_100 |
β |
rexnetr_130 |
β |
rexnetr_150 |
β |
rexnetr_200 |
β |
rexnetr_300 |
β |
sebotnet33ts_256 |
β |
sedarknet21 |
β |
sehalonet33ts |
β |
selecsls42 |
|
selecsls42b |
|
selecsls60 |
|
selecsls60b |
|
selecsls84 |
|
semnasnet_050 |
β |
semnasnet_075 |
β |
semnasnet_100 |
β |
semnasnet_140 |
β |
senet154 |
β |
seresnet18 |
β |
seresnet33ts |
β |
seresnet34 |
β |
seresnet50 |
β |
seresnet50t |
β |
seresnet101 |
β |
seresnet152 |
β |
seresnet152d |
β |
seresnet200d |
β |
seresnet269d |
β |
seresnetaa50d |
β |
seresnext26d_32x4d |
β |
seresnext26t_32x4d |
β |
seresnext26ts |
β |
seresnext50_32x4d |
β |
seresnext101_32x4d |
β |
seresnext101_32x8d |
β |
seresnext101_64x4d |
β |
seresnext101d_32x8d |
β |
seresnextaa101d_32x8d |
β |
seresnextaa201d_32x8d |
β |
skresnet18 |
β |
skresnet34 |
β |
skresnet50 |
β |
skresnet50d |
β |
skresnext50_32x4d |
β |
spnasnet_100 |
β |
tf_efficientnet_b0 |
β |
tf_efficientnet_b1 |
β |
tf_efficientnet_b2 |
β |
tf_efficientnet_b3 |
β |
tf_efficientnet_b4 |
β |
tf_efficientnet_b5 |
β |
tf_efficientnet_b6 |
β |
tf_efficientnet_b7 |
β |
tf_efficientnet_b8 |
β |
tf_efficientnet_cc_b0_4e |
β |
tf_efficientnet_cc_b0_8e |
β |
tf_efficientnet_cc_b1_8e |
β |
tf_efficientnet_el |
β |
tf_efficientnet_em |
β |
tf_efficientnet_es |
β |
tf_efficientnet_l2 |
β |
tf_efficientnet_lite0 |
β |
tf_efficientnet_lite1 |
β |
tf_efficientnet_lite2 |
β |
tf_efficientnet_lite3 |
β |
tf_efficientnet_lite4 |
β |
tf_efficientnetv2_b0 |
β |
tf_efficientnetv2_b1 |
β |
tf_efficientnetv2_b2 |
β |
tf_efficientnetv2_b3 |
β |
tf_efficientnetv2_l |
β |
tf_efficientnetv2_m |
β |
tf_efficientnetv2_s |
β |
tf_efficientnetv2_xl |
β |
tf_mixnet_l |
β |
tf_mixnet_m |
β |
tf_mixnet_s |
β |
tf_mobilenetv3_large_075 |
β |
tf_mobilenetv3_large_100 |
β |
tf_mobilenetv3_large_minimal_100 |
β |
tf_mobilenetv3_small_075 |
β |
tf_mobilenetv3_small_100 |
β |
tf_mobilenetv3_small_minimal_100 |
β |
tinynet_a |
β |
tinynet_b |
β |
tinynet_c |
β |
tinynet_d |
β |
tinynet_e |
β |
vgg11 |
|
vgg11_bn |
|
vgg13 |
|
vgg13_bn |
|
vgg16 |
|
vgg16_bn |
|
vgg19 |
|
vgg19_bn |
|
vovnet39a |
|
vovnet57a |
|
wide_resnet50_2 |
β |
wide_resnet101_2 |
β |
xception41 |
β |
xception41p |
β |
xception65 |
β |
xception65p |
β |
xception71 |
β |
Transformer-Style#
Transformer-style models (e.g., Swin Transformer, ConvNeXt) typically produce feature maps starting at a 1/4 scale, followed by 1/8, 1/16, and 1/32 scales
Encoder name |
Support dilation |
---|---|
caformer_b36 |
|
caformer_m36 |
|
caformer_s18 |
|
caformer_s36 |
|
convformer_b36 |
|
convformer_m36 |
|
convformer_s18 |
|
convformer_s36 |
|
convnext_atto |
β |
convnext_atto_ols |
β |
convnext_atto_rms |
β |
convnext_base |
β |
convnext_femto |
β |
convnext_femto_ols |
β |
convnext_large |
β |
convnext_large_mlp |
β |
convnext_nano |
β |
convnext_nano_ols |
β |
convnext_pico |
β |
convnext_pico_ols |
β |
convnext_small |
β |
convnext_tiny |
β |
convnext_tiny_hnf |
β |
convnext_xlarge |
β |
convnext_xxlarge |
β |
convnext_zepto_rms |
β |
convnext_zepto_rms_ols |
β |
convnextv2_atto |
β |
convnextv2_base |
β |
convnextv2_femto |
β |
convnextv2_huge |
β |
convnextv2_large |
β |
convnextv2_nano |
β |
convnextv2_pico |
β |
convnextv2_small |
β |
convnextv2_tiny |
β |
davit_base |
|
davit_base_fl |
|
davit_giant |
|
davit_huge |
|
davit_huge_fl |
|
davit_large |
|
davit_small |
|
davit_tiny |
|
edgenext_base |
|
edgenext_small |
|
edgenext_small_rw |
|
edgenext_x_small |
|
edgenext_xx_small |
|
efficientformer_l1 |
|
efficientformer_l3 |
|
efficientformer_l7 |
|
efficientformerv2_l |
|
efficientformerv2_s0 |
|
efficientformerv2_s1 |
|
efficientformerv2_s2 |
|
efficientvit_b0 |
|
efficientvit_b1 |
|
efficientvit_b2 |
|
efficientvit_b3 |
|
efficientvit_l1 |
|
efficientvit_l2 |
|
efficientvit_l3 |
|
fastvit_ma36 |
|
fastvit_mci0 |
|
fastvit_mci1 |
|
fastvit_mci2 |
|
fastvit_s12 |
|
fastvit_sa12 |
|
fastvit_sa24 |
|
fastvit_sa36 |
|
fastvit_t8 |
|
fastvit_t12 |
|
focalnet_base_lrf |
|
focalnet_base_srf |
|
focalnet_huge_fl3 |
|
focalnet_huge_fl4 |
|
focalnet_large_fl3 |
|
focalnet_large_fl4 |
|
focalnet_small_lrf |
|
focalnet_small_srf |
|
focalnet_tiny_lrf |
|
focalnet_tiny_srf |
|
focalnet_xlarge_fl3 |
|
focalnet_xlarge_fl4 |
|
hgnet_base |
|
hgnet_small |
|
hgnet_tiny |
|
hgnetv2_b0 |
|
hgnetv2_b1 |
|
hgnetv2_b2 |
|
hgnetv2_b3 |
|
hgnetv2_b4 |
|
hgnetv2_b5 |
|
hgnetv2_b6 |
|
hiera_base_224 |
|
hiera_base_abswin_256 |
|
hiera_base_plus_224 |
|
hiera_huge_224 |
|
hiera_large_224 |
|
hiera_small_224 |
|
hiera_small_abswin_256 |
|
hiera_tiny_224 |
|
hieradet_small |
|
inception_next_base |
|
inception_next_small |
|
inception_next_tiny |
|
mambaout_base |
|
mambaout_base_plus_rw |
|
mambaout_base_short_rw |
|
mambaout_base_tall_rw |
|
mambaout_base_wide_rw |
|
mambaout_femto |
|
mambaout_kobe |
|
mambaout_small |
|
mambaout_small_rw |
|
mambaout_tiny |
|
mvitv2_base |
|
mvitv2_base_cls |
|
mvitv2_huge_cls |
|
mvitv2_large |
|
mvitv2_large_cls |
|
mvitv2_small |
|
mvitv2_small_cls |
|
mvitv2_tiny |
|
nest_base |
|
nest_base_jx |
|
nest_small |
|
nest_small_jx |
|
nest_tiny |
|
nest_tiny_jx |
|
nextvit_base |
|
nextvit_large |
|
nextvit_small |
|
poolformer_m36 |
|
poolformer_m48 |
|
poolformer_s12 |
|
poolformer_s24 |
|
poolformer_s36 |
|
poolformerv2_m36 |
|
poolformerv2_m48 |
|
poolformerv2_s12 |
|
poolformerv2_s24 |
|
poolformerv2_s36 |
|
pvt_v2_b0 |
|
pvt_v2_b1 |
|
pvt_v2_b2 |
|
pvt_v2_b2_li |
|
pvt_v2_b3 |
|
pvt_v2_b4 |
|
pvt_v2_b5 |
|
rdnet_base |
|
rdnet_large |
|
rdnet_small |
|
rdnet_tiny |
|
repvit_m0_9 |
|
repvit_m1 |
|
repvit_m1_0 |
|
repvit_m1_1 |
|
repvit_m1_5 |
|
repvit_m2 |
|
repvit_m2_3 |
|
repvit_m3 |
|
sam2_hiera_base_plus |
|
sam2_hiera_large |
|
sam2_hiera_small |
|
sam2_hiera_tiny |
|
swin_base_patch4_window7_224 |
|
swin_base_patch4_window12_384 |
|
swin_large_patch4_window7_224 |
|
swin_large_patch4_window12_384 |
|
swin_s3_base_224 |
|
swin_s3_small_224 |
|
swin_s3_tiny_224 |
|
swin_small_patch4_window7_224 |
|
swin_tiny_patch4_window7_224 |
|
swinv2_base_window8_256 |
|
swinv2_base_window12_192 |
|
swinv2_base_window12to16_192to256 |
|
swinv2_base_window12to24_192to384 |
|
swinv2_base_window16_256 |
|
swinv2_cr_base_224 |
|
swinv2_cr_base_384 |
|
swinv2_cr_base_ns_224 |
|
swinv2_cr_giant_224 |
|
swinv2_cr_giant_384 |
|
swinv2_cr_huge_224 |
|
swinv2_cr_huge_384 |
|
swinv2_cr_large_224 |
|
swinv2_cr_large_384 |
|
swinv2_cr_small_224 |
|
swinv2_cr_small_384 |
|
swinv2_cr_small_ns_224 |
|
swinv2_cr_small_ns_256 |
|
swinv2_cr_tiny_224 |
|
swinv2_cr_tiny_384 |
|
swinv2_cr_tiny_ns_224 |
|
swinv2_large_window12_192 |
|
swinv2_large_window12to16_192to256 |
|
swinv2_large_window12to24_192to384 |
|
swinv2_small_window8_256 |
|
swinv2_small_window16_256 |
|
swinv2_tiny_window8_256 |
|
swinv2_tiny_window16_256 |
|
tiny_vit_5m_224 |
|
tiny_vit_11m_224 |
|
tiny_vit_21m_224 |
|
tiny_vit_21m_384 |
|
tiny_vit_21m_512 |
|
tresnet_l |
|
tresnet_m |
|
tresnet_v2_l |
|
tresnet_xl |
|
twins_pcpvt_base |
|
twins_pcpvt_large |
|
twins_pcpvt_small |
|
twins_svt_base |
|
twins_svt_large |
|
twins_svt_small |