From 1e3800cc16ab9c69ae40e11f4374d76ef0350aa0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?P=C5=99emysl=20Eric=20Janouch?= Date: Sun, 21 Jan 2024 10:38:46 +0100 Subject: [PATCH] deeptagger: fix Caformer By using the smaller resolution, it starts noticing 2girls, otherwise the output appears similar. --- deeptagger/README.adoc | 24 ++++++++++++------------ deeptagger/download.sh | 10 ++++++---- 2 files changed, 18 insertions(+), 16 deletions(-) diff --git a/deeptagger/README.adoc b/deeptagger/README.adoc index 7b338af..2973db9 100644 --- a/deeptagger/README.adoc +++ b/deeptagger/README.adoc @@ -62,16 +62,17 @@ GPU inference [cols="<,>,>", options=header] |=== |Model|Batch size|Time -|ML-Danbooru Caformer dec-5-97527|16|OOM |WD v1.4 ViT v2 (batch)|16|19 s |DeepDanbooru|16|21 s |WD v1.4 SwinV2 v2 (batch)|16|21 s +|ML-Danbooru Caformer dec-5-97527|16|25 s |WD v1.4 ViT v2 (batch)|4|27 s |WD v1.4 SwinV2 v2 (batch)|4|30 s |DeepDanbooru|4|31 s |ML-Danbooru TResNet-D 6-30000|16|31 s |WD v1.4 MOAT v2 (batch)|16|31 s |WD v1.4 ConvNeXT v2 (batch)|16|32 s +|ML-Danbooru Caformer dec-5-97527|4|32 s |WD v1.4 ConvNeXTV2 v2 (batch)|16|36 s |ML-Danbooru TResNet-D 6-30000|4|39 s |WD v1.4 ConvNeXT v2 (batch)|4|39 s @@ -79,7 +80,7 @@ GPU inference |WD v1.4 ConvNeXTV2 v2 (batch)|4|43 s |WD v1.4 ViT v2|1|43 s |WD v1.4 ViT v2 (batch)|1|43 s -|ML-Danbooru Caformer dec-5-97527|4|48 s +|ML-Danbooru Caformer dec-5-97527|1|52 s |DeepDanbooru|1|53 s |WD v1.4 MOAT v2|1|53 s |WD v1.4 ConvNeXT v2|1|54 s @@ -90,7 +91,6 @@ GPU inference |WD v1.4 ConvNeXTV2 v2|1|56 s |ML-Danbooru TResNet-D 6-30000|1|58 s |WD v1.4 ConvNeXTV2 v2 (batch)|1|58 s -|ML-Danbooru Caformer dec-5-97527|1|73 s |=== CPU inference @@ -110,6 +110,7 @@ CPU inference |WD v1.4 ConvNeXTV2 v2|1|245 s |WD v1.4 ConvNeXTV2 v2 (batch)|4|268 s |WD v1.4 ViT v2 (batch)|16|270 s +|ML-Danbooru Caformer dec-5-97527|4|270 s |WD v1.4 ConvNeXT v2 (batch)|1|272 s |WD v1.4 SwinV2 v2 (batch)|4|277 s |WD v1.4 ViT v2 (batch)|4|277 s @@ -117,6 +118,7 @@ CPU inference |WD v1.4 SwinV2 v2 (batch)|1|300 s |WD v1.4 SwinV2 v2|1|302 s |WD v1.4 SwinV2 v2 (batch)|16|305 s +|ML-Danbooru Caformer dec-5-97527|16|305 s |WD v1.4 MOAT v2 (batch)|4|307 s |WD v1.4 ViT v2|1|308 s |WD v1.4 ViT v2 (batch)|1|311 s @@ -124,9 +126,7 @@ CPU inference |WD v1.4 MOAT v2|1|332 s |WD v1.4 MOAT v2 (batch)|16|335 s |WD v1.4 MOAT v2 (batch)|1|339 s -|ML-Danbooru Caformer dec-5-97527|4|637 s -|ML-Danbooru Caformer dec-5-97527|16|689 s -|ML-Danbooru Caformer dec-5-97527|1|829 s +|ML-Danbooru Caformer dec-5-97527|1|352 s |=== Model benchmarks (macOS) @@ -166,12 +166,12 @@ GPU inference |WD v1.4 ConvNeXTV2 v2 (batch)|1|160 s |WD v1.4 MOAT v2 (batch)|1|165 s |WD v1.4 SwinV2 v2|1|166 s +|ML-Danbooru Caformer dec-5-97527|1|263 s |WD v1.4 ConvNeXT v2|1|273 s |WD v1.4 MOAT v2|1|273 s |WD v1.4 ConvNeXTV2 v2|1|340 s -|ML-Danbooru Caformer dec-5-97527|1|551 s -|ML-Danbooru Caformer dec-5-97527|4|swap hell -|ML-Danbooru Caformer dec-5-97527|8|swap hell +|ML-Danbooru Caformer dec-5-97527|4|445 s +|ML-Danbooru Caformer dec-5-97527|8|1790 s |WD v1.4 MOAT v2 (batch)|4|kernel panic |=== @@ -189,11 +189,14 @@ CPU inference |WD v1.4 SwinV2 v2 (batch)|1|98 s |ML-Danbooru TResNet-D 6-30000|4|99 s |WD v1.4 SwinV2 v2|1|99 s +|ML-Danbooru Caformer dec-5-97527|4|110 s +|ML-Danbooru Caformer dec-5-97527|8|110 s |WD v1.4 ViT v2 (batch)|4|111 s |WD v1.4 ViT v2 (batch)|8|111 s |WD v1.4 ViT v2 (batch)|1|113 s |WD v1.4 ViT v2|1|113 s |ML-Danbooru TResNet-D 6-30000|1|118 s +|ML-Danbooru Caformer dec-5-97527|1|122 s |WD v1.4 ConvNeXT v2 (batch)|8|124 s |WD v1.4 ConvNeXT v2 (batch)|4|125 s |WD v1.4 ConvNeXTV2 v2 (batch)|8|129 s @@ -206,9 +209,6 @@ CPU inference |WD v1.4 MOAT v2 (batch)|1|156 s |WD v1.4 MOAT v2|1|156 s |WD v1.4 ConvNeXTV2 v2 (batch)|1|157 s -|ML-Danbooru Caformer dec-5-97527|4|241 s -|ML-Danbooru Caformer dec-5-97527|8|241 s -|ML-Danbooru Caformer dec-5-97527|1|262 s |=== Comparison with WDMassTagger diff --git a/deeptagger/download.sh b/deeptagger/download.sh index 29f651e..7336f35 100755 --- a/deeptagger/download.sh +++ b/deeptagger/download.sh @@ -115,7 +115,7 @@ wd14() { # These models are an undocumented mess, thus using ONNX preconversions. mldanbooru() { - local name=$1 basename=$2 + local name=$1 size=$2 basename=$3 status "$name" if ! [ -d ml-danbooru-onnx ] @@ -138,7 +138,7 @@ mldanbooru() { channels=rgb normalize=true pad=stretch - size=640 + size=$size interpret=sigmoid END } @@ -157,5 +157,7 @@ wd14 'WD v1.4 SwinV2 v2' 'SmilingWolf/wd-v1-4-swinv2-tagger-v2' wd14 'WD v1.4 MOAT v2' 'SmilingWolf/wd-v1-4-moat-tagger-v2' # As suggested by author https://github.com/IrisRainbowNeko/ML-Danbooru-webui -mldanbooru 'ML-Danbooru Caformer dec-5-97527' 'ml_caformer_m36_dec-5-97527.onnx' -mldanbooru 'ML-Danbooru TResNet-D 6-30000' 'TResnet-D-FLq_ema_6-30000.onnx' +mldanbooru 'ML-Danbooru Caformer dec-5-97527' \ + 448 'ml_caformer_m36_dec-5-97527.onnx' +mldanbooru 'ML-Danbooru TResNet-D 6-30000' \ + 640 'TResnet-D-FLq_ema_6-30000.onnx'