onnx

onnx

README.md

@@ -8,23 +8,24 @@ PyTorch implementation and pretrained models for DINO. For details, see **Emergi
 </div>
 
 ## Pretrained models
-You can choose to download only the weights of the pretrained backbone used for downstream tasks, or the full checkpoint which contains backbone and projection head weights for both student and teacher networks. We also provide the training and evaluation logs.
+You can choose to download only the weights of the pretrained backbone used for downstream tasks, or the full checkpoint which contains backbone and projection head weights for both student and teacher networks. We also provide the backbone in `onnx` format, as well as detailed arguments and training/evaluation logs.
 
 <table>
   <tr>
     <th>arch</th>
     <th>params</th>
     <th>k-nn</th>
     <th>linear</th>
-    <th colspan="5">download</th>
+    <th colspan="6">download</th>
   </tr>
   <tr>
     <td>DeiT-S/16</td>
     <td>21M</td>
     <td>74.5%</td>
     <td>77.0%</td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall16_pretrain/dino_deitsmall16_pretrain.pth">backbone only</a></td>
-    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall16_pretrain/dino_deitsmall16_pretrain_full_checkpoint.pth">full checkpoint</a></td>
+    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall16_pretrain/dino_deitsmall16_pretrain_full_checkpoint.pth">full ckpt</a></td>
+    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall16_pretrain/dino_deits16.onnx">onnx</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall16_pretrain/args.txt">args</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall16_pretrain/dino_deitsmall16_pretrain_log.txt">logs</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall16_pretrain/dino_deitsmall16_pretrain_eval_linear_log.txt">eval logs</a></td>
@@ -35,7 +36,8 @@ You can choose to download only the weights of the pretrained backbone used for
     <td>78.3%</td>
     <td>79.7%</td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall8_pretrain/dino_deitsmall8_pretrain.pth">backbone only</a></td>
-    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall8_pretrain/dino_deitsmall8_pretrain_full_checkpoint.pth">full checkpoint</a></td>
+    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall8_pretrain/dino_deitsmall8_pretrain_full_checkpoint.pth">full ckpt</a></td>
+    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall8_pretrain/dino_deits8.onnx">onnx</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall8_pretrain/args.txt">args</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall8_pretrain/dino_deitsmall8_pretrain_log.txt">logs</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall8_pretrain/dino_deitsmall8_pretrain_eval_linear_log.txt">eval logs</a></td>
@@ -46,7 +48,8 @@ You can choose to download only the weights of the pretrained backbone used for
     <td>76.1%</td>
     <td>78.2%</td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase16_pretrain/dino_vitbase16_pretrain.pth">backbone only</a></td>
-    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase16_pretrain/dino_vitbase16_pretrain_full_checkpoint.pth">full checkpoint</a></td>
+    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase16_pretrain/dino_vitbase16_pretrain_full_checkpoint.pth">full ckpt</a></td>
+    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase16_pretrain/dino_vitb16.onnx">onnx</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase16_pretrain/args.txt">args</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase16_pretrain/dino_vitbase16_pretrain_log.txt">logs</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase16_pretrain/dino_vitbase16_pretrain_eval_linear_log.txt">eval logs</a></td>
@@ -57,7 +60,8 @@ You can choose to download only the weights of the pretrained backbone used for
     <td>77.4%</td>
     <td>80.1%</td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase8_pretrain/dino_vitbase8_pretrain.pth">backbone only</a></td>
-    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase8_pretrain/dino_vitbase8_pretrain_full_checkpoint.pth">full checkpoint</a></td>
+    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase8_pretrain/dino_vitbase8_pretrain_full_checkpoint.pth">full ckpt</a></td>
+    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase8_pretrain/dino_vitb8.onnx">onnx</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase8_pretrain/args.txt">args</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase8_pretrain/dino_vitbase8_pretrain_log.txt">logs</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase8_pretrain/dino_vitbase8_pretrain_eval_linear_log.txt">eval logs</a></td>
@@ -68,7 +72,8 @@ You can choose to download only the weights of the pretrained backbone used for
     <td>67.5%</td>
     <td>75.3%</td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_resnet50_pretrain/dino_resnet50_pretrain.pth">backbone only</a></td>
-    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_resnet50_pretrain/dino_resnet50_pretrain_full_checkpoint.pth">full checkpoint</a></td>
+    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_resnet50_pretrain/dino_resnet50_pretrain_full_checkpoint.pth">full ckpt</a></td>
+    <td><a href="https://dl.fbaipublicfiles.com/dino/dino_resnet50_pretrain/dino_resnet50.onnx">onnx</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_resnet50_pretrain/args.txt">args</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_resnet50_pretrain/dino_resnet50_pretrain_log.txt">logs</a></td>
     <td><a href="https://dl.fbaipublicfiles.com/dino/dino_resnet50_pretrain/dino_resnet50_pretrain_eval_linear_log.txt">eval logs</a></td>