update performance info

add some coming soon info

add some coming soon info

add some coming soon info

Author: Yang

configs/bit/README.md

@@ -69,16 +69,9 @@ Our reproduced model performance on ImageNet-1K is reported as follows.
 
 Experiments are tested on ascend 910* with mindspore 2.5.0 graph mode.
 
-*coming soon*
-
-Experiments are tested on ascend 910 with mindspore 2.5.0 graph mode.
-
-
-| model name   | params(M) | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | acc@top1 | acc@top5 | recipe                                                                                         | weight                                                                                  |
-| ------------ | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | ---------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------- |
-| bit_resnet50 | 25.55     | 8     | 32         | 224x224    | O2        | 146s          | 74.52   | 3413.33 | 76.81    | 93.17    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/bit/bit_resnet50_ascend.yaml) | [weights](https://download.mindspore.cn/toolkits/mindcv/bit/BiT_resnet50-1e4795a4.ckpt) |
-
-
+| model name  | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | recipe                                                                                           | weight                                                                                                  | acc@top1 | acc@top5 |
+| ----------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | ------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------- | -------- | -------- |
+| bit         | 8     | 32         | 224x224    | O0        | 171s          | 60.48   | 4232.80 | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/bit/bit_resnet50_ascend.yaml)             | [weights](https://download-mindspore.osinfra.cn/toolkits/mindcv/bit/BiT_resnet50-77dcaf0f-910v2.ckpt)             | 76.72    | 93.25    |
 
 ### Notes
 - top-1 and top-5: Accuracy reported on the validation set of ImageNet-1K.

configs/cmt/README.md

@@ -67,13 +67,10 @@ Our reproduced model performance on ImageNet-1K is reported as follows.
 
 Experiments are tested on ascend 910* with mindspore 2.5.0 graph mode.
 
-*coming soon*
+| model name  | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | recipe                                                                                           | weight                                                                                          | acc@top1 | acc@top5 |
+| ----------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | ------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------- | -------- | -------- |
+| cmt         | 8     | 128        | 224x224    | O2        | 1210s         | 324.95  | 3151.25 | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/cmt/cmt_small_ascend.yaml)             | [weights](https://download-mindspore.osinfra.cn/toolkits/mindcv/cmt/cmt_small-6858ee22.ckpt)             | 83.15    | 96.48    |
 
-Experiments are tested on ascend 910 with mindspore 2.5.0 graph mode.
-
-| model name | params(M) | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | acc@top1 | acc@top5 | recipe                                                                                      | weight                                                                               |
-| ---------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | ------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------ |
-| cmt_small  | 26.09     | 8     | 128        | 224x224    | O2        | 1268s         | 500.64  | 2048.01 | 83.24    | 96.41    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/cmt/cmt_small_ascend.yaml) | [weights](https://download.mindspore.cn/toolkits/mindcv/cmt/cmt_small-6858ee22.ckpt) |
 
 ### Notes
 - top-1 and top-5: Accuracy reported on the validation set of ImageNet-1K.

configs/coat/README.md

@@ -63,17 +63,9 @@ Our reproduced model performance on ImageNet-1K is reported as follows.
 
 Experiments are tested on ascend 910* with mindspore 2.5.0 graph mode.
 
-*coming soon*
-
-
-Experiments are tested on ascend 910 with mindspore 2.5.0 graph mode.
-
-
-
-
-| model name | params(M) | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | acc@top1 | acc@top5 | recipe                                                                                       | weight                                                                                |
-| ---------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | -------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- |
-| coat_tiny  | 5.50      | 8     | 32         | 224x224    | O2        | 543s          | 254.95  | 1003.92 | 79.67    | 94.88    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/coat/coat_tiny_ascend.yaml) | [weights](https://download.mindspore.cn/toolkits/mindcv/coat/coat_tiny-071cb792.ckpt) |
+| model name  | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | recipe                                                                                           | weight                                                                                         | acc@top1 | acc@top5 |
+| ----------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | ------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------- | -------- | -------- |
+| coat        | 8     | 32         | 224x224    | O2        | 644s          | 373.00  | 686.33  | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/coat/coat_lite_tiny_ascend.yaml)           | [weights](https://download-mindspore.osinfra.cn/toolkits/mindcv/coat/coat_tiny-dcca16b1-910v2.ckpt)           | 79.27    | 94.29    |
 
 
 

configs/convit/README.md

@@ -80,13 +80,6 @@ Experiments are tested on ascend 910* with mindspore 2.5.0 graph mode.
 | ----------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | ------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------- |
 | convit_tiny | 5.71      | 8     | 256        | 224x224    | O2        | 153s          | 226.51  | 9022.03 | 73.79    | 91.70    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/convit/convit_tiny_ascend.yaml) | [weights](https://download-mindspore.osinfra.cn/toolkits/mindcv/convit/convit_tiny-1961717e-910v2.ckpt) |
 
-Experiments are tested on ascend 910 with mindspore 2.5.0 graph mode.
-
-| model name  | params(M) | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | acc@top1 | acc@top5 | recipe                                                                                           | weight                                                                                    |
-| ----------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | ------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------- |
-| convit_tiny | 5.71      | 8     | 256        | 224x224    | O2        | 133s          | 231.62  | 8827.59 | 73.66    | 91.72    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/convit/convit_tiny_ascend.yaml) | [weights](https://download.mindspore.cn/toolkits/mindcv/convit/convit_tiny-e31023f2.ckpt) |
-
-
 ### Notes
 - top-1 and top-5: Accuracy reported on the validation set of ImageNet-1K.
 

configs/convnext/README.md

@@ -78,12 +78,6 @@ Experiments are tested on ascend 910* with mindspore 2.5.0 graph mode.
 | ------------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | ---------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------- |
 | convnext_tiny | 28.59     | 8     | 16         | 224x224    | O2        | 137s          | 48.7    | 2612.24 | 81.28    | 95.61    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/convnext/convnext_tiny_ascend.yaml) | [weights](https://download-mindspore.osinfra.cn/toolkits/mindcv/convnext/convnext_tiny-db11dc82-910v2.ckpt) |
 
-Experiments are tested on ascend 910 with mindspore 2.5.0 graph mode.
-
-| model name    | params(M) | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | acc@top1 | acc@top5 | recipe                                                                                               | weight                                                                                        |
-| ------------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | ---------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------- |
-| convnext_tiny | 28.59     | 8     | 16         | 224x224    | O2        | 127s          | 66.79   | 1910.45 | 81.91    | 95.79    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/convnext/convnext_tiny_ascend.yaml) | [weights](https://download.mindspore.cn/toolkits/mindcv/convnext/convnext_tiny-ae5ff8d7.ckpt) |
-
 ### Notes
 - top-1 and top-5: Accuracy reported on the validation set of ImageNet-1K.
 

configs/convnextv2/README.md

@@ -77,12 +77,6 @@ Experiments are tested on ascend 910* with mindspore 2.5.0 graph mode.
 | --------------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | -------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------- |
 | convnextv2_tiny | 28.64     | 8     | 128        | 224x224    | O2        | 268s          | 257.2   | 3984.44 | 82.39    | 95.95    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/convnextv2/convnextv2_tiny_ascend.yaml) | [weights](https://download-mindspore.osinfra.cn/toolkits/mindcv/convnextv2/convnextv2_tiny-a35b79ce-910v2.ckpt) |
 
-Experiments are tested on ascend 910 with mindspore 2.5.0 graph mode.
-
-| model name      | params(M) | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | acc@top1 | acc@top5 | recipe                                                                                                   | weight                                                                                            |
-| --------------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | -------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------- |
-| convnextv2_tiny | 28.64     | 8     | 128        | 224x224    | O2        | 237s          | 400.20  | 2560.00 | 82.43    | 95.98    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/convnextv2/convnextv2_tiny_ascend.yaml) | [weights](https://download.mindspore.cn/toolkits/mindcv/convnextv2/convnextv2_tiny-d441ba2c.ckpt) |
-
 ### Notes
 - top-1 and top-5: Accuracy reported on the validation set of ImageNet-1K.
 

configs/crossvit/README.md

@@ -73,12 +73,6 @@ Experiments are tested on ascend 910* with mindspore 2.5.0 graph mode.
 | ---------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | ------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------- |
 | crossvit_9 | 8.55      | 8     | 256        | 240x240    | O2        | 221s          | 514.36  | 3984.44 | 73.38    | 91.51    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/crossvit/crossvit_9_ascend.yaml) | [weights](https://download-mindspore.osinfra.cn/toolkits/mindcv/crossvit/crossvit_9-32c69c96-910v2.ckpt) |
 
-Experiments are tested on ascend 910 with mindspore 2.5.0 graph mode.
-
-| model name | params(M) | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | acc@top1 | acc@top5 | recipe                                                                                            | weight                                                                                     |
-| ---------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | ------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------ |
-| crossvit_9 | 8.55      | 8     | 256        | 240x240    | O2        | 206s          | 550.79  | 3719.30 | 73.56    | 91.79    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/crossvit/crossvit_9_ascend.yaml) | [weights](https://download.mindspore.cn/toolkits/mindcv/crossvit/crossvit_9-e74c8e18.ckpt) |
-
 ### Notes
 - top-1 and top-5: Accuracy reported on the validation set of ImageNet-1K.
 

configs/densenet/README.md

@@ -82,12 +82,6 @@ Experiments are tested on ascend 910* with mindspore 2.5.0 graph mode.
 | ----------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | --------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- |
 | densenet121 | 8.06      | 8     | 32         | 224x224    | O2        | 300s          | 47,34   | 5446.81 | 75.67    | 92.77    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/densenet/densenet_121_ascend.yaml) | [weights](https://download-mindspore.osinfra.cn/toolkits/mindcv/densenet/densenet121-bf4ab27f-910v2.ckpt) |
 
-Experiments are tested on ascend 910 with mindspore 2.5.0 graph mode.
-
-| model name  | params(M) | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | acc@top1 | acc@top5 | recipe                                                                                              | weight                                                                                             |
-| ----------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | --------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
-| densenet121 | 8.06      | 8     | 32         | 224x224    | O2        | 191s          | 43.28   | 5914.97 | 75.64    | 92.84    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/densenet/densenet_121_ascend.yaml) | [weights](https://download.mindspore.cn/toolkits/mindcv/densenet/densenet121-120_5004_Ascend.ckpt) |
-
 ### Notes
 - top-1 and top-5: Accuracy reported on the validation set of ImageNet-1K.
 

configs/dpn/README.md

@@ -75,14 +75,10 @@ Our reproduced model performance on ImageNet-1K is reported as follows.
 
 Experiments are tested on ascend 910* with mindspore 2.5.0 graph mode.
 
-*coming soon*
+| model name  | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | recipe                                                                                           | weight                                                                                          | acc@top1 | acc@top5 |
+| ----------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | ------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------- | -------- | -------- |
+| dpn         | 8     | 32         | 224x224    | O2        | 336s          | 76.23   | 3358.26 | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/dpn/dpn131_ascend.yaml)             | [weights](https://download-mindspore.osinfra.cn/toolkits/mindcv/dpn/dpn131-47f084b3.ckpt)             | 76.00    | 92.45    |
 
-Experiments are tested on ascend 910 with mindspore 2.5.0 graph mode.
-
-
-| model name | params(M) | cards | batch size | resolution | jit level | graph compile | ms/step | img/s   | acc@top1 | acc@top5 | recipe                                                                                  | weight                                                                          |
-| ---------- | --------- | ----- | ---------- | ---------- | --------- | ------------- | ------- | ------- | -------- | -------- | --------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------- |
-| dpn92      | 37.79     | 8     | 32         | 224x224    | O2        | 293s          | 78.22   | 3272.82 | 79.46    | 94.49    | [yaml](https://github.com/mindspore-lab/mindcv/blob/main/configs/dpn/dpn92_ascend.yaml) | [weights](https://download.mindspore.cn/toolkits/mindcv/dpn/dpn92-e3e0fca.ckpt) |
 
 ### Notes
 - top-1 and top-5: Accuracy reported on the validation set of ImageNet-1K.