[Doc] update benchmark add supported-model-list (#286)

* update benchmark add supported-model-list

* fix lint

* fix lint

* loc mmocr maximum version

csrc/core/utils/device_utils.h

@@ -29,7 +29,6 @@ MMDEPLOY_API Result<Mat> MakeAvailableOnDevice(const Mat& src, const Device& dev
 MMDEPLOY_API Result<Tensor> MakeAvailableOnDevice(const Tensor& src, const Device& device,
                                                   Stream& stream);
 
-
 // Calls stream.Wait() on destruction if active is true. This class is used to force a wait
 // operation before intermediate variables goes out of scope. Add variables in consideration to the
 // tailing parameter pack to ensure correctness (this make sure SyncOnScopeExit is created later

docs/en/benchmark.md

@@ -326,10 +326,10 @@ Users can directly test the speed through [how_to_measure_performance_of_models.
     <td align="center">Mask-RCNN</td>
     <td align="center">COCO</td>
     <td align="center">1x3x800x1344</td>
-    <td align="center">320.86 </td>
+    <td align="center">104.83</td>
-    <td align="center">3.12</td>
+    <td align="center">9.54</td>
-    <td align="center">241.32</td>
+    <td align="center">58.27</td>
-    <td align="center">4.14</td>
+    <td align="center">17.16</td>
     <td align="center">-</td>
     <td align="center">-</td>
     <td align="center">-</td>

docs/en/supported_models.md

@@ -3,7 +3,7 @@
 The table below lists the models that are guaranteed to be exportable to other backends.
 
 | Model                     | Codebase         | OnnxRuntime | TensorRT | NCNN  | PPLNN | OpenVINO |                                          Model config                                          |
-|:--------------------------|:-----------------|:-----------:|:--------:|:----:|:-----:|:--------:|:----------------------------------------------------------------------------------------------:|
+| :------------------------ | :--------------- | :---------: | :------: | :---: | :---: | :------: | :--------------------------------------------------------------------------------------------: |
 | RetinaNet                 | MMDetection      |      Y      |    Y     |   Y   |   Y   |    Y     |       [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/retinanet)        |
 | Faster R-CNN              | MMDetection      |      Y      |    Y     |   Y   |   Y   |    Y     |      [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn)       |
 | YOLOv3                    | MMDetection      |      Y      |    Y     |   Y   |   N   |    Y     |          [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/yolo)          |
@@ -16,7 +16,7 @@ The table below lists the models that are guaranteed to be exportable to other b
 | ATSS                      | MMDetection      |      Y      |    Y     |   N   |   N   |    Y     |          [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/atss)          |
 | GFL                       | MMDetection      |      Y      |    Y     |   N   |   ?   |    Y     |          [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/gfl)           |
 | Cascade R-CNN             | MMDetection      |      Y      |    Y     |   N   |   Y   |    Y     |      [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/cascade_rcnn)      |
-| Cascade Mask R-CNN        | MMDetection      |      Y      |    N     |  N   |   N   |    Y     |      [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/cascade_rcnn)      |
+| Cascade Mask R-CNN        | MMDetection      |      Y      |    Y     |   N   |   N   |    Y     |      [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/cascade_rcnn)      |
 | VFNet                     | MMDetection      |      N      |    N     |   N   |   N   |    Y     |         [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/vfnet)          |
 | ResNet                    | MMClassification |      Y      |    Y     |   Y   |   Y   |    Y     |      [config](https://github.com/open-mmlab/mmclassification/tree/master/configs/resnet)       |
 | ResNeXt                   | MMClassification |      Y      |    Y     |   Y   |   Y   |    Y     |      [config](https://github.com/open-mmlab/mmclassification/tree/master/configs/resnext)      |

docs/zh_cn/benchmark.md

@@ -327,10 +327,10 @@ GPU: ncnn, TensorRT, PPLNN
     <td align="center">Mask-RCNN</td>
     <td align="center">COCO</td>
     <td align="center">1x3x800x1344</td>
-    <td align="center">320.86 </td>
+    <td align="center">104.83</td>
-    <td align="center">3.12</td>
+    <td align="center">9.54</td>
-    <td align="center">241.32</td>
+    <td align="center">58.27</td>
-    <td align="center">4.14</td>
+    <td align="center">17.16</td>
     <td align="center">-</td>
     <td align="center">-</td>
     <td align="center">-</td>

requirements/optional.txt

@@ -1,7 +1,7 @@
 mmcls>=0.15.0,<=0.19.0
 mmdet>=2.19.0,<=2.20.0
 mmedit
-mmocr>=0.3.0
+mmocr>=0.3.0,<=0.4.1
 mmpose>=0.24.0
 mmsegmentation
 onnxruntime>=1.8.0

tools/deploy.py

@@ -276,7 +276,8 @@ def main():
                 show_result=args.show),
             ret_value=ret_value)
     else:
-        logger.warning('\"visualize_model\" has been skipped may be because it\'s \
+        logger.warning(
+            '\"visualize_model\" has been skipped may be because it\'s \
             running on a headless device.')
     logger.info('All process success.')