diff --git a/docs/en/benchmark.md b/docs/en/benchmark.md
index 6c00a456f..73533a6d8 100644
--- a/docs/en/benchmark.md
+++ b/docs/en/benchmark.md
@@ -557,7 +557,7 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
| 77.74 |
77.75 |
77.63 |
- ? |
+ 77.73 |
$MMCLS_DIR/configs/resnext/resnext50_32x4d_b32x8_imagenet.py |
@@ -567,7 +567,7 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
| 93.84 |
93.83 |
93.72 |
- ? |
+ 93.84 |
| ShuffleNetV1 1.0x |
@@ -578,7 +578,7 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
68.13 |
68.13 |
67.71 |
- ? |
+ 68.11 |
$MMCLS_DIR/configs/shufflenet_v1/shufflenet_v1_1x_b64x16_linearlr_bn_nowd_imagenet.py |
@@ -588,7 +588,7 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
| 87.81 |
87.81 |
87.58 |
- ? |
+ 87.80 |
@@ -600,7 +600,7 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
| 69.55 |
69.54 |
69.10 |
- ? |
+ 69.54 |
$MMCLS_DIR/configs/shufflenet_v2/shufflenet_v2_1x_b64x16_linearlr_bn_nowd_imagenet.py |
@@ -610,7 +610,7 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
| 88.92 |
88.91 |
88.58 |
- ? |
+ 88.92 |
@@ -623,8 +623,8 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
71.86 |
71.87 |
70.91 |
- ? |
- $MMEDIT_DIR/configs/restorers/real_esrgan/realesrnet_c64b23g32_12x4_lr2e-4_1000k_df2k_ost.py |
+ 71.84 |
+ $MMCLS_DIR/configs/mobilenet_v2/mobilenet_v2_b32x8_imagenet.py |
| top-5 |
@@ -633,7 +633,7 @@ Users can directly test the performance through [how_to_evaluate_a_model.md](doc
90.42 |
90.40 |
89.85 |
- ? |
+ 90.41 |
diff --git a/docs/en/tutorials/how_to_convert_model.md b/docs/en/tutorials/how_to_convert_model.md
index 2f13a62da..46cdefe8e 100644
--- a/docs/en/tutorials/how_to_convert_model.md
+++ b/docs/en/tutorials/how_to_convert_model.md
@@ -84,38 +84,38 @@ You can try to evaluate model, referring to [how_to_evaluate_a_model](./how_to_e
### List of supported models exportable to other backends
-The table below lists the models that are guaranteed to be exportable to other backend.
+The table below lists the models that are guaranteed to be exportable to other backends.
-| Model | codebase | OnnxRuntime | TensorRT | NCNN | PPLNN | OpenVINO | model config file(example) |
-|--------------------|------------------|:-----------:|:--------:|:----:|:-----:|:--------:|:--------------------------------------------------------------------------------------|
-| RetinaNet | MMDetection | Y | Y | Y | Y | Y | $MMDET_DIR/configs/retinanet/retinanet_r50_fpn_1x_coco.py |
-| Faster R-CNN | MMDetection | Y | Y | Y | Y | Y | $MMDET_DIR/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py |
-| YOLOv3 | MMDetection | Y | Y | Y | Y | Y | $MMDET_DIR/configs/yolo/yolov3_d53_mstrain-608_273e_coco.py |
-| YOLOX | MMDetection | Y | Y | ? | ? | Y | $MMDET_DIR/configs/yolox/yolox_tiny_8x8_300e_coco.py |
-| FCOS | MMDetection | Y | Y | Y | N | Y | $MMDET_DIR/configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco. |
-| FSAF | MMDetection | Y | Y | Y | Y | Y | $MMDET_DIR/configs/fsaf/fsaf_r50_fpn_1x_coco.py |
-| Mask R-CNN | MMDetection | Y | Y | N | Y | Y | $MMDET_DIR/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py |
-| SSD | MMDetection | Y | Y | Y | Y | Y | $MMDET_DIR/configs/ssd/ssd300_coco.py |
-| FoveaBox | MMDetection | Y | ? | ? | ? | Y | $MMDET_DIR/configs/foveabox/fovea_r50_fpn_4x4_1x_coco.py |
-| ATSS | MMDetection | Y | Y | ? | ? | Y | $MMDET_DIR/configs/atss/atss_r50_fpn_1x_coco.py |
-| Cascade R-CNN | MMDetection | Y | ? | ? | Y | Y | $MMDET_DIR/configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py |
-| Cascade Mask R-CNN | MMDetection | Y | ? | ? | Y | Y | $MMDET_DIR/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py |
-| VFNet | MMDetection | N | ? | ? | ? | Y | $MMDET_DIR/configs/vfnet/vfnet_r50_fpn_1x_coco.py |
-| ResNet | MMClassification | Y | Y | Y | Y | N | $MMCLS_DIR/configs/resnet/resnet18_b32x8_imagenet.py |
-| ResNeXt | MMClassification | Y | Y | Y | Y | N | $MMCLS_DIR/configs/resnext/resnext50_32x4d_b32x8_imagenet.py |
-| SE-ResNet | MMClassification | Y | Y | Y | Y | N | $MMCLS_DIR/configs/seresnet/seresnet50_b32x8_imagenet.py |
-| MobileNetV2 | MMClassification | Y | Y | Y | Y | N | $MMCLS_DIR/configs/mobilenet_v2/mobilenet_v2_b32x8_imagenet.py |
-| ShuffleNetV1 | MMClassification | Y | Y | Y | Y | N | $MMCLS_DIR/configs/shufflenet_v1/shufflenet_v1_1x_b64x16_linearlr_bn_nowd_imagenet.py |
-| ShuffleNetV2 | MMClassification | Y | Y | Y | Y | N | $MMCLS_DIR/configs/shufflenet_v2/shufflenet_v2_1x_b64x16_linearlr_bn_nowd_imagenet.py |
-| FCN | MMSegmentation | Y | Y | Y | Y | Y | $MMSEG_DIR/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py |
-| PSPNet | MMSegmentation | Y | Y | N | Y | Y | $MMSEG_DIR/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py |
-| DeepLabV3 | MMSegmentation | Y | Y | Y | Y | Y | $MMSEG_DIR/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py |
-| DeepLabV3+ | MMSegmentation | Y | Y | Y | Y | Y | $MMSEG_DIR/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py |
-| Fast-SCNN | MMSegmentation | Y | Y | N | Y | Y | ${MMSEG_DIR}/configs/fastscnn/fast_scnn_lr0.12_8x4_160k_cityscapes.py |
-| SRCNN | MMEditing | Y | Y | N | Y | N | $MMSEG_DIR/configs/restorers/srcnn/srcnn_x4k915_g1_1000k_div2k.py |
-| ESRGAN | MMEditing | Y | Y | N | Y | N | $MMSEG_DIR/configs/restorers/esrgan/esrgan_psnr_x4c64b23g32_g1_1000k_div2k.py |
-| DBNet | MMOCR | Y | Y | Y | Y | Y | $MMOCR_DIR/configs/textdet/dbnet/dbnet_r18_fpnc_1200e_icdar2015.py |
-| CRNN | MMOCR | Y | Y | Y | Y | N | $MMOCR_DIR/configs/textrecog/crnn/crnn_academic_dataset.py |
+| Model | codebase | OnnxRuntime | TensorRT | NCNN | PPLNN | OpenVINO | model config file(example) |
+| ------------------ | ---------------- | :---------: | :------: | :---: | :---: | :------: | :------------------------------------------------------------------------------------ |
+| RetinaNet | MMDetection | Y | Y | Y | Y | Y | $MMDET_DIR/configs/retinanet/retinanet_r50_fpn_1x_coco.py |
+| Faster R-CNN | MMDetection | Y | Y | Y | Y | Y | $MMDET_DIR/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py |
+| YOLOv3 | MMDetection | Y | Y | Y | Y | Y | $MMDET_DIR/configs/yolo/yolov3_d53_mstrain-608_273e_coco.py |
+| YOLOX | MMDetection | Y | Y | ? | ? | Y | $MMDET_DIR/configs/yolox/yolox_tiny_8x8_300e_coco.py |
+| FCOS | MMDetection | Y | Y | Y | N | Y | $MMDET_DIR/configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco. |
+| FSAF | MMDetection | Y | Y | Y | Y | Y | $MMDET_DIR/configs/fsaf/fsaf_r50_fpn_1x_coco.py |
+| Mask R-CNN | MMDetection | Y | Y | N | Y | Y | $MMDET_DIR/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py |
+| SSD | MMDetection | Y | Y | Y | Y | Y | $MMDET_DIR/configs/ssd/ssd300_coco.py |
+| FoveaBox | MMDetection | Y | ? | ? | ? | Y | $MMDET_DIR/configs/foveabox/fovea_r50_fpn_4x4_1x_coco.py |
+| ATSS | MMDetection | Y | Y | ? | ? | Y | $MMDET_DIR/configs/atss/atss_r50_fpn_1x_coco.py |
+| Cascade R-CNN | MMDetection | Y | ? | ? | Y | Y | $MMDET_DIR/configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py |
+| Cascade Mask R-CNN | MMDetection | Y | ? | ? | Y | Y | $MMDET_DIR/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py |
+| VFNet | MMDetection | N | ? | ? | ? | Y | $MMDET_DIR/configs/vfnet/vfnet_r50_fpn_1x_coco.py |
+| ResNet | MMClassification | Y | Y | Y | Y | Y | $MMCLS_DIR/configs/resnet/resnet18_b32x8_imagenet.py |
+| ResNeXt | MMClassification | Y | Y | Y | Y | Y | $MMCLS_DIR/configs/resnext/resnext50_32x4d_b32x8_imagenet.py |
+| SE-ResNet | MMClassification | Y | Y | Y | Y | Y | $MMCLS_DIR/configs/seresnet/seresnet50_b32x8_imagenet.py |
+| MobileNetV2 | MMClassification | Y | Y | Y | Y | Y | $MMCLS_DIR/configs/mobilenet_v2/mobilenet_v2_b32x8_imagenet.py |
+| ShuffleNetV1 | MMClassification | Y | Y | Y | Y | Y | $MMCLS_DIR/configs/shufflenet_v1/shufflenet_v1_1x_b64x16_linearlr_bn_nowd_imagenet.py |
+| ShuffleNetV2 | MMClassification | Y | Y | Y | Y | Y | $MMCLS_DIR/configs/shufflenet_v2/shufflenet_v2_1x_b64x16_linearlr_bn_nowd_imagenet.py |
+| FCN | MMSegmentation | Y | Y | Y | Y | Y | $MMSEG_DIR/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py |
+| PSPNet | MMSegmentation | Y | Y | N | Y | Y | $MMSEG_DIR/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py |
+| DeepLabV3 | MMSegmentation | Y | Y | Y | Y | Y | $MMSEG_DIR/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py |
+| DeepLabV3+ | MMSegmentation | Y | Y | Y | Y | Y | $MMSEG_DIR/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py |
+| Fast-SCNN | MMSegmentation | Y | Y | N | Y | Y | ${MMSEG_DIR}/configs/fastscnn/fast_scnn_lr0.12_8x4_160k_cityscapes.py |
+| SRCNN | MMEditing | Y | Y | Y | Y | Y | $MMSEG_DIR/configs/restorers/srcnn/srcnn_x4k915_g1_1000k_div2k.py |
+| ESRGAN | MMEditing | Y | Y | Y | Y | Y | $MMSEG_DIR/configs/restorers/esrgan/esrgan_psnr_x4c64b23g32_g1_1000k_div2k.py |
+| DBNet | MMOCR | Y | Y | Y | Y | Y | $MMOCR_DIR/configs/textdet/dbnet/dbnet_r18_fpnc_1200e_icdar2015.py |
+| CRNN | MMOCR | Y | Y | Y | Y | N | $MMOCR_DIR/configs/textrecog/crnn/crnn_academic_dataset.py |
### Reminders
diff --git a/mmdeploy/codebase/mmcls/deploy/classification.py b/mmdeploy/codebase/mmcls/deploy/classification.py
index a22e6f312..c3a9bbfb3 100644
--- a/mmdeploy/codebase/mmcls/deploy/classification.py
+++ b/mmdeploy/codebase/mmcls/deploy/classification.py
@@ -230,7 +230,7 @@ class Classification(BaseTask):
if metrics:
results = dataset.evaluate(outputs, metrics, metric_options)
for k, v in results.items():
- logging.info(f'\n{k} : {v:.2f}')
+ print(f'\n{k} : {v:.2f}')
else:
warnings.warn('Evaluation metrics are not specified.')
scores = np.vstack(outputs)
@@ -243,13 +243,13 @@ class Classification(BaseTask):
'pred_class': pred_class
}
if not out:
- logging.info('\nthe predicted result for the first element is '
- f'pred_score = {pred_score[0]:.2f}, '
- f'pred_label = {pred_label[0]} '
- f'and pred_class = {pred_class[0]}. '
- 'Specify --out to save all results to files.')
+ print('\nthe predicted result for the first element is '
+ f'pred_score = {pred_score[0]:.2f}, '
+ f'pred_label = {pred_label[0]} '
+ f'and pred_class = {pred_class[0]}. '
+ 'Specify --out to save all results to files.')
if out:
- logging.info(f'\nwriting results to {out}')
+ print(f'\nwriting results to {out}')
mmcv.dump(results, out)
def get_preprocess(self) -> Dict: