add bevformer benchmark and fix classification predict bug (#240)

docs/source/model_zoo_det3d.md

@@ -7,3 +7,4 @@ Pretrained on [nuScenes](https://www.nuscenes.org/) dataset.
 | Algorithm  | Config                                                       | Params<br/>                      | Train memory<br/>(GB) | NDS | mAP | Download                                                     |
 | ---------- | ------------------------------------------------------------ | ------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
 | BEVFormer-base | [bevformer_base_r101_dcn_nuscenes](https://github.com/alibaba/EasyCV/tree/master/configs/detection3d/bevformer/bevformer_base_r101_dcn_nuscenes.py) | 69M         | 23.9 | 52.46              | 41.83 | [model](http://pai-vision-data-hz.oss-accelerate.aliyuncs.com/EasyCV/modelzoo/detection3d/bevformer/epoch_24.pth) |
+| BEVFormer-base-hybrid | [bevformer_base_r101_dcn_nuscenes_hybrid](https://github.com/alibaba/EasyCV/blob/master/configs/detection3d/bevformer/bevformer_base_r101_dcn_nuscenes_hybrid.py) | 69M         | 46.1 | 53.02              | 42.48 | [model](http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/EasyCV/modelzoo/detection3d/bevformer_base_hybrid2/epoch_23.pth) |

easycv/models/detection3d/detectors/bevformer/attentions/multi_scale_deformable_attention.py

@@ -11,8 +11,6 @@ from mmcv.cnn import constant_init, xavier_init
 from mmcv.runner.base_module import BaseModule
 
 from easycv.models.registry import ATTENTION
-from easycv.thirdparty.deformable_attention.functions import \
-    MSDeformAttnFunction
 
 
 @ATTENTION.register_module()
@@ -99,6 +97,7 @@ class CustomMSDeformableAttention(BaseModule):
         if self.adapt_jit:
             self.ms_deform_attn_op = torch.ops.custom.ms_deform_attn
         else:
+            from easycv.thirdparty.deformable_attention.functions import MSDeformAttnFunction
             self.ms_deform_attn_op = MSDeformAttnFunction.apply
 
     def init_weights(self):

easycv/predictors/classifier.py

@@ -35,10 +35,10 @@ class ClassificationPredictor(PredictorV2):
                  device=None,
                  save_results=False,
                  save_path=None,
-                 pipelines=[],
+                 pipelines=None,
                  topk=1,
                  pil_input=True,
-                 label_map_path=[],
+                 label_map_path=None,
                  *args,
                  **kwargs):
         super(ClassificationPredictor, self).__init__(
@@ -59,7 +59,12 @@ class ClassificationPredictor(PredictorV2):
             self.INPUT_IMAGE_MODE = 'RGB'
 
         if label_map_path is None:
-            class_list = self.cfg.get('CLASSES', [])
+            if 'CLASSES' in self.cfg:
+                class_list = self.cfg.get('CLASSES', [])
+            elif 'class_list' in self.cfg:
+                class_list = self.cfg.get('class_list', [])
+            else:
+                class_list = []
         else:
             with io.open(label_map_path, 'r') as f:
                 class_list = f.readlines()
@@ -85,7 +90,9 @@ class ClassificationPredictor(PredictorV2):
                     img = img.convert(self.INPUT_IMAGE_MODE.upper())
                 results['filename'] = input
             else:
-                assert isinstance(input, ImageFile.ImageFile)
+                if isinstance(input, np.ndarray):
+                    input = Image.fromarray(input)
+                # assert isinstance(input, ImageFile.ImageFile)
                 img = input
                 results['filename'] = None
             results['img'] = img