Fix: ActivationMapHook process backbone instead of neck output (#2145)

* ActivationMapHook process backbone instead of neck output

* timm version fix

Author: Evgeny Tsykunov

otx/algorithms/detection/adapters/mmdet/models/detectors/custom_maskrcnn_detector.py

@@ -99,14 +99,16 @@ def load_state_dict_pre_hook(model, model_classes, chkpt_classes, chkpt_dict, pr
     def custom_mask_rcnn__simple_test(ctx, self, img, img_metas, proposals=None, **kwargs):
         """Function for custom_mask_rcnn__simple_test."""
         assert self.with_bbox, "Bbox head must be implemented."
-        x = self.extract_feat(img)
+        x = backbone_out = self.backbone(img)
+        if self.with_neck:
+            x = self.neck(x)
         if proposals is None:
             proposals, _ = self.rpn_head.simple_test_rpn(x, img_metas)
         out = self.roi_head.simple_test(x, proposals, img_metas, rescale=False)
 
         if ctx.cfg["dump_features"]:
             feature_vector = FeatureVectorHook.func(x)
-            saliency_map = ActivationMapHook.func(x[-1])
+            saliency_map = ActivationMapHook.func(backbone_out)
             return (*out, feature_vector, saliency_map)
 
         return out

otx/algorithms/detection/adapters/mmdet/models/detectors/custom_maskrcnn_tile_optimized.py

@@ -309,14 +309,16 @@ def custom_mask_rcnn__simple_test(ctx, self, img, img_metas, proposals=None):
         assert self.with_bbox, "Bbox head must be implemented."
         tile_prob = self.tile_classifier.simple_test(img)
 
-        x = self.extract_feat(img)
+        x = backbone_out = self.backbone(img)
+        if self.with_neck:
+            x = self.neck(x)
         if proposals is None:
             proposals, _ = self.rpn_head.simple_test_rpn(x, img_metas)
         out = self.roi_head.simple_test(x, proposals, img_metas, rescale=False)
 
         if ctx.cfg["dump_features"]:
             feature_vector = FeatureVectorHook.func(x)
-            saliency_map = ActivationMapHook.func(x[-1])
+            saliency_map = ActivationMapHook.func(backbone_out)
             return (*out, tile_prob, feature_vector, saliency_map)
 
         return (*out, tile_prob)

requirements/classification.txt

@@ -2,6 +2,6 @@
 # Classification Requirements.
 mmcv-full==1.7.0
 mmcls==0.25.0
-timm
+timm==0.6.12
 mmdeploy==0.14.0
 pytorchcv

requirements/detection.txt

@@ -4,6 +4,6 @@ mmcv-full==1.7.0
 mmdet==2.28.1
 pytorchcv
 mmcls==0.25.0
-timm
+timm==0.6.12
 mmdeploy==0.14.0
 scikit-image

requirements/segmentation.txt

@@ -4,5 +4,5 @@ mmcv-full==1.7.0
 mmsegmentation==0.30.0
 scikit-image
 mmdeploy==0.14.0
-timm
+timm==0.6.12
 pytorchcv