Rename to pointnet2.scanobjectnn-hardest.openpoints

README.md

@@ -11,12 +11,12 @@ tags:
 datasets:
 - scanobjectnn
 model-index:
-- name: pointnet2.scanobjectnn.openpoints
+- name: pointnet2.scanobjectnn-hardest.openpoints
   results:
   - task:
       type: point-cloud-classification
     dataset:
-      name: ScanObjectNN
+      name: ScanObjectNN (PB_T50_RS)
       type: scanobjectnn
     metrics:
     - name: OA
@@ -27,9 +27,9 @@ model-index:
       value: 84.36
 ---
 
-# Model card for pointnet2.scanobjectnn.openpoints
+# Model card for pointnet2.scanobjectnn-hardest.openpoints
 
-A PointNet++ point cloud classification model (hierarchical set abstraction). Trained on ScanObjectNN.
+A PointNet++ point cloud classification model (hierarchical set abstraction). Trained on ScanObjectNN (PB_T50_RS).
 
 ## Model Details
 
@@ -39,7 +39,7 @@ A PointNet++ point cloud classification model (hierarchical set abstraction). Tr
   - Input channels: 4
   - Classes: 15
   - Features: 1024
-- **Dataset:** ScanObjectNN
+- **Dataset:** ScanObjectNN (PB_T50_RS)
 - **Metrics:** OA 86.16, mAcc 84.36 (reference 86.2)
 - **Paper:** [PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space](https://arxiv.org/abs/1706.02413)
 - **Converted from:** [guochengqian/PointNeXt](https://github.com/guochengqian/PointNeXt) (MIT)
@@ -59,7 +59,7 @@ import torch_pointcloud as tp
 from torch_pointcloud.utils.data import collate
 
 model, info = tp.create_model(
-    "pointnet2.scanobjectnn.openpoints",
+    "pointnet2.scanobjectnn-hardest.openpoints",
     task="classification",
     pretrained=True,
     return_info=True,