Hi, I use the setup described in the script reproduce_paper_resuls.sh to reproduce paper's results, but the model I get has the following number of parameters:
| Name | Type | Params
0 | layers | ModuleList | 81.6 K
1 | output_layer | BRepNetFaceOutputLayer | 98.9 K
2 | classification_layer | Linear | 680
181 K Trainable params
0 Non-trainable params
181 K Total params
0.725 Total estimated model params size (MB)
And the following results:
DATALOADER:0 TEST RESULTS
{'test/Chamfer_iou': 0.8299525380134583,
'test/CutEnd_iou': 0.7150671482086182,
'test/CutSide_iou': 0.7787927389144897,
'test/ExtrudeEnd_iou': 0.8739719986915588,
'test/ExtrudeSide_iou': 0.9213229417800903,
'test/Fillet_iou': 0.978989839553833,
'test/RevolveEnd_iou': 0.5921052694320679,
'test/RevolveSide_iou': 0.7775700688362122,
'test/accuracy': 0.9383547306060791,
'test/mean_iou': 0.8084715604782104}
This is inconsistent with the results published in the paper, where the best performing model has 359k parameters and accuracy 92.52 ± 0.15 and IoU 77.10 ± 0.54. Can you tell me what I do wrong ?
Hi, I use the setup described in the script reproduce_paper_resuls.sh to reproduce paper's results, but the model I get has the following number of parameters:
| Name | Type | Params
0 | layers | ModuleList | 81.6 K
1 | output_layer | BRepNetFaceOutputLayer | 98.9 K
2 | classification_layer | Linear | 680
181 K Trainable params
0 Non-trainable params
181 K Total params
0.725 Total estimated model params size (MB)
And the following results:
DATALOADER:0 TEST RESULTS
{'test/Chamfer_iou': 0.8299525380134583,
'test/CutEnd_iou': 0.7150671482086182,
'test/CutSide_iou': 0.7787927389144897,
'test/ExtrudeEnd_iou': 0.8739719986915588,
'test/ExtrudeSide_iou': 0.9213229417800903,
'test/Fillet_iou': 0.978989839553833,
'test/RevolveEnd_iou': 0.5921052694320679,
'test/RevolveSide_iou': 0.7775700688362122,
'test/accuracy': 0.9383547306060791,
'test/mean_iou': 0.8084715604782104}
This is inconsistent with the results published in the paper, where the best performing model has 359k parameters and accuracy 92.52 ± 0.15 and IoU 77.10 ± 0.54. Can you tell me what I do wrong ?