First, thank you for open code engineering. But there is a big gap between my final result and your result.Evaluation results of your model (coco_homo) : accuracy(80.87), recall(96.22). I used your model (models/weights/superglue_cocohomo.pt) to get the final result : acc(81.43),recall(96.25).The results are very good.But I got the final result（acc : 76.70 recall : 89.20）when I trained the superglue with your superpoint model(models/weights/superpoint_v1.pth).This is a lot worse than your results.
I used the coco(2017) dataset and the other parameters have not changed , but I used DDP to train. Why is there a discrepancy in the evaluation results? I look forward to your response.
Leon-xc
commented
1 year ago
First, thank you for open code engineering. But there is a big gap between my final result and your result.Evaluation results of your model (coco_homo) : accuracy(80.87), recall(96.22). I used your model (models/weights/superglue_cocohomo.pt) to get the final result : acc(81.43),recall(96.25).The results are very good.But I got the final result（acc : 76.70 recall : 89.20）when I trained the superglue with your superpoint model(models/weights/superpoint_v1.pth).This is a lot worse than your results.
I used the coco(2017) dataset and the other parameters have not changed , but I used DDP to train. Why is there a discrepancy in the evaluation results? I look forward to your response.