Open samahwaleed opened 1 year ago
@samahwaleed
ResNet101 model is not yet added. Will add that for sure if that is a requirement.
Regarding precision and recall. You can check precision and recall, you can visualize class-wise precision and recall using the eval.py
script.
I would be grateful if you could add ResNet101 as soon as possible as I need it for research purpose.
Regarding precision and recall. You can check precision and recall, you can visualize class-wise precision and recall using the eval.py script.
Could you please explain more how to do it as I need these values for each class!?
Thank you for your time and consideration.
Sure, I would add the model by tomorrow.
After training the model, use the eval.py
script to check the metrics. Example command:
python eval.py --weights outputs/training/custom_training/best_model.pth --config data_configs/custom_data.yaml --model fasterrcnn_resnet50_fpn_v2 --verbose
Thank you so much Sir,
python eval.py --weights outputs/training/custom_training/best_model.pth --config data_configs/custom_data.yaml --model fasterrcnn_resnet50_fpn_v2 --verbose
I have tried this and I only got the AP. How I can get the Recall for each class and F1 score?
Right now, the library uses Torchmetrics to show class-wise mAP. I will try to add classwise recall and precision. But it may take some time.
It shows the average precision for each class but not recall, I just need the recall and F1 score.
Thank you so much.
I can add recall per class but not sure about the F1 score. Before that, I will add the ResNet101 model.
@samahwaleed I have added the ResNet101 model.
Thank you Sir.
I would be thankful if you add the recall at the earliest possible time.
1) I want to use resnet-101 model but I can't find it in the models folder. Could you please help me!?
2) How I can find the precision and recall for each object?
Thank you