Comments (8)
WuJunde
commented on August 28, 2024
1
According to the instruction of readme.md, I have trained and obtained best_checkpoint. May I ask how to call checkpoint for subsequent segmentation tasks?
Evaluation: The code can automatically evaluate the model on the test set during traing, set "--val_freq" to control how many epoches you want to evaluate once. You can also run val.py for the independent evaluation.
Result Visualization: You can set "--vis" parameter to control how many epoches you want to see the results in the training or evaluation process.
In default, everything will be saved at ./logs/
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Part-Work
commented on August 28, 2024
1
How can I evaluate 'OpticDisc_Fundus_SAM_1024.pth' and 'sam_vit_b_01ec64.pth' on 'REFUGE' dataset??
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Issues-translate-bot
commented on August 28, 2024
1
Bot detected the issue body's language is not English, translate it automatically. 👯👭🏻🧑🤝🧑👫🧑🏿🤝🧑🏻👩🏾🤝👨🏿👬🏿
How can I evaluate 'OpticDisc_Fundus_SAM_1024.pth' and 'sam_vit_b_01ec64.pth' on 'REFUGE' dataset??
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FJGEODEV
commented on August 28, 2024
+1, I was trying to use val.py, but no luck. May need author's help.
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WuJunde
commented on August 28, 2024
- you cannot evaluate the prediction accuracy without target masks (to my understanding, Ground-Truth). 2. SAM is an interactive model, so it is a common assumption that the user would provide a prompt for each image (like a click on the target object or sth). In the code, we generate this prompt from target mask instead to simulate the user-given prompt. If you have neither user-given prompt nor target-mask-generated prompt, you may want to try the "segment everything" setting described in SAM paper. It is basically click-prompted the original image in grid, and pick the top-k high-confidence predicted objects of the model. For using it, you need to train the adapters under this setting.
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janexue001
commented on August 28, 2024
According to the instruction of readme.md, I have trained and obtained best_checkpoint. May I ask how to call checkpoint for subsequent segmentation tasks?
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janexue001
commented on August 28, 2024
According to the instruction of readme.md, I have trained and obtained best_checkpoint. May I ask how to call checkpoint for subsequent segmentation tasks?
Evaluation: The code can automatically evaluate the model on the test set during traing, set "--val_freq" to control how many epoches you want to evaluate once. You can also run val.py for the independent evaluation.
Result Visualization: You can set "--vis" parameter to control how many epoches you want to see the results in the training or evaluation process.
In default, everything will be saved at ./logs/
Thank you for your reply. The details of the training process can indeed be seen in logs. However, besides that, I want to see the visual segmentation results performed with the trained model.
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janexue001
commented on August 28, 2024
Thank you very much for your reply. It is true that the detailed records of the model training process can be found in logs. However, in addition, I also want to see the visual segmentation results.
In addition, I would like to ask you one more question.
I tried multi-class segmentation by setting the "-multimask_output" in the cfg.py file to 2, which worked successfully with the sam model, but the "ValueError: Target size (torch.Size([16, 2, 256, 256])) must be the same as input size (torch.Size([16, 1, 256, 256]))" problem appeared with efficient_sam.
All the best to you
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主题: Re: [KidsWithTokens/Medical-SAM-Adapter] How to use the code for Inference? (Issue #74)
According to the instruction of readme.md, I have trained and obtained best_checkpoint. May I ask how to call checkpoint for subsequent segmentation tasks?
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Related Issues (20)
- Discord link not valid HOT 2
- multiple classification tasks HOT 3
- export onnx HOT 1
- 请问这个将来计划提供类似SAM提供的APP使用Demo程序吗 HOT 3
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