Comments (3)
Hello, the normal samples are randomly selected from the training set of the target dataset. Hence, you can just use the whole test set and do not need a data split. Please refer to the content in Sec 4.1 of my paper. Thank you.
from inctrl.
Thanks for your reply!
However, I find that several datasets do not provide standard training and testing sets, requiring users to split them themselves.
For example, the original headCT dataset consists of 100 normal slices and 100 abnormal slices, but in Table 5, your article uses the headCT dataset with 25 normal and 100 abnormal slices in the test set. The original SDD dataset contains 347 normal and 52 abnormal slices, but in the test set you used 286 normal and 54 abnormal slices.
from inctrl.
You should use the convert scripts to convert the datasets to MVTec AD format. Please follow the guidance in README.
from inctrl.
Related Issues (16)
- the step 2 google drive
- After I use the convert_visa.py to convert Visa, I found that I can't generate the json file through the gen_train_json.py, could you have a check at the convert_visa.py? thanks a lot HOT 4
- reproduce the code
- from binary_focal_loss import BinaryFocalLoss, No module HOT 1
- lower performance for Visa dataset validation HOT 11
- Can you provide the download address for vit'b_16_plus_240 laion400m_e32-699c4b84.pt HOT 2
- How is x.pt file generated with the extension python test.py --few_shot_dir HOT 1
- Can you provide code for visual inspection HOT 3
- Guidance on Training and Testing with Custom Dataset Similar to MVTec Format
- could you share how to visualize the segment result when inference? HOT 1
- Hi, you can use **_torch.save()_** to generate .pt file for your own few-shot samples. HOT 2
- The performance of using 4-shot or 8-shot on the Visa dataset is similar to that of 2-shot HOT 2
- the training process HOT 1
- lower performance on 2-shot visa-candle with the default setting (e.g., pre-trained model and few-shot prompts)
- Is the model trained on the full dataset of MVTec available?
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from inctrl.