Comments (7)
Since our method is designed for zero-shot applications, you can attempt testing it on your dataset by simply changing the text prompt. However, due to the significant disparity between medical tasks and industrial anomaly detection, direct testing may not yield satisfactory results. Therefore, you can also consider retraining our method by generating synthetic anomalies (e.g. DRAEM) to better align with your specific application.
The above is just my suggestion. Since I'm not specialized in medical tasks, my ideas may not be entirely suitable. Please take them as a reference. :)
from vand-april-gan.
Can you please provide more information about the new dataset (if possible)? Is it similar to datasets like MVTec-AD and VisA, or more like ImageNet and CIFAR-10? I might need more information to assess this.
from vand-april-gan.
This is a medical dataset (images of brain lesions) that has been used for anomaly detection tasks before, but without the information on masks for the abnormal regions.
from vand-april-gan.
The training process is only normal images, testing is normal and abnormal images
from vand-april-gan.
Thank you so much for your patient explanation and response. I have one more small request: could you please share the manual download link for the CLIP model ( ViT-L-14-336)?
from vand-april-gan.
Sure! You can find all the links you need here.
from vand-april-gan.
Thanks so much.
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Related Issues (20)
- Issues Recreating Model HOT 2
- -
- Calculation False Positive Rate
- Guidance on Threshold Setting for Accurate Defect Detection in Heatmap Visualizations (red mark) HOT 1
- Can we test without loading pre-trained weights? HOT 4
- Is there a way to get the score of how anomalous an image is? HOT 2
- is that possible to convert and using onnx file? HOT 1
- mvtec epoch HOT 1
- What type of GPU are you using and how long does it take HOT 2
- About text_probs. HOT 1
- 关于训练时梯度的问题 HOT 4
- initialized by other weight HOT 2
- 除了添加的线性层 clip其它部分的权重有被微调吗 HOT 2
- 关于train.py中的的Dataset问题 HOT 1
- global image representations HOT 4
- 检测结果 HOT 1
- few-shot的异常分类分数
- Show visualize heatmap
- The issue has been resolved.
- Question about License Information
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