diffusion-anomaly
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JuliaWolleb
Anomaly detection with diffusion models
creating data loader... dataset is chexpert creating optimizer... training classifier model... step 0 classnames ['diseased', 'healthy', 'diseased', 'diseased', 'diseased', 'healthy', 'healthy', 'healthy'] len 8 len 8 len 8 lenloader 8...
I believe I have successfully trained embeddings by following the steps for the classifier and the model itself. I made a shell script to do the inferencing: ``` MODEL_FLAGS="--image_size 256...
Hey! I just found, that you are missing a ')' in your code in the unet.py line 901 h = self.middle_block(h, emb **MISSING )** if self.pool.startswith("spatial"): results.append(h.type(x.dtype).mean(dim=(2, 3))) h =...
Hi, thanks for your great job I have some questions after training and testing on the brats dataset 1. Did you normalize the seg part(data/brats/training/000001/brats_train_001_seg_080_w.nii.gz) during preprocessing? I see that...
While using the command below for translation, error occurs. ---------------------------------- python scripts/classifier_sample_known.py --data_dir path_to_testdata --model_path ./results/model.pt --classifier_path ./results/classifier.pt --dataset brats_or_chexpert --classifier_scale 100 --noise_level 500 $MODEL_FLAGS $DIFFUSION_FLAGS $CLASSIFIER_FLAGS $SAMPLE_FLAGS -------------------------------- Traceback...
hello! I am interested in modifying your paper to a resolution of 1024 and have encountered an error related to channel size when training at this resolution. Could you kindly...
I found the error "No rendezvous handler for env://" when I train "classifier_train.py." Do you have any suggestions? File "C:\Users\K.Nuttapol\PycharmProjects\diffusion-anomaly\scripts\classifier_train.py", line 288, in main() File "C:\Users\K.Nuttapol\PycharmProjects\diffusion-anomaly\scripts\classifier_train.py", line 45, in main...
I've encountered this error with "RuntimeError: a leaf Variable that requires grad is being used in an in-place operation." in dist_util.py, where ` with th.no_grad(): dist.broadcast(p, 0)` My enviroment is...
Congratulation for your great work! Could you kindly share the preprocessed datasets or preprocessing scripts?
