fix inference folder error

README.md

@@ -27,11 +27,7 @@ An example result from inference is shown below:
 **This is a demonstration network meant to just show the training process for this sort of network with MONAI. To achieve better performance, users need to use larger dataset like [BraTS 2021](https://www.synapse.org/#!Synapse:syn25829067/wiki/610865).**
 
 ## MONAI Generative Model Dependencies
-[MONAI generative models](https://github.com/Project-MONAI/GenerativeModels) can be installed by
-```
-pip install lpips==0.1.4
-pip install git+https://github.com/Project-MONAI/[email protected]
-```
+This bundle requires to install [MONAI generative models](https://github.com/Project-MONAI/GenerativeModels).
 
 ## Data
 The training data is BraTS 2016 and 2017 from the Medical Segmentation Decathalon. Users can find more details on the dataset (`Task01_BrainTumour`) at http://medicaldecathlon.com/.

configs/inference.json

@@ -103,6 +103,7 @@
     "generated_image_np": "$@generated_image[0,0].cpu().numpy().transpose(1, 0)[::-1, ::-1]",
     "img_pil": "$Image.fromarray(visualize_2d_image(@generated_image_np), 'RGB')",
     "run": [
+        "$@create_output_dir",
         "$@img_pil.save(@output_dir+'/synimg_'+@output_postfix+'.png')"
     ]
 }

configs/inference_autoencoder.json

@@ -8,7 +8,7 @@
     ],
     "bundle_root": ".",
     "model_dir": "$@bundle_root + '/models'",
-    "dataset_dir": "@bundle_root",
+    "dataset_dir": "/workspace/data/medical",
     "output_dir": "$@bundle_root + '/output'",
     "create_output_dir": "$Path(@output_dir).mkdir(exist_ok=True)",
     "device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",

configs/metadata.json

@@ -1,10 +1,11 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_generator_ldm_20230507.json",
-    "version": "1.0.0",
+    "version": "1.0.1",
     "changelog": {
+        "1.0.1": "fix inference folder error",
         "1.0.0": "Initial release"
     },
-    "monai_version": "1.2.0rc5",
+    "monai_version": "1.2.0rc7",
     "pytorch_version": "1.13.1",
     "numpy_version": "1.22.2",
     "optional_packages_version": {

configs/train_autoencoder.json

@@ -8,7 +8,7 @@
     "device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",
     "ckpt_dir": "$@bundle_root + '/models'",
     "tf_dir": "$@bundle_root + '/eval'",
-    "dataset_dir": "@bundle_root",
+    "dataset_dir": "/workspace/data/medical",
     "pretrained": false,
     "perceptual_loss_model_weights_path": null,
     "train_batch_size_img": 1,

configs/train_diffusion.json

@@ -108,7 +108,7 @@
             "section": "training",
             "cache_rate": 1.0,
             "num_workers": 8,
-            "download": "@download_brats",
+            "download": false,
             "transform": "@train#preprocessing"
         },
         "dataloader": {

docs/README.md

@@ -20,11 +20,7 @@ An example result from inference is shown below:
 **This is a demonstration network meant to just show the training process for this sort of network with MONAI. To achieve better performance, users need to use larger dataset like [BraTS 2021](https://www.synapse.org/#!Synapse:syn25829067/wiki/610865).**
 
 ## MONAI Generative Model Dependencies
-[MONAI generative models](https://github.com/Project-MONAI/GenerativeModels) can be installed by
-```
-pip install lpips==0.1.4
-pip install git+https://github.com/Project-MONAI/[email protected]
-```
+This bundle requires to install [MONAI generative models](https://github.com/Project-MONAI/GenerativeModels).
 
 ## Data
 The training data is BraTS 2016 and 2017 from the Medical Segmentation Decathalon. Users can find more details on the dataset (`Task01_BrainTumour`) at http://medicaldecathlon.com/.