Open luxunxiansheng opened 10 months ago
@tangy would be able to help here? Thanks!
Hi @luxunxiansheng , the MONAI plugin does not provide any label editing functions. The annotation funcs are within OHIF. The tutorial used OHIF V2 . The brushes and erases should show as screenshot. The reason could be the OHIF compile. Did you observe any errors when build the OHIF or start OHIF?
Hi @luxunxiansheng , the MONAI plugin does not provide any label editing functions. The annotation funcs are within OHIF. The tutorial used OHIF V2 . The brushes and erases should show as screenshot. The reason could be the OHIF compile. Did you observe any errors when build the OHIF or start OHIF?
here is the screenshot:
there seem no errors when I start OHIF.
This looks strange to me (As OHIFV2 compile problem). And there is no "segmentation" dropdown panel when you hit the "+" on the top right? If so, I will give a try and investigate more, then update all necessary docs.
This looks strange to me (As OHIFV2 compile problem). And there is no "segmentation" dropdown panel when you hit the "+" on the top right? If so, I will give a try and investigate more, then update all necessary docs.
Hi @luxunxiansheng,
It seems you installed the latest MONAI Label version (0.8.1) which uses the latest OHIF version (V3).
The tutorial monailabel_radiology_spleen_segmentation_OHIF.ipynb uses a previous version of MONAI Label.
This has to be updated in the tutorial documentation.
For now, I'd suggest you install a previous version of MONAI Label that uses OHIFV2. i.e. pip install monailabel==0.7.0
Let us know,
OK. I will install 0.7.
I follow the tutorial monailabel_radiology_spleen_segmentation_OHIF.ipynb and can start the app. When I want to edit the inference labels as shown below:
I can not find the "segmentation" tool buttons and no upleft pannel either.
The info looks like this:
{ "name": "MONAILabel - Radiology (0.8.1)", "description": "DeepLearning models for radiology", "version": "0.8.1", "labels": [ "spleen" ], "models": { "segmentation_spleen": { "type": "segmentation", "labels": { "spleen": 1 }, "dimension": 3, "description": "A pre-trained model for volumetric (3D) segmentation of the spleen from CT image", "config": { "device": [ "NVIDIA GeForce RTX 3090:0", "NVIDIA GeForce RTX 3090:1", "NVIDIA GeForce RTX 3090:2", "NVIDIA GeForce RTX 3090:3" ] } }, "Histogram+GraphCut": { "type": "scribbles", "labels": { "spleen": 1 }, "dimension": 3, "description": "A post processing step with histogram-based GraphCut for Generic segmentation", "config": { "num_bins": 64, "lamda": 1, "sigma": 0.1, "device": [ "NVIDIA GeForce RTX 3090:0", "NVIDIA GeForce RTX 3090:1", "NVIDIA GeForce RTX 3090:2", "NVIDIA GeForce RTX 3090:3" ] } }, "GMM+GraphCut": { "type": "scribbles", "labels": { "spleen": 1 }, "dimension": 3, "description": "A post processing step with GMM-based GraphCut for Generic segmentation", "config": { "num_mixtures": 20, "lamda": 5, "sigma": 0.5, "device": [ "NVIDIA GeForce RTX 3090:0", "NVIDIA GeForce RTX 3090:1", "NVIDIA GeForce RTX 3090:2", "NVIDIA GeForce RTX 3090:3" ] } } }, "trainers": { "segmentation_spleen": { "description": "Train Spleen Segmentation Model", "config": { "name": "train_01", "pretrained": true, "device": [ "NVIDIA GeForce RTX 3090:0", "NVIDIA GeForce RTX 3090:1", "NVIDIA GeForce RTX 3090:2", "NVIDIA GeForce RTX 3090:3" ], "max_epochs": 50, "early_stop_patience": -1, "val_split": 0.2, "train_batch_size": 1, "val_batch_size": 1, "multi_gpu": true, "gpus": "all", "dataset": [ "SmartCacheDataset", "CacheDataset", "PersistentDataset", "Dataset" ], "dataloader": [ "ThreadDataLoader", "DataLoader" ], "tracking": [ "mlflow", "None" ], "tracking_uri": "", "tracking_experiment_name": "" }, "labels": { "spleen": 1 } } }, "strategies": { "random": { "description": "Random Strategy" }, "first": { "description": "Get First Sample" }, "last": { "description": "Get Last Sample" } }, "scoring": {}, "train_stats": { "segmentation_spleen": {} }, "datastore": { "total": 1, "completed": 0, "label_tags": {} } }