Merge branch 'dev' of github.com:heyufan1995/model-zoo into dev

ci/unit_tests/test_vista3d.py

@@ -313,7 +313,6 @@ def test_eval_config(self, override):
             os.path.join(bundle_root, "configs/train.json"),
             os.path.join(bundle_root, "configs/train_continual.json"),
             os.path.join(bundle_root, "configs/evaluate.json"),
-            os.path.join(bundle_root, "configs/data.yaml"),
         ]
         trainer = ConfigWorkflow(
             workflow_type="train",

ci/unit_tests/test_vista3d_dist.py

@@ -121,7 +121,6 @@ def test_eval_mgpu_config(self, override):
             os.path.join(bundle_root, "configs/train_continual.json"),
             os.path.join(bundle_root, "configs/evaluate.json"),
             os.path.join(bundle_root, "configs/mgpu_evaluate.json"),
-            os.path.join(bundle_root, "configs/data.yaml"),
         ]
         output_path = os.path.join(bundle_root, "configs/evaluate_override.json")
         n_gpu = torch.cuda.device_count()

models/brats_mri_axial_slices_generative_diffusion/configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
-    "version": "1.1.1",
+    "version": "1.1.2",
     "changelog": {
+        "1.1.2": "update issue for IgniteInfo",
         "1.1.1": "enable tensorrt",
         "1.1.0": "update to use monai 1.4, model ckpt not changed, rm GenerativeAI repo",
         "1.0.9": "update to use monai 1.3.1",

models/brats_mri_axial_slices_generative_diffusion/scripts/ldm_trainer.py

@@ -14,11 +14,10 @@
 from typing import TYPE_CHECKING, Any, Callable, Iterable, Sequence
 
 import torch
-from monai.config import IgniteInfo
 from monai.engines.utils import IterationEvents, default_metric_cmp_fn, default_prepare_batch
 from monai.inferers import Inferer, SimpleInferer
 from monai.transforms import Transform
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 from monai.utils.enums import CommonKeys, GanKeys
 from torch.optim.optimizer import Optimizer
 from torch.utils.data import DataLoader

models/brats_mri_generative_diffusion/configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
-    "version": "1.1.1",
+    "version": "1.1.2",
     "changelog": {
+        "1.1.2": "update issue for IgniteInfo",
         "1.1.1": "enable tensorrt",
         "1.1.0": "update to use monai 1.4, model ckpt not changed, rm GenerativeAI repo",
         "1.0.9": "update to use monai 1.3.1",

models/brats_mri_generative_diffusion/scripts/ldm_trainer.py

@@ -14,11 +14,10 @@
 from typing import TYPE_CHECKING, Any, Callable, Iterable, Sequence
 
 import torch
-from monai.config import IgniteInfo
 from monai.engines.utils import IterationEvents, default_metric_cmp_fn, default_prepare_batch
 from monai.inferers import Inferer, SimpleInferer
 from monai.transforms import Transform
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 from monai.utils.enums import CommonKeys, GanKeys
 from torch.optim.optimizer import Optimizer
 from torch.utils.data import DataLoader

models/lung_nodule_ct_detection/configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
-    "version": "0.6.7",
+    "version": "0.6.8",
     "changelog": {
+        "0.6.8": "update issue for IgniteInfo",
         "0.6.7": "use monai 1.4 and update large files",
         "0.6.6": "update to use monai 1.3.1",
         "0.6.5": "remove notes for trt_export in readme",

models/lung_nodule_ct_detection/scripts/detection_saver.py

@@ -14,9 +14,8 @@
 import warnings
 from typing import TYPE_CHECKING, Callable, Optional
 
-from monai.config import IgniteInfo
 from monai.handlers.classification_saver import ClassificationSaver
-from monai.utils import evenly_divisible_all_gather, min_version, optional_import, string_list_all_gather
+from monai.utils import IgniteInfo, evenly_divisible_all_gather, min_version, optional_import, string_list_all_gather
 
 from .utils import detach_to_numpy
 

models/lung_nodule_ct_detection/scripts/evaluator.py

@@ -15,11 +15,10 @@
 
 import torch
 from monai.apps.detection.networks.retinanet_detector import RetinaNetDetector
-from monai.config import IgniteInfo
 from monai.engines.evaluator import SupervisedEvaluator
 from monai.engines.utils import IterationEvents, default_metric_cmp_fn
 from monai.transforms import Transform
-from monai.utils import ForwardMode, min_version, optional_import
+from monai.utils import ForwardMode, IgniteInfo, min_version, optional_import
 from monai.utils.enums import CommonKeys as Keys
 from torch.utils.data import DataLoader
 

models/lung_nodule_ct_detection/scripts/trainer.py

@@ -14,12 +14,11 @@
 from typing import TYPE_CHECKING, Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
 
 import torch
-from monai.config import IgniteInfo
 from monai.engines.trainer import Trainer
 from monai.engines.utils import IterationEvents, default_metric_cmp_fn
 from monai.inferers import Inferer
 from monai.transforms import Transform
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 from monai.utils.enums import CommonKeys as Keys
 from torch.optim.optimizer import Optimizer
 from torch.utils.data import DataLoader

models/maisi_ct_generative/configs/metadata.json

@@ -1,7 +1,9 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_generator_ldm_20240318.json",
-    "version": "0.4.3",
+    "version": "0.4.5",
     "changelog": {
+        "0.4.5": "update README",
+        "0.4.4": "update issue for IgniteInfo",
         "0.4.3": "remove download large files, add weights_only when loading weights and add label_dict to large files",
         "0.4.2": "update train.json to fix finetune ckpt bug",
         "0.4.1": "update large files",

models/maisi_ct_generative/docs/README.md

@@ -22,6 +22,30 @@ The inference requires:
 - GPU: at least 58GB GPU memory for 512 x 512 x 512
 - Disk Memory: at least 21GB disk memory
 
+#### Inference parameters:
+The information for the inference input, like body region and anatomy to generate, is stored in [./configs/inference.json](../configs/inference.json). Please feel free to play with it. Here are the details of the parameters.
+
+- `"num_output_samples"`: int, the number of output image/mask pairs it will generate.
+- `"spacing"`: voxel size of generated images. E.g., if set to `[1.5, 1.5, 2.0]`, it will generate images with a resolution of 1.5×1.5×2.0 mm. The spacing for x and y axes has to be between 0.5 and 3.0 mm and the spacing for the z axis has to be between 0.5 and 5.0 mm.
+- `"output_size"`: volume size of generated images. E.g., if set to `[512, 512, 256]`, it will generate images with size of 512×512×256. They need to be divisible by 16. If you have a small GPU memory size, you should adjust it to small numbers. Note that `"spacing"` and `"output_size"` together decide the output field of view (FOV). For eample, if set them to `[1.5, 1.5, 2.0]`mm and `[512, 512, 256]`, the FOV is 768×768×512 mm. We recommend output_size is the FOV in x and y axis are same and to be at least 256mm for head, and at least 384mm for other body regions like abdomen. The output size for the x and y axes can be selected from [256, 384, 512], while for the z axis, it can be chosen from [128, 256, 384, 512, 640, 768].
+- `"controllable_anatomy_size"`: a list of controllable anatomy and its size scale (0--1). E.g., if set to `[["liver", 0.5],["hepatic tumor", 0.3]]`, the generated image will contain liver that have a median size, with size around 50% percentile, and hepatic tumor that is relatively small, with around 30% percentile. In addition, if the size scale is set to -1, it indicates that the organ does not exist or should be removed. The output will contain paired image and segmentation mask for the controllable anatomy.
+The following organs support generation with a controllable size: ``["liver", "gallbladder", "stomach", "pancreas", "colon", "lung tumor", "bone lesion", "hepatic tumor", "colon cancer primaries", "pancreatic tumor"]``.
+The raw output of the current mask generation model has a fixed size of $256^3$ voxels with a spacing of $1.5^3$ mm. If the "output_size" differs from this default, the generated masks will be resampled to the desired `"output_size"` and `"spacing"`. Note that resampling may degrade the quality of the generated masks and could trigger multiple inference attempts if the images fail to pass the [image quality check](../scripts/quality_check.py).
+- `"body_region"`: If "controllable_anatomy_size" is not specified, "body_region" will be used to constrain the region of generated images. It needs to be chosen from "head", "chest", "thorax", "abdomen", "pelvis", "lower".
+- `"anatomy_list"`: If "controllable_anatomy_size" is not specified, the output will contain paired image and segmentation mask for the anatomy in "./configs/label_dict.json".
+- `"autoencoder_sliding_window_infer_size"`: in order to save GPU memory, we use sliding window inference when decoding latents to image when `"output_size"` is large. This is the patch size of the sliding window. Small value will reduce GPU memory but increase time cost. They need to be divisible by 16.
+- `"autoencoder_sliding_window_infer_overlap"`: float between 0 and 1. Large value will reduce the stitching artifacts when stitching patches during sliding window inference, but increase time cost. If you do not observe seam lines in the generated image result, you can use a smaller value to save inference time.
+
+To generate images with substantial dimensions, such as 512 × 512 × 512 or larger, using GPUs with 80GB of memory, it is advisable to configure the `"num_splits"` parameter in [the auto-encoder configuration](./configs/config_maisi.json#L11-L37) to 16. This adjustment is crucial to avoid out-of-memory issues during inference.
+
+#### Recommended spacing for different output sizes:
+
+|`"output_size"`| Recommended `"spacing"`|
+|:-----:|:-----:|
+[256, 256, 256]  | [1.5, 1.5, 1.5] |
+[512, 512, 128]  | [0.8, 0.8, 2.5] |
+[512, 512, 512]  | [1.0, 1.0, 1.0] |
+
 ### Execute inference
 The following code generates a synthetic image from a random sampled noise.
 ```

models/maisi_ct_generative/scripts/trainer.py

@@ -15,13 +15,12 @@
 
 import torch
 import torch.nn.functional as F
-from monai.config import IgniteInfo
 from monai.engines.trainer import Trainer
 from monai.engines.utils import IterationEvents, PrepareBatchExtraInput, default_metric_cmp_fn
 from monai.inferers import Inferer
 from monai.networks.schedulers import Scheduler
 from monai.transforms import Transform
-from monai.utils import RankFilter, min_version, optional_import
+from monai.utils import IgniteInfo, RankFilter, min_version, optional_import
 from monai.utils.enums import CommonKeys as Keys
 from torch.optim.optimizer import Optimizer
 from torch.utils.data import DataLoader

models/model_info.json

@@ -1726,5 +1726,45 @@
     "vista3d_v0.5.1": {
         "checksum": "3a1d16b60a52889b0b04616156b104efcc261883",
         "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/vista3d/versions/0.5.1/files/vista3d_v0.5.1.zip"
+    },
+    "vista3d_v0.5.2": {
+        "checksum": "f0388a3f75152f709dda1fd6b08a4c4d8d565358",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/vista3d/versions/0.5.2/files/vista3d_v0.5.2.zip"
+    },
+    "pathology_nuclei_classification_v0.2.0": {
+        "checksum": "f8dd21b3711fa5705a0796704a0a477257b98da1",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/pathology_nuclei_classification/versions/0.2.0/files/pathology_nuclei_classification_v0.2.0.zip"
+    },
+    "brats_mri_axial_slices_generative_diffusion_v1.1.2": {
+        "checksum": "d6a2ac63890fd43280ff01310771ef265df784fb",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/brats_mri_axial_slices_generative_diffusion/versions/1.1.2/files/brats_mri_axial_slices_generative_diffusion_v1.1.2.zip"
+    },
+    "pathology_nuclick_annotation_v0.2.1": {
+        "checksum": "7287d19869b834235e51c1f3e3cfc387a324c76b",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/pathology_nuclick_annotation/versions/0.2.1/files/pathology_nuclick_annotation_v0.2.1.zip"
+    },
+    "brats_mri_generative_diffusion_v1.1.2": {
+        "checksum": "47bc08d062f5cb12d2a5efeba102ccb24e4cef2c",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/brats_mri_generative_diffusion/versions/1.1.2/files/brats_mri_generative_diffusion_v1.1.2.zip"
+    },
+    "lung_nodule_ct_detection_v0.6.8": {
+        "checksum": "1abae7a9379861c477f7b189e0171cfcd71370b0",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/lung_nodule_ct_detection/versions/0.6.8/files/lung_nodule_ct_detection_v0.6.8.zip"
+    },
+    "maisi_ct_generative_v0.4.4": {
+        "checksum": "30aa9a9f53a15ea06b0cfdadbb6876afb072d809",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/maisi_ct_generative/versions/0.4.4/files/maisi_ct_generative_v0.4.4.zip"
+    },
+    "vista2d_v0.2.9": {
+        "checksum": "36d220ff31b3b96ab4ea79b7c56b04aa105b45c9",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/vista2d/versions/0.2.9/files/vista2d_v0.2.9.zip"
+    },
+    "maisi_ct_generative_v0.4.5": {
+        "checksum": "e8271089c14e7aec261cac30ffeec7e07bfa10ef",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/maisi_ct_generative/versions/0.4.5/files/maisi_ct_generative_v0.4.5.zip"
+    },
+    "pathology_tumor_detection_v0.6.1": {
+        "checksum": "e41d063673ee1bc925eccea772b2535676e5e6f0",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/pathology_tumor_detection/versions/0.6.1/files/pathology_tumor_detection_v0.6.1.zip"
     }
 }

models/pathology_nuclei_classification/configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
-    "version": "0.1.9",
+    "version": "0.2.0",
     "changelog": {
+        "0.2.0": "update issue for IgniteInfo",
         "0.1.9": "update tensorrt benchmark results",
         "0.1.8": "enable tensorrt",
         "0.1.7": "update to use monai 1.3.1",

models/pathology_nuclei_classification/scripts/handlers.py

@@ -15,8 +15,7 @@
 import numpy as np
 import torch
 import torch.distributed
-from monai.config import IgniteInfo
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 from sklearn.metrics import classification_report
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")

models/pathology_nuclick_annotation/configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
-    "version": "0.2.0",
+    "version": "0.2.1",
     "changelog": {
+        "0.2.1": "update issue for IgniteInfo",
         "0.2.0": "use monai 1.4 and update large files",
         "0.1.9": "update to use monai 1.3.1",
         "0.1.8": "add load_pretrain flag for infer",

models/pathology_nuclick_annotation/scripts/handlers.py

@@ -15,8 +15,7 @@
 import numpy as np
 import torch
 import torch.distributed
-from monai.config import IgniteInfo
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 make_grid, _ = optional_import("torchvision.utils", name="make_grid")

models/pathology_tumor_detection/configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
-    "version": "0.6.0",
+    "version": "0.6.1",
     "changelog": {
+        "0.6.1": "fix multi-gpu issue",
         "0.6.0": "use monai 1.4 and update large files",
         "0.5.9": "update to use monai 1.3.1",
         "0.5.8": "update readme to add memory warning",

models/pathology_tumor_detection/configs/train.json

@@ -196,6 +196,11 @@
             ]
         },
         "handlers": [
+            {
+                "_target_": "LrScheduleHandler",
+                "lr_scheduler": "@lr_scheduler",
+                "print_lr": true
+            },
             {
                 "_target_": "ValidationHandler",
                 "validator": "@validate#evaluator",
@@ -207,11 +212,6 @@
                 "tag_name": "train_loss",
                 "output_transform": "$monai.handlers.from_engine(['loss'], first=True)"
             },
-            {
-                "_target_": "LrScheduleHandler",
-                "lr_scheduler": "@lr_scheduler",
-                "print_lr": true
-            },
             {
                 "_target_": "TensorBoardStatsHandler",
                 "log_dir": "@output_dir",

models/vista2d/configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
-    "version": "0.2.8",
+    "version": "0.2.9",
     "changelog": {
+        "0.2.9": "fix unsupported data dtype in findContours",
         "0.2.8": "remove relative path in readme",
         "0.2.7": "enhance readme",
         "0.2.6": "update tensorrt benchmark results",

models/vista2d/scripts/components.py

@@ -251,6 +251,7 @@ def __call__(self, data):
                 cv2.imwrite(output_filepath, image)
                 logger.info(f"Overlay Masks: Saving {output_filepath}")
             else:
+                label = cv2.convertScaleAbs(label, alpha=255.0 / label.max())
                 contours, _ = cv2.findContours(label, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
                 polygons.extend(self.to_polygons(contours))
 

models/vista3d/configs/evaluate.json

@@ -22,7 +22,7 @@
         ]
     },
     "label_set": "$list(x[1] for x in @label_mappings#default)",
-    "validate#evaluator#hyper_kwargs#val_head": "auto", 
+    "validate#evaluator#hyper_kwargs#val_head": "auto",
     "validate#preprocessing": {
         "_target_": "Compose",
         "transforms": [
@@ -128,7 +128,10 @@
             },
             {
                 "_target_": "monai.apps.vista3d.transforms.Relabeld",
-                "keys": ["pred", "label"],
+                "keys": [
+                    "pred",
+                    "label"
+                ],
                 "label_mappings": "${'default': [[c, i+1] for i, c in enumerate(@label_set)]}",
                 "dtype": "$torch.uint8"
             }

models/vista3d/configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
-    "version": "0.5.1",
+    "version": "0.5.2",
     "changelog": {
+        "0.5.2": "fix eval issue",
         "0.5.1": "add description for zero-shot and upate eval",
         "0.5.0": "update json file link and add test",
         "0.4.9": "fix oom issue and update readme",