{
    "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
    "version": "0.4.0",
    "changelog": {
        "0.4.0": "rebrand as VISTA-2D, enhance metadata and documentation",
        "0.3.1": "update to huggingface hosting",
        "0.3.0": "update readme",
        "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",
        "0.2.5": "add tensorrt benchmark results",
        "0.2.4": "enable tensorrt inference",
        "0.2.3": "update weights link",
        "0.2.2": "update to use monai components",
        "0.2.1": "initial OSS version"
    },
    "monai_version": "1.4.0",
    "pytorch_version": "2.4.0",
    "numpy_version": "1.24.4",
    "required_packages_version": {
        "einops": "0.7.0",
        "scikit-image": "0.23.2",
        "cucim-cu12": "24.6.0",
        "gdown": "5.2.0",
        "fire": "0.6.0",
        "pyyaml": "6.0.1",
        "tensorboard": "2.17.0",
        "opencv-python": "4.7.0.68",
        "numba": "0.59.1",
        "torchvision": "0.19.0",
        "cellpose": "3.0.8",
        "natsort": "8.4.0",
        "roifile": "2024.5.24",
        "tifffile": "2024.7.2",
        "fastremap": "1.15.0",
        "imagecodecs": "2024.6.1",
        "segment_anything": "1.0"
    },
    "optional_packages_version": {
        "mlflow": "2.14.3",
        "pynvml": "11.4.1",
        "psutil": "5.9.8"
    },
    "supported_apps": {},
    "name": "VISTA-2D: Cell Instance Segmentation",
    "task": "Cell Instance Segmentation in Microscopy Images",
    "description": "VISTA-2D is a flow-based cell instance segmentation model for microscopy images. It processes 256x256 RGB images and generates instance masks with unique labels for each cell. The model supports brightfield, fluorescence, and phase contrast imaging, handling touching cells and overlapping instances.",
    "authors": "MONAI team",
    "copyright": "Copyright (c) MONAI Consortium",
    "data_type": "tiff",
    "image_classes": "3-channel RGB microscopy images, normalized to [0, 1] intensity range",
    "label_classes": "Single-channel instance segmentation mask with unique integer labels for each cell",
    "pred_classes": "3 channels",
    "eval_metrics": {
        "mean_dice": 0.0
    },
    "intended_use": "This is an example, not to be used for diagnostic purposes",
    "references": [],
    "network_data_format": {
        "inputs": {
            "image": {
                "type": "image",
                "num_channels": 3,
                "spatial_shape": [
                    256,
                    256
                ],
                "format": "RGB",
                "value_range": [
                    0,
                    255
                ],
                "dtype": "float32",
                "is_patch_data": true,
                "channel_def": {
                    "0": "image"
                }
            }
        },
        "outputs": {
            "pred": {
                "type": "image",
                "format": "segmentation",
                "num_channels": 3,
                "dtype": "float32",
                "value_range": [
                    0,
                    1
                ],
                "spatial_shape": [
                    256,
                    256
                ]
            }
        }
    }
}