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14 changes: 7 additions & 7 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@ limitations under the License.
# MONAI Label
[![License](https://img.shields.io/badge/license-Apache%202.0-green.svg)](https://opensource.org/licenses/Apache-2.0)
[![CI Build](https://github.com/Project-MONAI/MONAILabel/workflows/build/badge.svg?branch=main)](https://github.com/Project-MONAI/MONAILabel/commits/main)
[![Documentation Status](https://readthedocs.org/projects/monailabel/badge/?version=latest)](https://docs.monai.io/projects/label/en/latest/?badge=latest)
[![Documentation Status](https://readthedocs.org/projects/monailabel/badge/?version=latest)](https://monai.readthedocs.io/projects/label/en/latest/?badge=latest)
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⚠️ Potential issue | 🟡 Minor

Fix heading level hierarchy.

The static analysis flagged a heading-level mismatch at this line. Review the heading structure to ensure it increments by only one level at a time.

🧰 Tools
🪛 markdownlint-cli2 (0.18.1)

17-17: Heading levels should only increment by one level at a time
Expected: h2; Actual: h3

(MD001, heading-increment)

🤖 Prompt for AI Agents
In README.md around line 17, the badge line sits at a heading level that creates
a mismatch in the document's heading hierarchy; adjust the surrounding headings
so levels increment by only one at a time (e.g., change an H3 to H2 or H2 to H3
as appropriate) or move the badge out of the heading block so that the sequence
of headings before and after line 17 follows a single-level step difference,
ensuring consistent Markdown heading levels throughout the file.

[![PyPI version](https://badge.fury.io/py/monailabel.svg)](https://badge.fury.io/py/monailabel)
[![Azure DevOps tests (compact)](https://img.shields.io/azure-devops/tests/projectmonai/monai-label/10?compact_message)](https://dev.azure.com/projectmonai/monai-label/_test/analytics?definitionId=10&contextType=build)
[![Azure DevOps coverage](https://img.shields.io/azure-devops/coverage/projectmonai/monai-label/10)](https://dev.azure.com/projectmonai/monai-label/_build?definitionId=10)
Expand All @@ -27,7 +27,7 @@ open-source and easy-to-install ecosystem that can run locally on a machine with
and client work on the same/different machine. It shares the same principles
with [MONAI](https://github.com/Project-MONAI).

Refer to full [MONAI Label documentations](https://docs.monai.io/projects/label/en/latest/index.html) for more details or check out our [MONAI Label Deep Dive videos series](https://www.youtube.com/playlist?list=PLtoSVSQ2XzyD4lc-lAacFBzOdv5Ou-9IA).
Refer to full [MONAI Label documentations](https://monai.readthedocs.io/projects/label/en/latest/index.html) for more details or check out our [MONAI Label Deep Dive videos series](https://www.youtube.com/playlist?list=PLtoSVSQ2XzyD4lc-lAacFBzOdv5Ou-9IA).

Refer to [MONAI Label Tutorial](https://github.com/Project-MONAI/tutorials/tree/main/monailabel) series for application and viewer workflows with different medical image tasks. Notebook-like tutorials are created for detailed instructions.

Expand Down Expand Up @@ -182,8 +182,8 @@ In addition, you can find a table of the basic supported fields, modalities, vie
<pre>pip install -U monailabel</pre>

MONAI Label supports the following OS with **GPU/CUDA** enabled. For more details instruction, please see the installation guides.
- [Ubuntu](https://docs.monai.io/projects/label/en/latest/installation.html)
- [Windows](https://docs.monai.io/projects/label/en/latest/installation.html#windows)
- [Ubuntu](https://monai.readthedocs.io/projects/label/en/latest/installation.html)
- [Windows](https://monai.readthedocs.io/projects/label/en/latest/installation.html#windows)

### GPU Acceleration (Optional Dependencies)
Following are the optional dependencies which can help you to accelerate some GPU based transforms from MONAI. These dependencies are enabled by default if you are using `projectmonai/monailabel` docker.
Expand Down Expand Up @@ -401,15 +401,15 @@ the [contributing guidelines](https://github.com/Project-MONAI/MONAILabel/blob/m
## Community

Join the conversation on Twitter [@ProjectMONAI](https://twitter.com/ProjectMONAI) or join
our [Slack channel](https://projectmonai.slack.com/archives/C031QRE0M1C).
our [Slack channel](https://join.slack.com/t/projectmonai/shared_invite/zt-3hucgm02q-i8Bn9XofDZs2UGOH4jUl4w).

Ask and answer questions over
on [MONAI Label's GitHub Discussions tab](https://github.com/Project-MONAI/MONAILabel/discussions).

## Additional Resources

- Website: https://monai.io/
- API documentation: https://docs.monai.io/projects/label
- Website: https://project-monai.github.io/
- API documentation: https://monai.readthedocs.io/projects/label
- Code: https://github.com/Project-MONAI/MONAILabel
- Project tracker: https://github.com/Project-MONAI/MONAILabel/projects
- Issue tracker: https://github.com/Project-MONAI/MONAILabel/issues
Expand Down
6 changes: 3 additions & 3 deletions sample-apps/endoscopy/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -106,7 +106,7 @@ interactive and automated segmentation.
</summary>
This model is currently trained to segment **Tool** from 2D in-body images.

- Network: This model uses the [BasicUNet](https://docs.monai.io/en/latest/networks.html#basicunet) as the default network.
- Network: This model uses the [BasicUNet](https://monai.readthedocs.io/en/stable/networks.html#basicunet) as the default network.
- Labels: `{ "Tool": 1 }`
- Dataset: The model is pre-trained over few in-body Images related to Endoscopy
- Inputs: 3 channels.
Expand All @@ -119,7 +119,7 @@ This model is currently trained to segment **Tool** from 2D in-body images.
<summary>
<strong>ToolTracking</strong> is based on UNet for automated segmentation. This model works for single label segmentation tasks.
</summary>
- Network: This model uses the [FlexibleUNet](https://docs.monai.io/en/latest/networks.html#flexibleunet) as the default network.
- Network: This model uses the [FlexibleUNet](https://monai.readthedocs.io/en/stable/networks.html#flexibleunet) as the default network.
- Labels: `{ "Tool": 1 }`
- Dataset: The model is pre-trained over few in-body Images related to Endoscopy
- Inputs: 1 channel for the image modality
Expand All @@ -130,7 +130,7 @@ This model is currently trained to segment **Tool** from 2D in-body images.
<summary>
<strong>InBody/OutBody</strong> is based on SEResNet50 for classification. This model determines if tool is present or not (in-body vs out-body).
</summary>
- Network: This model uses the [SEResNet50](https://docs.monai.io/en/latest/networks.html#seresnet50) as the default network.
- Network: This model uses the [SEResNet50](https://monai.readthedocs.io/en/stable/networks.html#seresnet50) as the default network.
- Labels: `{ "InBody": 0, "OutBody": 1 }`
- Dataset: The model is pre-trained over few in-body Images related to Endoscopy
- Inputs: 1 channel for the image modality
Expand Down
2 changes: 1 addition & 1 deletion sample-apps/monaibundle/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@ limitations under the License.
# MONAI Bundle Application
The MONAIBundle App allows you to easily pull any MONAI Bundle from the [MONAI Model Zoo](https://github.com/Project-MONAI/model-zoo/tree/dev/models) and import it into MONAI Label. However, it's important to note that any MONAI Bundle used with MONAI Label must meet the following constraints:

- It must comply with the [MONAI Bundle Specification](https://docs.monai.io/en/latest/mb_specification.html).
- It must comply with the [MONAI Bundle Specification](https://monai.readthedocs.io/en/stable/mb_specification.html).
Copy link

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⚠️ Potential issue | 🟡 Minor

Fix heading level hierarchy.

The static analysis flagged a heading-level mismatch at this line. Review the heading structure to ensure it increments by only one level at a time (e.g., h1 → h2, not h1 → h3).

🧰 Tools
🪛 markdownlint-cli2 (0.18.1)

17-17: Heading levels should only increment by one level at a time
Expected: h2; Actual: h3

(MD001, heading-increment)

🤖 Prompt for AI Agents
In sample-apps/monaibundle/README.md around line 17, the parser flagged a
heading-level mismatch at this line — ensure the heading here increments by only
one level from the previous heading. Inspect the preceding heading level and
change this heading so it is exactly one level deeper (e.g., if the previous is
h1 make this h2, if previous is h2 make this h3), updating the Markdown heading
markers accordingly so the document hierarchy is consistent.

- For inference, the bundle must define either an `inference.json` or `inference.yaml` file, and it must include the keys described in the bundle.py file located in the `monailabel/tasks/infer/` directory.
- For training, the bundle must define either a `train.json` or `train.yaml file`, and it must include the keys described in the bundle.py file located in the `monailabel/tasks/train/` directory.
- For multi-GPU training, the bundle must define either a `multi_gpu_train.json` or `multi_gpu_train.yaml` file.
Expand Down
12 changes: 6 additions & 6 deletions sample-apps/radiology/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,7 @@ monailabel start_server --app workspace/radiology --studies workspace/images --c

### Hybrid Radiology App with Models and Bundles

Radiology app now supports loading models from local or from bundles in [MONAI Model Zoo](https://monai.io/model-zoo)
Radiology app now supports loading models from local or from bundles in [MONAI Model Zoo](https://project-monai.github.io/model-zoo)

```bash
# Example: Pick two models of spleen and multi-organ segmentation model, and two model-zoo bundles.
Expand Down Expand Up @@ -106,7 +106,7 @@ A command example to use active learning strategies with DeepEdit would be:

> monailabel start_server --app workspace/radiology --studies workspace/images --conf models deepedit --conf skip_scoring false --conf skip_strategies false --conf epistemic_enabled true

- Network: This model uses the DynUNet as the default network. It also comes with pretrained model for [UNETR](https://docs.monai.io/en/latest/networks.html#unetr). Researchers can define their own network or use one of the listed [here](https://docs.monai.io/en/latest/networks.html)
- Network: This model uses the DynUNet as the default network. It also comes with pretrained model for [UNETR](https://monai.readthedocs.io/en/stable/networks.html#unetr). Researchers can define their own network or use one of the listed [here](https://monai.readthedocs.io/en/stable/networks.html)
- Labels:
```json
{
Expand Down Expand Up @@ -151,7 +151,7 @@ the model to learn on new organ.
|----------------------|--------------------|-----------------------------------------------------------------|
| preload | true, **false** | Preload model into GPU |

- Network: This App uses the [BasicUNet](https://docs.monai.io/en/latest/networks.html#basicunet) as the default network.
- Network: This App uses the [BasicUNet](https://monai.readthedocs.io/en/stable/networks.html#basicunet) as the default network.
- Labels:
```json
[
Expand Down Expand Up @@ -191,7 +191,7 @@ the model to learn on new organ.
| preload | true, **false** | Preload model into GPU |
| scribbles | **true**, false | Don't load the scribble models, useful for user studies |

- Network: This model uses the [UNet](https://docs.monai.io/en/latest/networks.html#unet) as the default network. Researchers can define their own network or use one of the listed [here](https://docs.monai.io/en/latest/networks.html)
- Network: This model uses the [UNet](https://monai.readthedocs.io/en/stable/networks.html#unet) as the default network. Researchers can define their own network or use one of the listed [here](https://monai.readthedocs.io/en/stable/networks.html)
- Labels
```json
{
Expand Down Expand Up @@ -242,7 +242,7 @@ A command example to use active learning strategies with segmentation_spleen wou
> monailabel start_server --app workspace/radiology --studies workspace/images --conf models segmentation_spleen --conf skip_scoring false --conf skip_strategies false --conf epistemic_enabled true


- Network: This App uses the [UNet](https://docs.monai.io/en/latest/networks.html#unet) as the default network.
- Network: This App uses the [UNet](https://monai.readthedocs.io/en/stable/networks.html#unet) as the default network.
- Labels: `{ "Spleen": 1 }`
- Dataset: The model is pre-trained over dataset: http://medicaldecathlon.com/
- Inputs: 1 channel for the image modality
Expand Down Expand Up @@ -280,7 +280,7 @@ The difference between second and third stage is that third stage get a more fin
|----------------------|--------------------|-----------------------------------------------------------------|
| use_pretrained_model | **true**, false | Disable this NOT to load any pretrained weights |

- Network: This App uses the [UNet](https://docs.monai.io/en/latest/networks.html#unet) as the default network.
- Network: This App uses the [UNet](https://monai.readthedocs.io/en/stable/networks.html#unet) as the default network.
- Labels:
```json
{
Expand Down
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