| nnUNet | s2ds | |
|---|---|---|
| 11 | 1 | |
| 5,045 | 4 | |
| 3.6% | - | |
| 9.2 | 10.0 | |
| 3 days ago | over 1 year ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
nnUNet
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Where to even begin to extract yellow spots from these pictures?
Now just run your images and masks in nnUNet to see if it works. https://github.com/MIC-DKFZ/nnUNet
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[D] Improvements/alternatives to U-net for medical images segmentation?
I would also try the nnU-Net which should give state-of-the-art performance, and so will give you a good idea of what's possible with the dataset that you have: https://github.com/MIC-DKFZ/nnUNet
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Seeking ideas for Road Damage Detection
I used the nnUnet repo and their guide on using it on your own data
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Model conversion from Pytorch to Tf using Onnx.
Hi all, Does anyone have experience with converting a nnUNet pytorch models into Tf using Onnx?
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[D] Best practices for training medical imaging models
If you want my honest opinion, you should probably always use nnUnet as a baseline for any 3d segmentation tasks - https://github.com/MIC-DKFZ/nnUNet.
- Image segmentation: huggingface segformers vs detectronv2
- How to get started with 3D computer vision?
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3D rcnn
Not a "detection" but a "segmenting" CNN: https://github.com/MIC-DKFZ/nnunet
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Underwhelming performance of Tesla V100 and A100 in vast.ai, why?
I ran some model fitting performance benchmarks on a 3D (medical) image segmentation UNET on various cloud providers and I am flabbergasted by the very low performance of V100 and A100 machines on vast.ai.
- [D] Which approach is recommended for Brain 🧠Tumor Segmentation on MRI scans (DICOM Files)?
s2ds
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Seeking ideas for Road Damage Detection
It was a custom and private dataset but my colleague has published a very similar one https://github.com/ben-z-original/s2ds
What are some alternatives?
segmentation_models - Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
3d-multi-resolution-rcnn - Official PyTorch implementaiton of the paper "3D Instance Segmentation Framework for Cerebral Microbleeds using 3D Multi-Resolution R-CNN."
medicaldetectiontoolkit - The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
mmpose - OpenMMLab Pose Estimation Toolbox and Benchmark.
albumentations - Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
anime-segmentation - high-accuracy segmentation for anime character