The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more ā
Segmentation_models.pytorch Alternatives
Similar projects and alternatives to segmentation_models.pytorch
-
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
detectron2
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
-
pytorch-image-models
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
-
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
-
-
labelme
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
-
SegmentationCpp
A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: VGG, ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.
-
pyannote-audio
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
-
efficientdet-pytorch
A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights
-
-
TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch
Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better segmentation_models.pytorch alternative or higher similarity.
segmentation_models.pytorch reviews and mentions
Posts with mentions or reviews of segmentation_models.pytorch.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-09.
-
Instance segmentation of small objects in grainy drone imagery
Also, Iād suggest considering switching to the segmentation-models library - it provides U-Net models with a variety of pretrained backbones of as encoders. The author also put out a PyTorch version. https://github.com/qubvel/segmentation_models.pytorch https://github.com/qubvel/segmentation_models
-
[D] Improvements/alternatives to U-net for medical images segmentation?
SMP offers a wide variety of segmentation models with the option to use pre-trained weights.
-
Improvements/alternatives to U-net for medical images segmentation?
SMP has a lot of different choices for architecture other than unet, and a ton of different encoders. I like deeplabv3+/unet with regnety encoder, works well for most things https://github.com/qubvel/segmentation_models.pytorch
-
Medical Image Segmentation Human Retina
This basic example from segmentation models PyTorch repo would be good tutorial to start with. The library is very good, I like the unet, fpn and deeplabv3+ architectures with regnety as encoder https://github.com/qubvel/segmentation_models.pytorch/blob/master/examples/binary_segmentation_intro.ipynb
-
Automatic generation of image-segmentation mask pairs with StableDiffusion
Sounds like a good semantic segmentation problem, I like this repo: https://github.com/qubvel/segmentation_models.pytorch
-
Dice Score not decreasing when doing semantic segmentation
When i pass the CT-Scans and the masks to the Loss Function, which is the Jaccard-Loss from the segmentation_models.pytorch library, the value does not decrease but stay in the range of 1.0-0.9 over 50 epochs training on only one batch of 32 images. As far as I have understood, my network should overfit and the loss should decrease since I am only training on one batch of a small amount of images. However this does not happen. I also tried more batches with all the data over 100 epochs, but the loss does not decrease either obviously. Does anyone have an idea what I might have done wrong? Do I have to change anything when passing the masks to my loss function?
-
Good Brain Tumor segmentation model !?
I know there is a decent one in segmentation models python (MA-Net: A Multi-Scale Attention Network for Liver and Tumor Segmentation)
-
Advice needed
You could also use qubvel's segmentation models if you would like to explore semantic segmentation.
-
[D][R] Is there a standard architecture for U-Nets, pixel-to-pixel models, VAEs, and the like?
Check out segmentation models pytorch, really easy to use, has a great interface.
-
Pytorch GPU Memory Leak Problem: Cuda Out of Memory Error !!
Have you tried another implementation? For example: qubvel/segmentation_models.pytorch
-
A note from our sponsor - WorkOS
workos.com | 26 Apr 2024
Stats
Basic segmentation_models.pytorch repo stats
14
8,800
2.8
4 days ago
qubvel/segmentation_models.pytorch is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of segmentation_models.pytorch is Python.
Popular Comparisons
- segmentation_models.pytorch VS yolact
- segmentation_models.pytorch VS mmsegmentation
- segmentation_models.pytorch VS face-parsing.PyTorch
- segmentation_models.pytorch VS EfficientNet-PyTorch
- segmentation_models.pytorch VS SegmentationCpp
- segmentation_models.pytorch VS pyannote-audio
- segmentation_models.pytorch VS efficientdet-pytorch
- segmentation_models.pytorch VS pytorch-image-models
- segmentation_models.pytorch VS TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch
- segmentation_models.pytorch VS Pytorch-UNet
Sponsored
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com