keras-io / deeplabv3p-resnet50

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Total runs: 16
24-hour runs: -4
7-day runs: -4
30-day runs: -10
Model's Last Updated: July 05 2024
image-segmentation

Introduction of deeplabv3p-resnet50

Model Details of deeplabv3p-resnet50

Multiclass semantic segmentation using DeepLabV3+

This repo contains the model and the notebook to this Keras example on Multiclass semantic segmentation using DeepLabV3+ .

Full credits to: Soumik Rakshit

The model is trained for demonstrative purposes and does not guarantee the best results in production. For better results, follow & optimize the Keras example as per your need.

Background Information

Semantic segmentation, with the goal to assign semantic labels to every pixel in an image, is an essential computer vision task. In this example, we implement the DeepLabV3+ model for multi-class semantic segmentation, a fully-convolutional architecture that performs well on semantic segmentation benchmarks.

Training Data

The model is trained on a subset (10,000 images) of Crowd Instance-level Human Parsing Dataset . The Crowd Instance-level Human Parsing (CIHP) dataset has 38,280 diverse human images. Each image in CIHP is labeled with pixel-wise annotations for 20 categories, as well as instance-level identification. This dataset can be used for the "human part segmentation" task.

Model

The model uses ResNet50 pretrained on ImageNet as the backbone model.

References:

  1. Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
  2. Rethinking Atrous Convolution for Semantic Image Segmentation
  3. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Runs of keras-io deeplabv3p-resnet50 on huggingface.co

16
Total runs
-4
24-hour runs
-4
3-day runs
-4
7-day runs
-10
30-day runs

More Information About deeplabv3p-resnet50 huggingface.co Model

More deeplabv3p-resnet50 license Visit here:

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deeplabv3p-resnet50 huggingface.co

deeplabv3p-resnet50 huggingface.co is an AI model on huggingface.co that provides deeplabv3p-resnet50's model effect (), which can be used instantly with this keras-io deeplabv3p-resnet50 model. huggingface.co supports a free trial of the deeplabv3p-resnet50 model, and also provides paid use of the deeplabv3p-resnet50. Support call deeplabv3p-resnet50 model through api, including Node.js, Python, http.

deeplabv3p-resnet50 huggingface.co Url

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keras-io deeplabv3p-resnet50 online free

deeplabv3p-resnet50 huggingface.co is an online trial and call api platform, which integrates deeplabv3p-resnet50's modeling effects, including api services, and provides a free online trial of deeplabv3p-resnet50, you can try deeplabv3p-resnet50 online for free by clicking the link below.

keras-io deeplabv3p-resnet50 online free url in huggingface.co:

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deeplabv3p-resnet50 install

deeplabv3p-resnet50 is an open source model from GitHub that offers a free installation service, and any user can find deeplabv3p-resnet50 on GitHub to install. At the same time, huggingface.co provides the effect of deeplabv3p-resnet50 install, users can directly use deeplabv3p-resnet50 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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