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Semantic segmentation tensorflow

Semantic segmentation task for ADE20k & cityscapse dataset, based on several models.

From hellochick·Updated January 30, 2026·View on GitHub·

This is a Tensorflow implementation of semantic segmentation models on [MIT ADE20K scene parsing dataset](https://github.com/hangzhaomit/semantic-segmentation-pytorch) and [Cityscapes dataset](https://www.cityscapes-dataset.com/benchmarks/) The project is written primarily in Python, first published in 2018. Key topics include: ade20k, cityscapes, enet, fcn-8s, icnet.

semantic-segmentation-tensorflow

This is a Tensorflow implementation of semantic segmentation models on MIT ADE20K scene parsing dataset and Cityscapes dataset
 
We re-produce the inference phase of several models, including PSPNet, FCN, and ICNet by transforming the released pre-trained weights into tensorflow format, and apply on handcraft models. Also, we refer to ENet from freg856 github. Still working on task integrated.

Models

  1. PSPNet
  2. FCN
  3. ENet
  4. ICNet

...to be continue

Install

Get corresponding transformed pre-trained weights, and put into model directory:

FCNPSPNetICNet
Google driveGoogle driveGoogle drive

Inference

Run following command:

python inference.py --img-path /Path/To/Image --dataset Model_Type

Arg list

--model - choose from "icnet"/"pspnet"/"fcn"/"enet"  

Import module in your code:

python
from model import FCN8s, PSPNet50, ICNet, ENet model = PSPNet50() # or another model model.read_input(img_path) # read image data from path sess = tf.Session(config=config) init = tf.global_variables_initializer() sess.run(init) model.load(model_path, sess) # load pretrained model preds = model.forward(sess) # Get prediction

Results

ade20k

Input ImagePSPNetFCN

cityscapes

Input ImageICNetENet

Citation

@inproceedings{zhao2017pspnet,
  author = {Hengshuang Zhao and
            Jianping Shi and
            Xiaojuan Qi and
            Xiaogang Wang and
            Jiaya Jia},
  title = {Pyramid Scene Parsing Network},
  booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017}
}

Scene Parsing through ADE20K Dataset. B. Zhou, H. Zhao, X. Puig, S. Fidler, A. Barriuso and A. Torralba. Computer Vision and Pattern Recognition (CVPR), 2017. (http://people.csail.mit.edu/bzhou/publication/scene-parse-camera-ready.pdf)

@inproceedings{zhou2017scene,
    title={Scene Parsing through ADE20K Dataset},
    author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
    booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
    year={2017}
}

Semantic Understanding of Scenes through ADE20K Dataset. B. Zhou, H. Zhao, X. Puig, S. Fidler, A. Barriuso and A. Torralba. arXiv:1608.05442. (https://arxiv.org/pdf/1608.05442.pdf)

@article{zhou2016semantic,
  title={Semantic understanding of scenes through the ade20k dataset},
  author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
  journal={arXiv preprint arXiv:1608.05442},
  year={2016}
}

Contributors

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This article is auto-generated from hellochick/semantic-segmentation-tensorflow via the GitHub API.Last fetched: 6/17/2026