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

Related tags

Deep Learning tensorflow enet semantic-segmentation cityscapes pspnet ade20k icnet fcn-8s
Overview

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:

FCN PSPNet ICNet
Google drive Google drive Google 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:

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 Image PSPNet FCN

cityscapes

Input Image ICNet ENet

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}
}
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Comments
  • Error when using ICNet model

    Error when using ICNet model

    Hi!

    First of all, thanks for sharing your very helpful code. Following the README.md, I have downloaded icnet.npy from Google Drive link to the model/cityscapes folder.

    However, when I run

    python inference.py --img-path input/outdoor_1.png --model icnet

    the following error happens:

    Traceback (most recent call last):
  File "inference.py", line 65, in <module>
    main()
  File "inference.py", line 44, in main
    model = ICNet()
  File "/home/tadashi/ML/semantic-segmentation-tensorflow/model.py", line 907, in __init__
    super().__init__({'data': self.img_tf}, num_classes, is_training)
TypeError: super() takes at least 1 argument (0 given)
    opened by htadashi 2
  • Cityscapes test data

    Cityscapes test data

    Can you tell me how to test the mean iou in the cityscape test set online? Because the cityscape test set has no tags, online testing is required, but I don't know what to do.I uploaded the test results as he asked, but there was always Content of zip archive does not match specifications. Not all predictions for all images were found. Thank you very much！

    opened by InstantWindy 0
  • about the training

    about the training

    Hi, @hellochick ,

    Thanks for releasing such useful package. However, only inference tools are provided. Would you also release the training part for them?

    Thanks~

    opened by amiltonwong 1
  • How to use ENet?

    How to use ENet?

    I am trying to use ENet for segmentation, but from the README.md it is not clear how I may do that. I tried passing the model_path as os.path.join('model','cityscapes','enet.ckpt.meta')

    But I get the following error:

    InvalidArgumentError (see above for traceback): No OpKernel was registered to support Op 'MaxPoolWithArgmax' with these attrs. Registered devices: [CPU], Registered kernels:

    [[Node: MaxPoolWithArgmax = MaxPoolWithArgmaxT=DT_FLOAT, Targmax=DT_INT64, ksize=[1, 2, 2, 1], padding="SAME", strides=[1, 2, 2, 1]]]

    Note: I fixed your typo at line 898, where you had "variabl" instead of "variable"

    opened by srcolinas 0
Owner
HsuanKung Yang
HsuanKung Yang
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