DAGAN | ACM MM 2020 ] Dual Attention GANs | Machine Learning library

 by   Ha0Tang Python Version: Current License: Non-SPDX

kandi X-RAY | DAGAN Summary

kandi X-RAY | DAGAN Summary

DAGAN is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Generative adversarial networks applications. DAGAN has no bugs, it has no vulnerabilities, it has build file available and it has low support. However DAGAN has a Non-SPDX License. You can download it from GitHub.

Dual Attention GANs for Semantic Image Synthesis Hao Tang1, Song Bai2, Nicu Sebe13. 1University of Trento, Italy, 2University of Oxford, UK, 3Huawei Research Ireland, Ireland. In ACM MM 2020. The repository offers the official implementation of our paper in PyTorch. In the meantime, check out our related CVPR 2020 paper Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation and Arxiv paper Edge Guided GANs with Semantic Preserving for Semantic Image Synthesis.
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            kandi-support Support

              DAGAN has a low active ecosystem.
              It has 88 star(s) with 11 fork(s). There are 4 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 0 open issues and 7 have been closed. On average issues are closed in 6 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of DAGAN is current.

            kandi-Quality Quality

              DAGAN has 0 bugs and 0 code smells.

            kandi-Security Security

              DAGAN has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              DAGAN code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              DAGAN has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

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              DAGAN releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              DAGAN saves you 982 person hours of effort in developing the same functionality from scratch.
              It has 2235 lines of code, 177 functions and 34 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed DAGAN and discovered the below as its top functions. This is intended to give you an instant insight into DAGAN implemented functionality, and help decide if they suit your requirements.
            • Display the current visual results
            • Add images
            • Saves numpy array to png
            • Convert visuals to numpy tensors
            • Create the path to the dataset
            • Recursively make a set of images
            • Create a dataset from a directory
            • Colormap
            • Convert ID to label
            • Modify commandline options
            • Get paths for training images
            • Get paths for training data
            • Get the paths for the images
            • Make the paths for the image
            • Create a data loader
            • Create the paths for the dataset
            • Record end of epoch
            • Perform the forward computation
            • Print current errors
            • Records one iteration per iteration
            • Forward pass through x
            • Forward the forward function
            • Saves visuals to the webpage
            • Parse the options
            • Update learning rate
            • Compute the loss function
            Get all kandi verified functions for this library.

            DAGAN Key Features

            No Key Features are available at this moment for DAGAN.

            DAGAN Examples and Code Snippets

            No Code Snippets are available at this moment for DAGAN.

            Community Discussions

            QUESTION

            Regex to extract bibliography text from paragraph - Python
            Asked 2020-Jul-06 at 20:34

            In my Python task, I've a string (Paragraph) of bibliography that I want to parse into list of strings.

            here is whole string

            ...

            ANSWER

            Answered 2020-Jul-06 at 20:34

            unable to get a proper result. because string does not have any specific end. But every new string is starting with Author Name(s) following by year

            This may be enough. I've written a regex that works on your whole sample,
            however it is still subjective. Any add or subtract of name form or punctuation
            will blow it out of the water.

            Source https://stackoverflow.com/questions/62762766

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install DAGAN

            This code requires PyTorch 1.0 and python 3+. Please install dependencies by. This code also requires the Synchronized-BatchNorm-PyTorch rep. To reproduce the results reported in the paper, you would need an NVIDIA DGX1 machine with 8 V100 GPUs.

            Support

            If you have any questions/comments/bug reports, feel free to open a github issue or pull a request or e-mail to the author Hao Tang (hao.tang@unitn.it).
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            git@github.com:Ha0Tang/DAGAN.git

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