pytorch-CycleGAN-and-pix2pix | Image-to-Image Translation in PyTorch | Machine Learning library

 by   junyanz Python Version: Current License: Non-SPDX

kandi X-RAY | pytorch-CycleGAN-and-pix2pix Summary

kandi X-RAY | pytorch-CycleGAN-and-pix2pix Summary

pytorch-CycleGAN-and-pix2pix is a Python library typically used in Telecommunications, Media, Media, Entertainment, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Generative adversarial networks applications. pytorch-CycleGAN-and-pix2pix has no bugs, it has no vulnerabilities, it has build file available and it has medium support. However pytorch-CycleGAN-and-pix2pix has a Non-SPDX License. You can download it from GitHub.

Image-to-Image Translation in PyTorch

            kandi-support Support

              pytorch-CycleGAN-and-pix2pix has a medium active ecosystem.
              It has 20095 star(s) with 5896 fork(s). There are 343 watchers for this library.
              It had no major release in the last 6 months.
              There are 477 open issues and 935 have been closed. On average issues are closed in 54 days. There are 16 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of pytorch-CycleGAN-and-pix2pix is current.

            kandi-Quality Quality

              pytorch-CycleGAN-and-pix2pix has 0 bugs and 0 code smells.

            kandi-Security Security

              pytorch-CycleGAN-and-pix2pix has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              pytorch-CycleGAN-and-pix2pix code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              pytorch-CycleGAN-and-pix2pix 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.

            kandi-Reuse Reuse

              pytorch-CycleGAN-and-pix2pix 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.
              pytorch-CycleGAN-and-pix2pix saves you 874 person hours of effort in developing the same functionality from scratch.
              It has 2039 lines of code, 178 functions and 36 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed pytorch-CycleGAN-and-pix2pix and discovered the below as its top functions. This is intended to give you an instant insight into pytorch-CycleGAN-and-pix2pix implemented functionality, and help decide if they suit your requirements.
            • Display the current visual results
            • Add html header text
            • Save the document
            • Add images
            • Download data
            • Downloads data from a given dataset url
            • This function processes the cities of the cityscapes
            • Checks if a pair of segments match the given image
            • Define a discriminator layer
            • Get a norm layer
            • Get a palette for the given label
            • Creates a model instance
            • Preprocess the image
            • Save the document to disk
            • Create a dataset
            • Align two images
            • Optimizes G and G
            • Return a list of all files in a folder
            • List all label ids for a given split
            • Define a network layer
            • Plot the current loss for a given epoch
            • Parse options
            • Saves visuals
            • Save all the networks
            • Performs optimization of parameters
            • Modify commandline options
            • Print the current loss
            Get all kandi verified functions for this library.

            pytorch-CycleGAN-and-pix2pix Key Features

            No Key Features are available at this moment for pytorch-CycleGAN-and-pix2pix.

            pytorch-CycleGAN-and-pix2pix Examples and Code Snippets

            FashionGAN Search,Setup
            Jupyter Notebookdot img1Lines of Code : 10dot img1no licencesLicense : No License
            copy iconCopy
            cd data
            conda create -n fashion_gan python=3.6
            source activate fashion_gan
            conda install --file conda_requirements.txt
            pip install -r pip_requirements.txt
            source activate fashion_gan
            jupyter notebook
            source deactivate
            conda env  
            Pythondot img2Lines of Code : 10dot img2License : Permissive (MIT)
            copy iconCopy
              	title={CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering},
              	author={Zhengqi Li and Noah Snavely},
              	booktitle={European Conference on Computer Vision (ECCV)},
            copy iconCopy
            python --dataroot ./datasets/test  --model test --checkpoints_dir ./checkpoints/  --name d2p/  --dataset_mode single --no_dropout  --norm batch
            demo_steps=1000 # number of iterations
            img_path='./simulated.JPEG' . # given an image

            Community Discussions


            pytorch cyclegann gives a Missing key error when testing
            Asked 2021-May-26 at 11:04

            I have trained a model using the pix2pix pytorch implementation and would like to test it.

            However when I test it I get the error



            Answered 2021-May-26 at 11:04

            I think the problem here is some layer the bias=None but in testing the model required this, you should check the code for details.

            After I check your config in train and test, the norm is different. For the code in GitHub, the norm difference may set the bias term is True or False.



            How can only have one tensor?
            Asked 2021-Mar-27 at 17:12

            I think there is an error in line 53 of the following code:

            CycleGan, Buffer for Images

            It says:



            Answered 2021-Mar-27 at 17:12

  's first argument is expected to be a sequence of tensors rather than a single tensor. So you pass in like:



            Converting a pytorch model to nn.Module for exporting to onnx for lens studio
            Asked 2020-Aug-06 at 22:20

            I am trying to convert pix2pix to a pb or onnx that can run in Lens Studio. Lens studio has strict requirements for the models. I am trying to export this pytorch model to onnx using this guide provided by lens studio. The issue is the pytorch model found here uses its own base class, when in the example it uses Module.nn, and therefore doesnt have methods/variables that the torch.onnx.export function needs to run. So far Ive run into its missing a variable called training and a method called train

            Would it be worth it to try to modify the base model, or should I try to build it from scratch using nn.Module? Is there a way to make the pix2pix model inherit from both the abstract base class and nn.module? Am I not understanding the situation? The reason why I want to do it using the lens studio tutorial is because I have gotten it to export onnx different ways but Lens Studio wont accept those for various reasons.

            Also this is my first time asking a SO question (after 6 years of coding), let me know if I make any mistakes and I can correct them. Thank you.

            This is the important code from the tutorial creating a pytorch model for Lens Studio:



            Answered 2020-Aug-06 at 22:08

            You can definitely have your model inherit from both the base class and torch.nn.Module (python allows multiple inheritance). However you should take care about the conflicts if both inherited class have functions with identical names (I can see at least one : their base provide the eval function and so to nn.module).

            However since you do not need the CycleGan, and a lot of the code is compatibility with their training environment, you'd probably better just re-implement the pix2pix. Just steal the code, have it inherit from nn.Module, copy-paste useful/mandatory functions from the base class, and have everything translated into clean pytorch code. You already have the forward function (which is the only requirement for a pytorch module).

            All the subnetworks they use (like the resnet blocks) seem to inherit from nn.Module already so there is nothing to change here (double check that though)



            "ignoring potentially dangerous server-supplied filename" in pscp
            Asked 2020-May-29 at 16:59

            I want to copy some file from a remote Linux system to my Windows PC using pscp (from PuTTY). I wrote a small script that should copy all .png files in a directory on my server:



            Answered 2020-May-28 at 14:25

            -unsafe won't help with this.

            The problem is that your file names contain colons. Colons are not allowed in Windows file names.


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


            No vulnerabilities reported

            Install pytorch-CycleGAN-and-pix2pix

            Clone this repo:
            Install PyTorch and 0.4+ and other dependencies (e.g., torchvision, visdom and dominate). For pip users, please type the command pip install -r requirements.txt. For Conda users, you can create a new Conda environment using conda env create -f environment.yml. For Docker users, we provide the pre-built Docker image and Dockerfile. Please refer to our Docker page. For Repl users, please click .


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
            Find more information at:

            Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items

            Find more libraries
          • HTTPS


          • CLI

            gh repo clone junyanz/pytorch-CycleGAN-and-pix2pix

          • sshUrl


          • Stay Updated

            Subscribe to our newsletter for trending solutions and developer bootcamps

            Agree to Sign up and Terms & Conditions

            Share this Page

            share link