fast-style-transfer | TensorFlow CNN for fast style transfer ⚡🖥🎨🖼 | Computer Vision library

by lengstrom Python Version: Current License: No License

X-Ray Key Features Code Snippets(3)Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | fast-style-transfer Summary

fast-style-transfer is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning, Pytorch, Tensorflow applications. fast-style-transfer has no bugs, it has no vulnerabilities and it has medium support. However fast-style-transfer build file is not available. You can download it from GitHub.

Add styles from famous paintings to any photo in a fraction of a second! You can even style videos!. It takes 100ms on a 2015 Titan X to style the MIT Stata Center (1024×680) like Udnie, by Francis Picabia. Our implementation is based off of a combination of Gatys' A Neural Algorithm of Artistic Style, Johnson's Perceptual Losses for Real-Time Style Transfer and Super-Resolution, and Ulyanov's Instance Normalization.

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Quality

Security

License

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Support

fast-style-transfer has a medium active ecosystem.

It has 10663 star(s) with 2638 fork(s). There are 323 watchers for this library.

It had no major release in the last 6 months.

There are 98 open issues and 130 have been closed. On average issues are closed in 132 days. There are 9 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of fast-style-transfer is current.

Quality

fast-style-transfer has 0 bugs and 0 code smells.

Security

fast-style-transfer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

fast-style-transfer code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

fast-style-transfer does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

fast-style-transfer releases are not available. You will need to build from source code and install.

fast-style-transfer has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed fast-style-transfer and discovered the below as its top functions. This is intended to give you an instant insight into fast-style-transfer implemented functionality, and help decide if they suit your requirements.

Optimizer for training
Return the size of a tensor
Net layer
Layer convolution layer
Get list of images in img_dir
List files in_path
Wrapper for fwd
Save image to out_path
Validate options
Fail if path exists
Run ffwd on different images
Wrapper for ffwd
Build the argument parser
List all files in_path
Wrapper for ffmpeg
Wrapper function for fwd

Get all kandi verified functions for this library.

fast-style-transfer Key Features

No Key Features are available at this moment for fast-style-transfer.

fast-style-transfer Examples and Code Snippets

fast-style-transfer,Run style transfer

Python

Lines of Code : 14

License : Permissive (MIT)

Copy

sh get_data.sh

python main.py train \
  --content-weight 15 \
  --style-weight 100 \
  --target-style data/styles/hatch.jpg \
  --validation-dir data/validation

python main.py test \
  --model-name MODEL_NAME \
  --ckpt CKPT \
  --test-dir data/val

fast-style-transfer,Dependencies

Python

Lines of Code : 6

License : Permissive (MIT)

Copy

python==2.7
ffmpeg==3.2.2

numpy==1.13.0
scipy==0.18.1
tensorflow==1.1.0
tensorbayes==0.2.0

Fast Style Transfer,Usage,Train model

Python

Lines of Code : 5

License : No License

Copy

python train.py \
    --log-dir models/mosaic/ \
    --style-image images/style/mosaic.jpg \
    --test-image images/content/amber.jpg

tensorboard --logdir models/

Community Discussions

Trending Discussions on fast-style-transfer

How to fix Cross-Origin Request Block in angular when making a post request to an external api call

How to send a curl request in angular

OpenCV does not accept ndarray to TextDecectorCNN.detect()

QUESTION

How to fix Cross-Origin Request Block in angular when making a post request to an external api call

Asked 2021-Oct-13 at 21:56

I have the following post request that im making to an external api : The request works when i pass 2 links to images but when i pass the base64 string of an image i get a Cross-Origin error this is my code:

Html:

...

ANSWER

Answered 2021-Oct-13 at 21:56

If you use the developer console to inspect the request that is sent when calling the API here: https://deepai.org/machine-learning-model/fast-style-transfer, you'll see that a File object rather than a data URL is being appended to the FormData object.

You should be able to skip the FileReader and use the File object directly:

Source https://stackoverflow.com/questions/69550263

QUESTION

How to send a curl request in angular

Asked 2021-Oct-12 at 14:56

I have the following curl request using postman, and i want to create an http request in angular that does the same thing

...

ANSWER

Answered 2021-Oct-12 at 14:33

The POST request body is expected to be in JSON, therefore try to build a FormData object as shown in the following code snippet.

Also, set the headers to accept data as JSON.

Source https://stackoverflow.com/questions/69541424

QUESTION

OpenCV does not accept ndarray to TextDecectorCNN.detect()

Asked 2020-Apr-21 at 11:50

I am trying to use this OpenCV class of text detector to find out if I can use it for my project. I am loaging image like this:

...

ANSWER

Answered 2020-Apr-21 at 11:50

Your problem is that you don't create an instance of your text detector. See this:

Source https://stackoverflow.com/questions/61329523

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

Vulnerabilities

No vulnerabilities reported

Install fast-style-transfer

Tested on | Spec | | |-----------------------------|-------------------------------------------------------------| | Operating System | Windows 10 Home | | GPU | Nvidia GTX 2080 TI | | CUDA Version | 11.0 | | Driver Version | 445.75 |.

Support

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 .

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