DeOldify | Deep Learning based project | Computer Vision library

by jantic Python Version: 0.0.1 License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | DeOldify Summary

DeOldify is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning applications. DeOldify has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install DeOldify' or download it from GitHub, PyPI.

Simply put, the mission of this project is to colorize and restore old images and film footage. We'll get into the details in a bit, but first let's see some pretty pictures and videos!.

Support

Quality

Security

License

Reuse

Support

DeOldify has a medium active ecosystem.

It has 16638 star(s) with 2409 fork(s). There are 442 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 352 have been closed. On average issues are closed in 2 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of DeOldify is 0.0.1

Quality

DeOldify has 0 bugs and 0 code smells.

Security

DeOldify has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

DeOldify code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

DeOldify is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

DeOldify releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

It has 1794 lines of code, 122 functions and 20 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

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DeOldify Key Features

No Key Features are available at this moment for DeOldify.

DeOldify Examples and Code Snippets

Functions,Examples,Breadfruit, approx. 1870

Lines of Code : 14

License : Non-SPDX (NOASSERTION)

Copy

# API call
colorizer::colorize(
  img = "https://upload.wikimedia.org/wikipedia/commons/9/9e/Breadfruit.jpg", 
  key = my_key
  ) %>%
  
  # Saving colorized image
  colorizer::clsave(destfile = "colorized.png") %>% 
  
  # Comparing colorized

Functions,Examples,My Grandpa, 1936

Lines of Code : 6

License : Non-SPDX (NOASSERTION)

Copy

colorizer::colorize(
  img = "diskus1936.jpg", 
  key = my_key
  ) %>%
  colorizer::juxtapose("side-by-side") %>% 
  colorizer::clsave("HansZumbach.jpg")

Functions,Examples,Children, 1920s

Lines of Code : 6

License : Non-SPDX (NOASSERTION)

Copy

colorizer::colorize(
  img = "https://cdn.pixabay.com/photo/2013/02/13/22/38/children-81487_1280.jpg", 
  key = my_key,
  ) %>% 
  juxtapose("side-by-side") %>% 
  clsave("children1920.jpg")

Community Discussions

Trending Discussions on DeOldify

How do you read a Python Traceback error?

QUESTION

How do you read a Python Traceback error?

Asked 2021-Jun-06 at 10:31

I have run some Python code in Windows 10 and gotten the Traceback error below. Does it mean the string that is supposed to be an int occurs in line 347 of /DeOldify/deoldify/filters.py or line 1943 of /lib/site-packages/PIL/Image.py?

For context, below the traceback error, I've also included the steps that lead to this error (I attempted to colorize a black and white film clip based on the DeOldify Colab https://colab.research.google.com/github/jantic/DeOldify/blob/master/VideoColorizerColab.ipynb but only succeeded at colorizing the first frame as a .jpeg) and the full terminal output.

EDIT: Thanks to @Daweo's response, I discovered the problem was with the arguments I entered into the terminal as indicated by "", line 1. The correct command should have been:
video_path = colorizer.colorize_from_file_name(file_name='my_video.mp4', render_factor=render_factor)
Also, the code for colorizing a photograph is from https://colab.research.google.com/github/jantic/DeOldify/blob/master/ImageColorizerColab.ipynb

The error:

...

ANSWER

Answered 2021-May-31 at 07:59

Does it mean the string that is supposed to be an int occurs in line 347 of /DeOldify/deoldify/filters.py or line 1943 of /lib/site-packages/PIL/Image.py

This imply something in filters.py is responsbile for such usage of something from Image.py that raised TypeError.

Consider simple example let zerodiv.py content be:

Source https://stackoverflow.com/questions/67769750

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

Vulnerabilities

No vulnerabilities reported

Install DeOldify

We have build for you a quickstart script for you in order to get up to speed in a minute. It's even compatible if you don't have GPU and will automatically adjust it's configuration according to your hardware (running on CPU will be slow with no surprise).
your notebook will be accessible on port 8888.
Starting the image api. Starting the video api. your API will be accessible on port 5000.
This project is built around the wonderful Fast.AI library. Prereqs, in summary:.
Fast.AI 1.0.51 (and its dependencies). If you use any higher version you'll see grid artifacts in rendering and tensorboard will malfunction. So yeah...don't do that.
PyTorch 1.0.1 Not the latest version of PyTorch- that will not play nicely with the version of FastAI above. Note however that the conda install of FastAI 1.0.51 grabs the latest PyTorch, which doesn't work. This is patched over by our own conda install but fyi.
Jupyter Lab conda install -c conda-forge jupyterlab
Tensorboard (i.e. install Tensorflow) and TensorboardX (https://github.com/lanpa/tensorboardX). I guess you don't have to but man, life is so much better with it. FastAI now comes with built in support for this- you just need to install the prereqs: conda install -c anaconda tensorflow-gpu and pip install tensorboardX
ImageNet – Only if you're training, of course. It has proven to be a great dataset for my purposes. http://www.image-net.org/download-images

Support

We believe that open source has done a lot of good for the world. After all, DeOldify simply wouldn't exist without it. But we also believe that there needs to be boundaries on just how much is reasonable to be expected from an open source project maintained by just two developers. Our stance is that we're providing the code and documentation on research that we believe is beneficial to the world. What we have provided are novel takes on colorization, GANs, and video that are hopefully somewhat friendly for developers and researchers to learn from and adopt. This is the culmination of well over a year of continuous work, free for you. What wasn't free was shouldered by us, the developers. We left our jobs, bought expensive GPUs, and had huge electric bills as a result of dedicating ourselves to this. What we haven't provided here is a ready to use free "product" or "app", and we don't ever intend on providing that. It's going to remain a Linux based project without Windows support, coded in Python, and requiring people to have some extra technical background to be comfortable using it. Others have stepped in with their own apps made with DeOldify, some paid and some free, which is what we want! We're instead focusing on what we believe we can do best- making better commercial models that people will pay for. Does that mean you're not getting the very best for free? Of course. We simply don't believe that we're obligated to provide that, nor is it feasible! We compete on research and sell that. Not a GUI or web service that wraps said research- that part isn't something we're going to be great at anyways. We're not about to shoot ourselves in the foot by giving away our actual competitive advantage for free, quite frankly. We're also not willing to go down the rabbit hole of providing endless, open ended and personalized support on this open source project. Our position is this: If you have the proper background and resources, the project provides more than enough to get you started. We know this because we've seen plenty of people using it and making money off of their own projects with it. . Thus, if you have an issue come up and it happens to be an actual bug that having it be fixed will benefit users generally, then great- that's something we'll be happy to look into. . In contrast, if you're asking about something that really amounts to asking for personalized and time consuming support that won't benefit anybody else, we're not going to help. It's simply not in our interest to do that. We have bills to pay, after all. And if you're asking for help on something that can already be derived from the documentation or code? That's simply annoying, and we're not going to pretend to be ok with that.

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