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https://github.com/pvnieo/deep-levi
Automatic colorization using deep neural networks.
https://github.com/pvnieo/deep-levi
automatic-colorization colorization computer-vision deep-learning keras
Last synced: 11 days ago
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Automatic colorization using deep neural networks.
- Host: GitHub
- URL: https://github.com/pvnieo/deep-levi
- Owner: pvnieo
- License: apache-2.0
- Created: 2018-04-08T17:39:19.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2020-12-15T10:39:58.000Z (about 4 years ago)
- Last Synced: 2024-08-27T14:16:49.166Z (4 months ago)
- Topics: automatic-colorization, colorization, computer-vision, deep-learning, keras
- Language: Python
- Homepage:
- Size: 446 MB
- Stars: 7
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Deep-Levi
Implementation of some automatic colorization models using deep neural network:
1. Implementation of the regression-based model provided in: "Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification" [Link to the original paper](http://hi.cs.waseda.ac.jp/~iizuka/projects/colorization/en/)
2. Implementation of a classification-based model inspired in part by Zhang et al. in "Colorful Image Colorization" [[Link to the original paper](https://github.com/richzhang/colorization)] and R.Dah in [here](http://tinyclouds.org/colorize)
3. Implementation of a regression-based model inspired from [this Medium blog article](https://medium.freecodecamp.org/colorize-b-w-photos-with-a-100-line-neural-network-53d9b4449f8d)
## Project report
You can consult the project report [here](https://github.com/pvnieo/Deep-Levi/blob/master/%C3%89tude%20comparative%20d%E2%80%99architecture%20de%20colorisation%20automatique.pdf) (in French)
## Installation
This project runs on python >= 3.6, use pip to install dependencies:
```
pip3 install -r requirements.txt
```
## Usage
Use the `main.py` script to choose the model to train and the parameters to use
```
usage: main.py [-h] [-m {naive,reg,classif}] [-d DATA_DIR] [-e EPOCHS]
[-b BATCH_SIZE] [-tc TO_COLOR] [--no-load] [--no-save]
[--no-train] [--early]
An implementation of multiple approachs to automatically colorize grey-scale
images
optional arguments:
-h, --help show this help message and exit
-m {naive,reg,classif}, --model {naive,reg,classif}
Colorization model
-d DATA_DIR, --data-dir DATA_DIR
Directory where data is
-e EPOCHS, --epochs EPOCHS
Number of epochs to train for
-b BATCH_SIZE, --batch-size BATCH_SIZE
Batch size to use
-tc TO_COLOR, --to-color TO_COLOR
Number of samples to be colored
--no-load Disable loading saved model
--no-save Disable saving the new model
--no-train Disable training the model
--early Enable early stopping
```
Use the `levi.py` script to color images using a model
```
usage: levi.py -h [-d DATA_DIR]
An implementation of multiple approachs to automatically colorize grey-scale
images
optional arguments:
-h, --help show this help message and exit
-m {naive,reg,classif}, --model {naive,reg,classif}
Colorization model
-d DATA_DIR, --data-dir DATA_DIR
Directory where the images to be colored is
```
## Note
This project is under development. The final objective being to create a model that colors mangas by learning on the corresponding anime, this project will be updated regularly.