srgan | Realistic Single Image Super-Resolution Using | Computer Vision library

by tensorlayer Python Version: 1.4.1 License: No License

X-Ray Key Features Code Snippets(4)Community Discussions(7)Vulnerabilities Install Support

kandi X-RAY | srgan Summary

srgan is a Python library typically used in Telecommunications, Media, Media, Entertainment, Artificial Intelligence, Computer Vision, Deep Learning, Tensorflow, Generative adversarial networks applications. srgan has no bugs, it has no vulnerabilities, it has build file available and it has medium support. You can download it from GitHub.

TensorFlow Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network".

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Quality

Security

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Support

srgan has a medium active ecosystem.

It has 2880 star(s) with 784 fork(s). There are 95 watchers for this library.

It had no major release in the last 12 months.

There are 132 open issues and 103 have been closed. On average issues are closed in 61 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of srgan is 1.4.1

Quality

srgan has 0 bugs and 0 code smells.

Security

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

srgan code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

srgan 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

srgan releases are available to install and integrate.

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

Installation instructions are not available. Examples and code snippets are available.

srgan saves you 84 person hours of effort in developing the same functionality from scratch.

It has 216 lines of code, 8 functions and 3 files.

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

Top functions reviewed by kandi - BETA

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

Create a VGG16 model
Restore pre - trained weights
Train the network
Create a VGG19 model

Get all kandi verified functions for this library.

srgan Key Features

No Key Features are available at this moment for srgan.

srgan Examples and Code Snippets

网络结构

Python

Lines of Code : 168

License : No License

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def SRGAN_g(t_image):
    # Input-Conv-Relu
    n = fluid.layers.conv2d(input=t_image, num_filters=64, filter_size=3, stride=1, padding='SAME', name='n64s1/c', data_format='NCHW')
    # print('conv0', n.shape)
    n = fluid.layers.batch_norm(n, momen

训练策略

Python

Lines of Code : 123

License : No License

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# init
t_image = fluid.layers.data(name='t_image',shape=[96, 96, 3],dtype='float32')
t_target_image = fluid.layers.data(name='t_target_image',shape=[384, 384, 3],dtype='float32')
vgg19_input = fluid.layers.data(name='vgg19_input',shape=[224, 224, 3],

图像超分辨率（Image Super Resolution）,五、模型设计,5.4 判别器

Python

Lines of Code : 76

License : No License

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class Discriminator(tf.keras.Model):
    def __init__(self, data_format='channels_last'):
        super(Discriminator, self).__init__(name='')

        if data_format == 'channels_first':
            self._input_shape = [-1, 3, 128, 128]

tensorlayer - tutorial cifar10 cnn static

Python

Lines of Code : 130

License : Non-SPDX

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import multiprocessing
import time

import numpy as np
import tensorflow as tf

import tensorlayer as tl
from tensorlayer.layers import (BatchNorm, Conv2d, Dense, Flatten, Input, LocalResponseNorm, MaxP

Community Discussions

Trending Discussions on srgan

Error: All inputs to the layer should be tensors- when trying to use VGG19 model

Bicubic block in Keras model

Input 0 of layer fc1 is incompatible with the layer: expected axis -1 of input shape to have value 25088 but received input with shape (None, 32768)

Why and How to make range of Output image from a Neural Network [-1,1] in SRGAN?

How to save a jupyter notebook with outputs

Enhancing the resolution of an image

I have cuDNN error when tensorflow Docker

QUESTION

Error: All inputs to the layer should be tensors- when trying to use VGG19 model

Asked 2021-Dec-09 at 07:08

While trying to import VGG19 model, the code below generates an error of non tensor inputs. Although I am following another this code snippet here.

Code:

...

ANSWER

Answered 2021-Dec-02 at 16:49

Maybe try converting your images to tensors:

Source https://stackoverflow.com/questions/70202638

QUESTION

Bicubic block in Keras model

Asked 2021-Nov-01 at 01:37

While working with the code of SRGAN, I wanted to replace UpSampling2D by tf.image.resize_bicubic. I used keras lambda layer for this function, as below

...

ANSWER

Answered 2021-Nov-01 at 01:37

here is a one liner solution.

Source https://stackoverflow.com/questions/69785637

QUESTION

Input 0 of layer fc1 is incompatible with the layer: expected axis -1 of input shape to have value 25088 but received input with shape (None, 32768)

Asked 2021-Jun-01 at 11:46

I'm implementing SRGAN (and am not very experienced in this field), which uses a pre-trained VGG19 model to extract features. The following code was working fine on Keras 2.1.2 and tf 1.15.0 till yesterday. then it started throwing an "AttributeError: module 'keras.utils.generic_utils' has no attribute 'populate_dict_with_module_objects'" So i updated the keras version to 2.4.3 and tf to 2.5.0. but then its showing a "Input 0 of layer fc1 is incompatible with the layer: expected axis -1 of input shape to have value 25088 but received input with shape (None, 32768)" on the following line

...

ANSWER

Answered 2021-Jun-01 at 11:46

Importing keras from tensorflow and setting include_top=False in

Source https://stackoverflow.com/questions/67707204

QUESTION

Why and How to make range of Output image from a Neural Network [-1,1] in SRGAN?

Asked 2020-Jul-23 at 04:06

I've been working on reimplementing Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network (SRGAN), now I'm stuck with the given information in section 3.2. Based on the paper, the target HR should be in the range [-1,1], the input LR should be in the range [0,1], and MSE loss was calculated on images in range [-1,1].

The last sentence implies that the output from the generator network should be in [-1,1]. So that the content_loss = MSELoss(generator(output), target). Am I understanding correctly? But when I print the output from my generator network, whose laster is just a conv2d, it gives me images in the rage [0,1].

I'm not getting a good result by running SRResNet-MSE part, and I think maybe because the MSE loss is calculating on different ranges instead of just one [-1,1]?

But how can the output from my generator be in range [-1,1] if I still want to follow paper's architecture, which has conv2d as the last layer?

I also include my code Class Generator here

...

ANSWER

Answered 2020-Jul-23 at 04:06

Given that you want output in the range [-1,1] and currently you are getting output in [0,1] simply doing.

Source https://stackoverflow.com/questions/63045572

QUESTION

How to save a jupyter notebook with outputs

Asked 2020-Jun-09 at 18:12

How can I save a jupyter notebook with outputs? I'm editing my notebook with Google Collab and want to save it as a .ipynb file with outputs shown, like here: https://nbviewer.jupyter.org/github/krasserm/super-resolution/blob/master/example-srgan.ipynb.

But when I Download .ipynb on Google Collab, you can't see the outputs in the resulting file. How can I get the outputs to show?

Related question: how can I have the outputs save in the Google Collab doc? Right now, the outputs always disappear on reload, even though I disabled the hide outputs on save.

...

ANSWER

Answered 2020-Jun-09 at 18:12

When I downloaded it did show me the content. Make sure you used Save on the notebook before downloading (I uploaded my result to https://nbviewer.jupyter.org/ and it worked and showed the preview). If it doesn't work, check the next item on my list.
Double-check the settings at "Settings" -> "Site" and make sure "New notebooks use private outputs (omit outputs when saving)" is disabled. Similarly, check also "Edit" -> "Notebook settings" and make sure "Omit code cell output when saving this notebook" is disabled. Yes, these are two separate settings.
Retry 1# if it didn't work before after toggling both settings. Also, notebooks should now save the output.

Source https://stackoverflow.com/questions/62288996

QUESTION

Enhancing the resolution of an image

Asked 2020-Feb-21 at 02:22

I have images that are having very low quality and these images I have to use for person identification but with this quality it's difficult to detect. I want to enhance the quality of the images using deep learning/machine learning techniques. I have studied about SRCNN, perceptual Loss, SRResNet, SRGAN but most of the super image resolution techniques require original images for improving the quality of the images. So my question is there any deep learning techniques that can be used for the improving the quality of the images without using the original images.

...

ANSWER

Answered 2020-Feb-21 at 02:22

You can try applying a sharpening kernel

Before -> After

Source https://stackoverflow.com/questions/60319321

QUESTION

I have cuDNN error when tensorflow Docker

Asked 2020-Jan-14 at 05:57

I want to use including and after tensorflow2.0 in Docker. I want to use (https://github.com/tensorlayer/srgan).

My Dockerfile is

...

ANSWER

Answered 2020-Jan-14 at 05:57

Can you try setting

config.gpu_options.allow_growth = True

Source https://stackoverflow.com/questions/59728205

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

Vulnerabilities

No vulnerabilities reported

Install srgan

You can download it from GitHub.
You can use srgan like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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