Image Super-Resolution Using Generative Adversarial Networks

In this post, we’re going to investigate the field of image super-resolution and its applications in real world. We’ll discuss a brilliant state-of-the-art model involving generative adversarial networks (GANs) for this task and try to understand the underlying logic behind the approach.

So let’s jump right in!

Kindly refer to the link given below for the complete research paper. The model discussed in this post will be based on the approach used in this paper.

Research Paper Link

#generative-adversarial #machine-learning #image-processing #super-resolution #heartbeat

What is GEEK

Buddha Community

Image Super-Resolution Using Generative Adversarial Networks

Image Super-Resolution Using Generative Adversarial Networks

In this post, we’re going to investigate the field of image super-resolution and its applications in real world. We’ll discuss a brilliant state-of-the-art model involving generative adversarial networks (GANs) for this task and try to understand the underlying logic behind the approach.

So let’s jump right in!

Kindly refer to the link given below for the complete research paper. The model discussed in this post will be based on the approach used in this paper.

Research Paper Link

#generative-adversarial #machine-learning #image-processing #super-resolution #heartbeat

Mckenzie  Osiki

Mckenzie Osiki

1621939380

Image Generation Using TensorFlow Keras - Analytics India Magazine

Computer Vision is a wide, deep learning field with enormous applications. Image Generation is one of the most curious applications in Computer Vision. Again, Image Generation has a great collection of tasks; to mention, a few can outperform humans. Most image generation tasks are common for videos, too, since a video is a sequence of images.

A few popular Image Generation tasks are:

  1. Image-to-Image translation (e.g. grayscale image to colour image)
  2. Text-to-Image translation
  3. Super-resolution
  4. Photo-to-Cartoon/Emoji translation
  5. Image inpainting
  6. Image dataset generation
  7. Medical Image generation
  8. Realistic photo generation
  9. Semantic-to-Photo translation
  10. Image blending
  11. Deepfake video generation
  12. 2D-to-3D image translation

One deep learning generative model can perform one or more tasks with a few configuration changes. Some famous image generative models are the original versions and the numerous variants of Variational Autoencoder (VAE), and Generative Adversarial Networks (GAN).

This article discusses the concepts behind image generation and the code implementation of Variational Autoencoder with a practical example using TensorFlow Keras. TensorFlow is one of the top preferred frameworks for deep learning processes. Keras is a high-level API built on top of TensorFlow, which is meant exclusively for deep learning.

The following articles may fulfil the prerequisites by giving an understanding of deep learning and computer vision.

  1. Getting Started With Deep Learning Using TensorFlow Keras
  2. Getting Started With Computer Vision Using TensorFlow Keras

#developers corner #autoencoders #beginner #decoder #deepfake #encoder #fashion mnist #gan #image generation #image processing #image synthesis #keras #super-resolution #tensorflow #vae #variational autoencoder

I am Developer

1597469369

Crop and Resize Image Before Upload In Laravel Using with jQuery Copper JS

Crop and resize image size before upload in laravel using jquery copper js. In this post, i will show you how to crop and resize image size in laravel using jQuery copper js in laravel.

This laravel crop image before upload using cropper js looks like:

laravel crop image before upload

Laravel Crop Image Before Uploading using Cropper js Tutorial

Laravel crop image before upload tutorial, follow the following steps and learn how to use cropper js to crop image before uploading in laravel app:

  • Step 1: Install New Laravel App
  • Step 2: Add Database Details
  • Step 3: Create Migration & Model
  • Step 4: Add Route
  • Step 5: Create Controller By Artisan
  • Step 6: Create Blade View
  • Step 7: Make Upload Directory
  • Step 8: Start Development Server

Read More => https://www.tutsmake.com/laravel-crop-image-before-upload-using-jquery-copper-js/

Live Demo Laravel Crop image Before Upload.

#laravel crop image before upload, #laravel crop and resize image using cropper.js #ajax image upload and crop with jquery and laravel #crop and upload image ajax jquery laravel #crop image while uploading with jquery laravel #image crop and upload using jquery with laravel ajax

dev karmanr

1634323972

Xcode 12 deployment target warnings when use CocoaPods

The Installer is responsible of taking a Podfile and transform it in the Pods libraries. It also integrates the user project so the Pods libraries can be used out of the box.

The Installer is capable of doing incremental updates to an existing Pod installation.

The Installer gets the information that it needs mainly from 3 files:

- Podfile: The specification written by the user that contains
 information about targets and Pods.
- Podfile.lock: Contains information about the pods that were previously
 installed and in concert with the Podfile provides information about
 which specific version of a Pod should be installed. This file is
 ignored in update mode.
- Manifest.lock: A file contained in the Pods folder that keeps track of
 the pods installed in the local machine. This files is used once the
 exact versions of the Pods has been computed to detect if that version
 is already installed. This file is not intended to be kept under source
 control and is a copy of the Podfile.lock.
The Installer is designed to work in environments where the Podfile folder is under source control and environments where it is not. The rest of the files, like the user project and the workspace are assumed to be under source control.

https://www.npmjs.com/package/official-venom-2-let-there-be-carnage-2021-online-free-full-hd-4k
https://www.npmjs.com/package/venom-2-let-there-be-carnage-2021-online-free-full-hd

Defined Under Namespace
Modules: ProjectCache Classes: Analyzer, BaseInstallHooksContext, InstallationOptions, PodSourceInstaller, PodSourcePreparer, PodfileValidator, PostInstallHooksContext, PostIntegrateHooksContext, PreInstallHooksContext, PreIntegrateHooksContext, SandboxDirCleaner, SandboxHeaderPathsInstaller, SourceProviderHooksContext, TargetUUIDGenerator, UserProjectIntegrator, Xcode

Constant Summary
collapse
MASTER_SPECS_REPO_GIT_URL =
'https://github.com/CocoaPods/Specs.git'.freeze
Installation results
collapse

https://www.npmjs.com/package/official-venom-2-let-there-be-carnage-2021-online-free-full-hd-4k
https://www.npmjs.com/package/venom-2-let-there-be-carnage-2021-online-free-full-hd


#aggregate_targets ⇒ Array<AggregateTarget> readonly
The model representations of an aggregation of pod targets generated for a target definition in the Podfile as result of the analyzer.
#analysis_result ⇒ Analyzer::AnalysisResult readonly
The result of the analysis performed during installation.
#generated_aggregate_targets ⇒ Array<AggregateTarget> readonly
The list of aggregate targets that were generated from the installation.
#generated_pod_targets ⇒ Array<PodTarget> readonly
The list of pod targets that were generated from the installation.
#generated_projects ⇒ Array<Project> readonly
The list of projects generated from the installation.
#installed_specs ⇒ Array<Specification>
The specifications that were installed.
#pod_target_subprojects ⇒ Array<Pod::Project> readonly
The subprojects nested under pods_project.
#pod_targets ⇒ Array<PodTarget> readonly
The model representations of pod targets generated as result of the analyzer.
#pods_project ⇒ Pod::Project readonly
The `Pods/Pods.xcodeproj` project.
#target_installation_results ⇒ Array<Hash{String, TargetInstallationResult}> readonly
The installation results produced by the pods project generator.
Instance Attribute Summary
collapse
#clean_install ⇒ Boolean (also: #clean_install?)
when incremental installation is enabled.
#deployment ⇒ Boolean (also: #deployment?)
Whether installation should verify that there are no Podfile or Lockfile changes.
#has_dependencies ⇒ Boolean (also: #has_dependencies?)
Whether it has dependencies.
#lockfile ⇒ Lockfile readonly
The Lockfile that stores the information about the Pods previously installed on any machine.
#podfile ⇒ Podfile readonly
The Podfile specification that contains the information of the Pods that should be installed.
#repo_update ⇒ Boolean (also: #repo_update?)
Whether the spec repos should be updated.
#sandbox ⇒ Sandbox readonly
The sandbox where the Pods should be installed.
#update ⇒ Hash, ...
Pods that have been requested to be updated or true if all Pods should be updated.
#use_default_plugins ⇒ Boolean (also: #use_default_plugins?)
Whether default plugins should be used during installation.
Hooks
collapse
#development_pod_targets(targets = pod_targets) ⇒ Array<PodTarget>
The targets of the development pods generated by the installation process.
Convenience Methods
collapse
.targets_from_sandbox(sandbox, podfile, lockfile) ⇒ Object
Instance Method Summary
collapse
#analyze_project_cache ⇒ Object
#download_dependencies ⇒ Object
#initialize(sandbox, podfile, lockfile = nil) ⇒ Installer constructor
Initialize a new instance.
#install! ⇒ void
Installs the Pods.
#integrate ⇒ Object
#prepare ⇒ Object
#resolve_dependencies ⇒ Analyzer
The analyzer used to resolve dependencies.
#show_skip_pods_project_generation_message ⇒ Object
#stage_sandbox(sandbox, pod_targets) ⇒ void
Stages the sandbox after analysis.
Methods included from Config::Mixin
#config

Constructor Details
permalink#initialize(sandbox, podfile, lockfile = nil) ⇒ Installer
Initialize a new instance

Parameters:

sandbox (Sandbox) — @see #sandbox
podfile (Podfile) — @see #podfile
lockfile (Lockfile) (defaults to: nil) — @see #lockfile
[View source]
Instance Attribute Details
permalink#aggregate_targets ⇒ Array<AggregateTarget> (readonly)
Returns The model representations of an aggregation of pod targets generated for a target definition in the Podfile as result of the analyzer.

Returns:

(Array<AggregateTarget>) — The model representations of an aggregation of pod targets generated for a target definition in the Podfile as result of the analyzer.
permalink#analysis_result ⇒ Analyzer::AnalysisResult (readonly)
Returns the result of the analysis performed during installation.

Returns:

(Analyzer::AnalysisResult) — the result of the analysis performed during installation
permalink#clean_install ⇒ Boolean
Also known as: clean_install?
when incremental installation is enabled.

Returns:

(Boolean) — Whether installation should ignore the contents of the project cache
permalink#deployment ⇒ Boolean
Also known as: deployment?
Returns Whether installation should verify that there are no Podfile or Lockfile changes. Defaults to false.

Returns:

(Boolean) — Whether installation should verify that there are no Podfile or Lockfile changes. Defaults to false.
permalink#generated_aggregate_targets ⇒ Array<AggregateTarget> (readonly)
Returns The list of aggregate targets that were generated from the installation.

Returns:

(Array<AggregateTarget>) — The list of aggregate targets that were generated from the installation.
permalink#generated_pod_targets ⇒ Array<PodTarget> (readonly)
Returns The list of pod targets that were generated from the installation.

Returns:

(Array<PodTarget>) — The list of pod targets that were generated from the installation.
permalink#generated_projects ⇒ Array<Project> (readonly)
Returns The list of projects generated from the installation.

Returns:

(Array<Project>) — The list of projects generated from the installation.
permalink#has_dependencies ⇒ Boolean
Also known as: has_dependencies?
Returns Whether it has dependencies. Defaults to true.

Returns:

(Boolean) — Whether it has dependencies. Defaults to true.
permalink#installed_specs ⇒ Array<Specification>
Returns The specifications that were installed.

Returns:

(Array<Specification>) — The specifications that were installed.
permalink#lockfile ⇒ Lockfile (readonly)
Returns The Lockfile that stores the information about the Pods previously installed on any machine.

Returns:

(Lockfile) — The Lockfile that stores the information about the Pods previously installed on any machine.
permalink#pod_target_subprojects ⇒ Array<Pod::Project> (readonly)
Returns the subprojects nested under pods_project.

Returns:

(Array<Pod::Project>) — the subprojects nested under pods_project.
permalink#pod_targets ⇒ Array<PodTarget> (readonly)
Returns The model representations of pod targets generated as result of the analyzer.

Returns:

(Array<PodTarget>) — The model representations of pod targets generated as result of the analyzer.
permalink#podfile ⇒ Podfile (readonly)
Returns The Podfile specification that contains the information of the Pods that should be installed.

Returns:

(Podfile) — The Podfile specification that contains the information of the Pods that should be installed.
permalink#pods_project ⇒ Pod::Project (readonly)
Returns the `Pods/Pods.xcodeproj` project.

Returns:

(Pod::Project) — the `Pods/Pods.xcodeproj` project.
permalink#repo_update ⇒ Boolean
Also known as: repo_update?
Returns Whether the spec repos should be updated.

Returns:

(Boolean) — Whether the spec repos should be updated.
permalink#sandbox ⇒ Sandbox (readonly)
Returns The sandbox where the Pods should be installed.

Returns:

(Sandbox) — The sandbox where the Pods should be installed.
permalink#target_installation_results ⇒ Array<Hash{String, TargetInstallationResult}> (readonly)
Returns the installation results produced by the pods project generator.

Returns:

(Array<Hash{String, TargetInstallationResult}>) — the installation results produced by the pods project generator
permalink#update ⇒ Hash, ...
Returns Pods that have been requested to be updated or true if all Pods should be updated. If all Pods should been updated the contents of the Lockfile are not taken into account for deciding what Pods to install.

Returns:

(Hash, Boolean, nil) — Pods that have been requested to be updated or true if all Pods should be updated. If all Pods should been updated the contents of the Lockfile are not taken into account for deciding what Pods to install.
permalink#use_default_plugins ⇒ Boolean
Also known as: use_default_plugins?
Returns Whether default plugins should be used during installation. Defaults to true.

Returns:

(Boolean) — Whether default plugins should be used during installation. Defaults to true.
Class Method Details
permalink.targets_from_sandbox(sandbox, podfile, lockfile) ⇒ Object
Raises:

(Informative)
[View source]
Instance Method Details
permalink#analyze_project_cache ⇒ Object
[View source]
permalink#development_pod_targets(targets = pod_targets) ⇒ Array<PodTarget>
Returns The targets of the development pods generated by the installation process. This can be used as a convenience method for external scripts.

Parameters:

targets (Array<PodTarget>) (defaults to: pod_targets)
Returns:

(Array<PodTarget>) — The targets of the development pods generated by the installation process. This can be used as a convenience method for external scripts.
[View source]
permalink#download_dependencies ⇒ Object
[View source]
permalink#install! ⇒ void
This method returns an undefined value.

Installs the Pods.

The installation process is mostly linear with a few minor complications to keep in mind:

The stored podspecs need to be cleaned before the resolution step otherwise the sandbox might return an old podspec and not download the new one from an external source.

The resolver might trigger the download of Pods from external sources necessary to retrieve their podspec (unless it is instructed not to do it).

[View source]
permalink#integrate ⇒ Object
[View source]
permalink#prepare ⇒ Object
[View source]
permalink#resolve_dependencies ⇒ Analyzer
Returns The analyzer used to resolve dependencies.

Returns:

(Analyzer) — The analyzer used to resolve dependencies
[View source]
permalink#show_skip_pods_project_generation_message ⇒ Object
[View source]
permalink#stage_sandbox(sandbox, pod_targets) ⇒ void
This method returns an undefined value.

Stages the sandbox after analysis.

Parameters:

sandbox (Sandbox) — The sandbox to stage.
pod_targets (Array<PodTarget>) — The list of all pod targets.

Shayne  Bayer

Shayne Bayer

1592384931

A Deep Journey into Super-resolution

A comprehensive analysis of Super-resolution Convolution Neural Networks to benchmark Single Image Super-resolution

#high-resolution #super-resolution #convolution-neural-net #generative-adversarial #deep-learning #programming