WebCam Effects: A Virtual Webcam tool Built with OpenCV and ONNX

WebCam Effects

Requirements

Go through the following steps to get your environment up and running.

Installing

To install the WebCam Effects module run the following command:

pip install -e .

obs: It has only been tested on python 3.7 but it is likely to work on other versions.

Setup Virtual Video Device

To create the virtual video device run the following command:

sudo modprobe v4l2loopback exclusive_caps=1 video_nr=2 # creates /dev/video2

obs: It may require you to install v4l2loopback module (sudo apt install v4l2loopback-dkms)

Running

During the installation of the WebCam Effects it will create an entrypoint called 'wce' which you can use to run it. So, just put it in your console and press enter:

wce

You can change the effects in real time by updating the config.yaml file.

Available Effects

NameDescriptionArguments
BG_BLURBlur the image background(kernel_size: int, dilate: int)
BG_REMOVERemove the background(kernel_size: int, dilate: int)
FACE_FOLLOWFollow the face(scale: float, filter: float)
FLIPFlip the image(horizontal: bool, vertical: bool)
BRIGHTNESS_AND_CONTRASTEnhance the image brightness and contrast(alpha: float, beta: int)
BILATERAL_FILTEROpenCV Bilateral filter(kernel_size: int)
FPSShow the FPS(flip: bool, scale: float, color: list)

 

Demo

OriginalProcessed
webcam originalwebcam processed

Download details:

Author: esgario
Source code: https://github.com/esgario/webcam-effects
License: MIT license

#opencv #python

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WebCam Effects: A Virtual Webcam tool Built with OpenCV and ONNX

WebCam Effects: A Virtual Webcam tool Built with OpenCV and ONNX

WebCam Effects

Requirements

Go through the following steps to get your environment up and running.

Installing

To install the WebCam Effects module run the following command:

pip install -e .

obs: It has only been tested on python 3.7 but it is likely to work on other versions.

Setup Virtual Video Device

To create the virtual video device run the following command:

sudo modprobe v4l2loopback exclusive_caps=1 video_nr=2 # creates /dev/video2

obs: It may require you to install v4l2loopback module (sudo apt install v4l2loopback-dkms)

Running

During the installation of the WebCam Effects it will create an entrypoint called 'wce' which you can use to run it. So, just put it in your console and press enter:

wce

You can change the effects in real time by updating the config.yaml file.

Available Effects

NameDescriptionArguments
BG_BLURBlur the image background(kernel_size: int, dilate: int)
BG_REMOVERemove the background(kernel_size: int, dilate: int)
FACE_FOLLOWFollow the face(scale: float, filter: float)
FLIPFlip the image(horizontal: bool, vertical: bool)
BRIGHTNESS_AND_CONTRASTEnhance the image brightness and contrast(alpha: float, beta: int)
BILATERAL_FILTEROpenCV Bilateral filter(kernel_size: int)
FPSShow the FPS(flip: bool, scale: float, color: list)

 

Demo

OriginalProcessed
webcam originalwebcam processed

Download details:

Author: esgario
Source code: https://github.com/esgario/webcam-effects
License: MIT license

#opencv #python

Verda  Conroy

Verda Conroy

1591743681

Create a Virtual Pen and Eraser with Python OpenCV - Genial Code

Learn Free how to create a virtual pen and eraser with python and OpenCV with source code and complete guide. This entire application is built fundamentally on contour detection. It can be thought of as something like closed color curves on compromises that have the same color or intensity, it’s like a blob. In this project we use color masking to get the binary mask of our target color pen, then we use the counter detection to find the location of this pen and the contour to find it.

#python #create virtual pen and eraser with opencv #create virtual pen and eraser with python opencv #programming #opencv #python opencv

Virtual Sports Betting Software Development | Virtual Sports Betting Solutions

Mobiweb Technologies offers extensive Virtual Sports Betting Software solutions that includes a variety of sports like Football, Horse racing, Golf, Tennis etc. on which bettors can place wager. Team focuses on realistic animation creation that enhances the user-experience. This kind of special feature attracts fans from different regions and brings a large amount of betting options. With a dedicated team of sports betting software developers, it is possible for us to design customized and engaging betting softwares, the only difference from real-betting is that users can bet online at any time by just one click.

#virtual sports betting software #virtual sports betting app development #virtual sports betting app developers #virtual sports betting software developers #virtual sports betting website developers

50+ Useful DevOps Tools

The article comprises both very well established tools for those who are new to the DevOps methodology.

What Is DevOps?

The DevOps methodology, a software and team management approach defined by the portmanteau of Development and Operations, was first coined in 2009 and has since become a buzzword concept in the IT field.

DevOps has come to mean many things to each individual who uses the term as DevOps is not a singularly defined standard, software, or process but more of a culture. Gartner defines DevOps as:

“DevOps represents a change in IT culture, focusing on rapid IT service delivery through the adoption of agile, lean practices in the context of a system-oriented approach. DevOps emphasizes people (and culture), and seeks to improve collaboration between operations and development teams. DevOps implementations utilize technology — especially automation tools that can leverage an increasingly programmable and dynamic infrastructure from a life cycle perspective.”

As you can see from the above definition, DevOps is a multi-faceted approach to the Software Development Life Cycle (SDLC), but its main underlying strength is how it leverages technology and software to streamline this process. So with the right approach to DevOps, notably adopting its philosophies of co-operation and implementing the right tools, your business can increase deployment frequency by a factor of 30 and lead times by a factor of 8000 over traditional methods, according to a CapGemini survey.

The Right Tools for the Job

This list is designed to be as comprehensive as possible. The article comprises both very well established tools for those who are new to the DevOps methodology and those tools that are more recent releases to the market — either way, there is bound to be a tool on here that can be an asset for you and your business. For those who already live and breathe DevOps, we hope you find something that will assist you in your growing enterprise.

With such a litany of tools to choose from, there is no “right” answer to what tools you should adopt. No single tool will cover all your needs and will be deployed across a variety of development and Operational teams, so let’s break down what you need to consider before choosing what tool might work for you.

  • Plan and collaborate: Before you even begin the SDLC, your business needs to have a cohesive idea of what tools they’ll need to implement across your teams. There are even DevOps tools that can assist you with this first crucial step.
  • Build: Here you want tools that create identically provisioned environments. The last you need is to hear “But it works for me on my computer”
  • Automation: This has quickly become a given in DevOps, but automation will always drastically increase production over manual methods.
  • Continuous Integration: Tools need to provide constant and immediate feedback, several times a day but not all integrations are implemented equally, will the tool you select be right for the job?
  • Deployment: Deployments need to be kept predictable, smooth, and reliable with minimal risks, automation will also play a big part in this process.

With all that in mind, I hope this selection of tools will aid you as your business continues to expand into the DevOps lifestyle.

Tools Categories List:

Infrastructure As Code

Continuous Integration and Delivery

Development Automation

Usability Testing

Database and Big Data

Monitoring

Testing

Security

Helpful CLI Tools

Development

Visualization

Infrastructure As Code

#AWSCloudFormation

1. AWS CloudFormation

AWS CloudFormation is an absolute must if you are currently working, or planning to work, in the AWS Cloud. CloudFormation allows you to model your AWS infrastructure and provision all your AWS resources swiftly and easily. All of this is done within a JSON or YAML template file and the service comes with a variety of automation features ensuring your deployments will be predictable, reliable, and manageable.

Link: https://aws.amazon.com/cloudformation/

2. Azure Resource Manager

Azure Resource Manager (ARM) is Microsoft’s answer to an all-encompassing IAC tool. With its ARM templates, described within JSON files, Azure Resource Manager will provision your infrastructure, handle dependencies, and declare multiple resources via a single template.

Link: https://azure.microsoft.com/en-us/features/resource-manager/

#Google Cloud Deployment Manager

3. Google Cloud Deployment Manager

Much like the tools mentioned above, Google Cloud Deployment Manager is Google’s IAC tool for the Google Cloud Platform. This tool utilizes YAML for its config files and JINJA2 or PYTHON for its templates. Some of its notable features are synchronistic deployment and ‘preview’, allowing you an overhead view of changes before they are committed.

Link: https://cloud.google.com/deployment-manager/

4. Terraform

Terraform is brought to you by HashiCorp, the makers of Vault and Nomad. Terraform is vastly different from the above-mentioned tools in that it is not restricted to a specific cloud environment, this comes with increased benefits for tackling complex distributed applications without being tied to a single platform. And much like Google Cloud Deployment Manager, Terraform also has a preview feature.

Link: https://www.terraform.io/

#Chef

5. Chef

Chef is an ideal choice for those who favor CI/CD. At its heart, Chef utilizes self-described recipes, templates, and cookbooks; a collection of ready-made templates. Cookbooks allow for consistent configuration even as your infrastructure rapidly scales. All of this is wrapped up in a beautiful Ruby-based DSL pie.

Link: https://www.chef.io/products/chef-infra/

#Ansible

#tools #devops #devops 2020 #tech tools #tool selection #tool comparison

A Simple HDR Implementation on OpenCV Python

Learn how to create a high dynamic range (HDR) image using Python and OpenCV

HDR images encompass the information of multiple pictures with different exposures. In a scene which the source of light is uneven, a single shot may overexpose certain areas of the image and details will be lost due to elevated brightness. Conversely, this picture may also present underexposed areas which will also lead to information loss.

To create an HDR image you will need:

  1. Take pictures with different exposures. Minimum of 2, generally 3, you can use more than 3 images but it will take a lot of CPU resources.
  2. Align the images. Even if you use a tripod you will need to perform this step (we are talking about pixel level alignment). Not properly aligning your image will lead to artifacts and ‘ghosts’ in your HDR image.
  3. Merge the aligned images into one.
  4. Perform tone mapping on the merged image. In nature the minimum possible brightness is zero but the maximum is not limited to 255, in fact there is no limit to it, it can be infinity. For this reason we need to map the image obtained in the third step to a (0, 255) range. This can be achieved with tone mapping.

#hdr #opencv #computer-vision #python #opencv #opencv python