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Creating a Short Film - 03 Pre-Production

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Creating a Short Film is a 13-part training series that shows the actual struggles and challenges filmmakers have to overcome to get films made. Author Chad Perkins and his team made a short film, The Assurance, and documented the process: from writing and directing to editing and screening the film. This installment covers pre-production—because there are so many preliminary steps that go into a successful film, and they happen long before the cameras start rolling.

Learn how to prepare the assets, such as shooting scripts, storyboards, and shot lists. Discover how to schedule and budget a shoot, and keep costs down while leaving room for the creative decisions that need to be made along the way. Find out how to hire a crew, scout and secure locations for each scene, and prepare props, sets, and wardrobe for actors. Learn what you need to do to keep your people safe, and the things you can prepare ahead of time to make sure production and post-production run smoothly.

There are more filmmaking tips to be had! Make sure to watch the first installment to learn about the background of the project and to get an overview of the role of the producer. Look for the follow-up episodes to learn more about writing, directing, working with actors, editing and visual effects, and everything else that goes into filmmaking.

Topics include:

Turning the script into a shooting script
Working with script breakdown software such as Adobe Story
Creating storyboards and a shot list
Scheduling the shoot
Budgeting the shoot and post-production
Hiring a crew
Preparing sets and costumes
Scouting locations
Creating props
Preparing assets for post-production

Creating a Short Film - 03 Pre-Production

0
0
Creating a Short Film is a 13-part training series that shows the actual struggles and challenges filmmakers have to overcome to get films made. Author Chad Perkins and his team made a short film, The Assurance, and documented the process: from writing and directing to editing and screening the film. This installment covers pre-production—because there are so many preliminary steps that go into a successful film, and they happen long before the cameras start rolling.

Learn how to prepare the assets, such as shooting scripts, storyboards, and shot lists. Discover how to schedule and budget a shoot, and keep costs down while leaving room for the creative decisions that need to be made along the way. Find out how to hire a crew, scout and secure locations for each scene, and prepare props, sets, and wardrobe for actors. Learn what you need to do to keep your people safe, and the things you can prepare ahead of time to make sure production and post-production run smoothly.

There are more filmmaking tips to be had! Make sure to watch the first installment to learn about the background of the project and to get an overview of the role of the producer. Look for the follow-up episodes to learn more about writing, directing, working with actors, editing and visual effects, and everything else that goes into filmmaking.

Topics include:

Turning the script into a shooting script
Working with script breakdown software such as Adobe Story
Creating storyboards and a shot list
Scheduling the shoot
Budgeting the shoot and post-production
Hiring a crew
Preparing sets and costumes
Scouting locations
Creating props
Preparing assets for post-production

Unreal Engine 4 Marketplace - Multiplayer Survival Game Template

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Multiplayer Survival Game Template

This 100% blueprint powered template has everything you need to get your
survival game up and running

Packed to the brim with all the standard survival game mechanics, as
well as some of the more exotic ones, the template is easy to configure,
easy to extend and easy to learn. Mechanics are all modular so you can
drop anything you don't need to save time and processing power.

Built with almost a year of feedback on the singleplayer origins, this
template is now 100% multiplayer ready and optimized for network play.

Including systems to manage hunger, thirst, time of day, temperature
(both body and world), health, oxygen, blood, stamina, power, poison and
more, you will be able to give your players the survival challenge of a
life time! Includes a full extensive graphical inventory with support
for randomized loot spawning, chests, item cooldowns and more.

All blueprint logic is extensively commented and easily laid out for
learning and understanding.

There's never been a better time to jump on board and buy the original
Survival Game Template!

Please note that this system will work in both singleplayer and
multiplayer projects.

Mamoworld iExpressions V2 (AE).

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iExpressions combine the power of After Effects expressions with the convenience of effects or plugins. They allow you to use expressions without writing any code. Instead, each iExpression comes with an interface, as you know it from effects or plugins, where you control everything using adjustable parameters.

The iExpressions library contains more than 125 expressions in eight categories and each of them comes with an easy to use interface.

Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research

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An interesting book (2013). Some may think there are BS points in it, but for some of you it might be an interesting read.

Excerpts:
"To consider the problem of generating motions for a character in a movie, it is important to realize that the motions can be created procedurally, i.e. by designing algorithms that synthesize motion. The animations can be created "by hand" or captured from an actor in a studio. These "pure data" approaches give the highest quality motions, but at substantial cost in time and effort of artists or actors. Moreover, there is little flexibility: If it is discovered that the right motions were not captured in the studio, it is necessary to retrack and capture more. The situation is worse for a video game, where all the motions that might conceivably be needed must be captured. To solve this problem, machine learning techniques can be adopted to promise the best of both worlds: Starting with an amount of captured data, we can procedurally synthesize more data in the style of the original. Moreover, we can constrain the synthetic data, for example, according to the requirements of an artist. For such problems, machine learning offers an attractive set of tools for modeling the patterns of data. These data-driven techniques have gained a steadily increasing presence in graphics research."


"Computer animation is a time-intensive process, and this is true for both 2D and 3D cartoon animation. As a result, there has long been interest in partially automating animation, and indeed, animation has thus far benefited greatly from applications of machine learning. The majority of the computer animation production burden is usually artistic, not scientific or computational. This is due to the fact that computer animation algorithms are eminently reusable, but the data they operate on is often custom-designed and highly stylized. This bottleneck is illustrated by computer-generated movie production in which the human workload is usually more than 80 % artistic (e.g., modeling, texturing, animating, etc.).
There is therefore a need in computer animation for data transformation and modeling techniques that can synthesize and/or generalize data, thereby at least partially alleviating the data bottleneck. Machine learning techniques are proposed to fulfill this need, and they have two functions that are particularly useful to computer graphics: (1) They extract functional information from data, and (2) they synthesize new data based on existing data. Machine learning allows us to leverage existing data in a nondirect and nontrivial manner, which can save both human and computational time. For example, techniques have been developed for generating meshes of novel human bodies given a small set of example meshes. This is done by creating a generative model of the mesh data through regression."


Description
The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations in areas such as virtual reality, video games, animation films, and sport simulations.

Contents
1 Introduction
1.1 Perception
1.2 Overview of Machine Learning Techniques
1.2.1 Manifold Learning
1.2.2 Semi-supervised Learning
1.2.3 Multiview Learning
1.2.4 Learning-based Optimization

1.3 Recent Developments in Computer Animation
1.3.1 Example-Based Motion Reuse
1.3.2 Physically Based Computer Animation
1.3.3 Computer-Assisted Cartoon Animation
1.3.4 Crowd Animation
1.3.5 Facial Animation

2 Modern Machine Learning Techniques
2.1 A Unified Framework for Manifold Learning
2.1.1 Framework Introduction
2.1.2 Various Manifold Learning Algorithm Unifying
2.1.3 Discriminative Locality Alignment
2.2 Spectral Clustering and Graph Cut
2.2.1 Spectral Clustering
2.2.2 Graph Cut Approximation
2.3 Ensemble Manifold Learning
2.3.1 Motivation for EMR
2.3.2 Overview of EMR
2.3.3 Applications of EMR

2.4 Multiple Kernel Learning
2.4.1 A Unified Mulitple Kernel Learning Framework
2.4.2 SVM with Multiple Unweighted-Sum Kernels
2.4.3 QCQP Multiple Kernel Learning

2.5 Multiview Subspace Learning
2.5.1 Approach Overview
2.5.2 Techinique Details
2.5.3 Alternative Optimization Used in PA-MSL
2.6 Multiview Distance Metric Learning
2.6.1 Motivation for MDML
2.6.2 Graph-Based Semi-supervised Learning

2.6.3 Overview of MDML

2.7 Multi-task Learning
2.7.1 Introduction of Structural Learning
2.7.2 Hypothesis Space Selection
2.7.3 Algorithm for Multi-task Learning
2.7.4 Solution by Alternative Optimization

3 Animation Research: A Brief Introduction
3.1 Traditional Animation Production
3.1.1 History of Traditional Animation Production
3.1.2 Procedures of Animation Production
3.1.3 Relationship Between Traditional Animation and Computer Animation

3.2 Computer-Assisted Systems
3.2.1 Computer Animation Techniques

3.3 Cartoon Reuse Systems for Animation Synthesis
3.3.1 Cartoon Texture for Animation Synthesis
3.3.2 Cartoon Motion Reuse
3.3.3 Motion Capture Data Reuse in Cartoon Characters

3.4 Graphical Materials Reuse: More Examples
3.4.1 Video Clips Reuse
3.4.2 Motion Captured Data Reuse by Motion Texture
3.4.3 Motion Capture Data Reuse by Motion Graph

4 Animation Research: Modern Techniques
4.1 Automatic Cartoon Generation with Correspondence Construction
4.1.1 Related Work in Correspondence Construction
4.1.2 Introduction of the Semi-supervised Correspondence Construction
4.1.3 Stroke Correspondence Construction via Stroke Reconstruction Algorithm
4.1.4 Simulation Results

4.2 Cartoon Characters Represented by Multiple Features
4.2.1 Cartoon Character Extraction
4.2.2 Color Histogram
4.2.3 Hausdorff Edge Feature
4.2.4 Motion Feature
4.2.5 Skeleton Feature
4.2.6 Complementary Characteristics of Multiview Features

4.3 Graph-based Cartoon Clips Synthesis
4.3.1 Graph Model Construction
4.3.2 Distance Calculation
4.3.3 Simulation Results

4.4 Retrieval-based Cartoon Clips Synthesis
4.4.1 Constrained Spreading Activation Network
4.4.2 Semi-supervised Multiview Subspace Learning
4.4.3 Simulation Results

https://www.amazon.com/Learning-Techniques-Applications-Animation-Research/dp/1118115147

zov |||

Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research

0
0
An interesting book (2013). Some may think there are BS points in it, but for some of you it might be an interesting read.

Excerpts:
"To consider the problem of generating motions for a character in a movie, it is important to realize that the motions can be created procedurally, i.e. by designing algorithms that synthesize motion. The animations can be created "by hand" or captured from an actor in a studio. These "pure data" approaches give the highest quality motions, but at substantial cost in time and effort of artists or actors. Moreover, there is little flexibility: If it is discovered that the right motions were not captured in the studio, it is necessary to retrack and capture more. The situation is worse for a video game, where all the motions that might conceivably be needed must be captured. To solve this problem, machine learning techniques can be adopted to promise the best of both worlds: Starting with an amount of captured data, we can procedurally synthesize more data in the style of the original. Moreover, we can constrain the synthetic data, for example, according to the requirements of an artist. For such problems, machine learning offers an attractive set of tools for modeling the patterns of data. These data-driven techniques have gained a steadily increasing presence in graphics research."


"Computer animation is a time-intensive process, and this is true for both 2D and 3D cartoon animation. As a result, there has long been interest in partially automating animation, and indeed, animation has thus far benefited greatly from applications of machine learning. The majority of the computer animation production burden is usually artistic, not scientific or computational. This is due to the fact that computer animation algorithms are eminently reusable, but the data they operate on is often custom-designed and highly stylized. This bottleneck is illustrated by computer-generated movie production in which the human workload is usually more than 80 % artistic (e.g., modeling, texturing, animating, etc.).
There is therefore a need in computer animation for data transformation and modeling techniques that can synthesize and/or generalize data, thereby at least partially alleviating the data bottleneck. Machine learning techniques are proposed to fulfill this need, and they have two functions that are particularly useful to computer graphics: (1) They extract functional information from data, and (2) they synthesize new data based on existing data. Machine learning allows us to leverage existing data in a nondirect and nontrivial manner, which can save both human and computational time. For example, techniques have been developed for generating meshes of novel human bodies given a small set of example meshes. This is done by creating a generative model of the mesh data through regression."


Description
The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations in areas such as virtual reality, video games, animation films, and sport simulations.

Contents
1 Introduction
1.1 Perception
1.2 Overview of Machine Learning Techniques
1.2.1 Manifold Learning
1.2.2 Semi-supervised Learning
1.2.3 Multiview Learning
1.2.4 Learning-based Optimization

1.3 Recent Developments in Computer Animation
1.3.1 Example-Based Motion Reuse
1.3.2 Physically Based Computer Animation
1.3.3 Computer-Assisted Cartoon Animation
1.3.4 Crowd Animation
1.3.5 Facial Animation

2 Modern Machine Learning Techniques
2.1 A Unified Framework for Manifold Learning
2.1.1 Framework Introduction
2.1.2 Various Manifold Learning Algorithm Unifying
2.1.3 Discriminative Locality Alignment
2.2 Spectral Clustering and Graph Cut
2.2.1 Spectral Clustering
2.2.2 Graph Cut Approximation
2.3 Ensemble Manifold Learning
2.3.1 Motivation for EMR
2.3.2 Overview of EMR
2.3.3 Applications of EMR

2.4 Multiple Kernel Learning
2.4.1 A Unified Mulitple Kernel Learning Framework
2.4.2 SVM with Multiple Unweighted-Sum Kernels
2.4.3 QCQP Multiple Kernel Learning

2.5 Multiview Subspace Learning
2.5.1 Approach Overview
2.5.2 Techinique Details
2.5.3 Alternative Optimization Used in PA-MSL
2.6 Multiview Distance Metric Learning
2.6.1 Motivation for MDML
2.6.2 Graph-Based Semi-supervised Learning

2.6.3 Overview of MDML

2.7 Multi-task Learning
2.7.1 Introduction of Structural Learning
2.7.2 Hypothesis Space Selection
2.7.3 Algorithm for Multi-task Learning
2.7.4 Solution by Alternative Optimization

3 Animation Research: A Brief Introduction
3.1 Traditional Animation Production
3.1.1 History of Traditional Animation Production
3.1.2 Procedures of Animation Production
3.1.3 Relationship Between Traditional Animation and Computer Animation

3.2 Computer-Assisted Systems
3.2.1 Computer Animation Techniques

3.3 Cartoon Reuse Systems for Animation Synthesis
3.3.1 Cartoon Texture for Animation Synthesis
3.3.2 Cartoon Motion Reuse
3.3.3 Motion Capture Data Reuse in Cartoon Characters

3.4 Graphical Materials Reuse: More Examples
3.4.1 Video Clips Reuse
3.4.2 Motion Captured Data Reuse by Motion Texture
3.4.3 Motion Capture Data Reuse by Motion Graph

4 Animation Research: Modern Techniques
4.1 Automatic Cartoon Generation with Correspondence Construction
4.1.1 Related Work in Correspondence Construction
4.1.2 Introduction of the Semi-supervised Correspondence Construction
4.1.3 Stroke Correspondence Construction via Stroke Reconstruction Algorithm
4.1.4 Simulation Results

4.2 Cartoon Characters Represented by Multiple Features
4.2.1 Cartoon Character Extraction
4.2.2 Color Histogram
4.2.3 Hausdorff Edge Feature
4.2.4 Motion Feature
4.2.5 Skeleton Feature
4.2.6 Complementary Characteristics of Multiview Features

4.3 Graph-based Cartoon Clips Synthesis
4.3.1 Graph Model Construction
4.3.2 Distance Calculation
4.3.3 Simulation Results

4.4 Retrieval-based Cartoon Clips Synthesis
4.4.1 Constrained Spreading Activation Network
4.4.2 Semi-supervised Multiview Subspace Learning
4.4.3 Simulation Results

https://www.amazon.com/Learning-Techniques-Applications-Animation-Research/dp/1118115147

zov |||

Lynda - 2D Animation: Animate Monsters & Aliens

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Animating a convincing Dracula or zombie involves many of the classic principles of animation; however, in order to properly spook your audience, you'll often want to make your creatures move in creepy or unnatural ways. In this course, Dermot O'Connor shares 2D animation techniques for making monsters, aliens, and other supernatural subjects come to life. Dermot explains how to deal with muscular creatures, animate jerky creatures, and make eerily smooth movements. He illustrates how to apply each technique by drawing familiar monsters like ghosts, werewolves, vampires, and more.

Topics include:

Animating mummies, werewolves, and trolls
Animating jerky movements of zombies and elves
Animating smooth movements

http://lynda.com/tutorial/501128

The Legend of Korra Air The Art of the Animated [Artbook]

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Return to the world of Avatar!

This handsome hardcover contains hundreds of pieces of never-before-seen artwork created during the development of Season 1 of The Legend of Korra. With captions from Mike and Bryan throughout, this is an intimate look inside the creative process that brought the mystical world of bending and a new generation of heroes to life!

* Captions bycreators Michael Dante DiMartino and Bryan Konietzko!

* Follow-up to smash hit animated series Avatar: The Last Airbender!

* Never-before-seen artwork!

https://www.amazon.com/Legend-Korra-Air-Art-Animated/dp/1616551682

Phlearn Pro - Light my fire

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This Phlearn PRO Tutorial shows you some of the tricks for using Photoshop to make the riskiest shoots less dangerous so you can create more impactful images. Learn about advanced color modes, compositing images, dodging, burning, selective blurs and more.
Creating an image where the model has sparks blowing directly at her face might seem incredibly dangerous. Probably because it is. But with proper planning and the Photoshop skills you will learn in this tutorial, you can make your next risky shoot safe for everyone. Not to mention much more impactful.

Adobe CC master 2015

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Full Adobe CC 2015 Plus crack

DELUTS Canon DSLR camera profiles and Lut looks (porcini)

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DELUTS Canon DSLR camera profiles and Lut looks.
Version 1.1 Oct/16


There are several LOG type profiles for the Canon DSLR cameras and I first made one 7 years ago. Things have moved on since then and LOG camera profiles have really moved on.

I have developed 2 main profiles for the Canon DSLR and around 120 Lut looks across the camera profiles to download.

• CLOG Neutral (v1.0 & v2.0)

• CLOG 3 Samples https://vimeo.com/182394450/0d109c1bcd

CLOG Neutral comes in two options, one with a highlight roll off knee that stays below clipping (v1) and one where its a little more pronounced (v2).

CLOG 3 gives you a more Canon style modern LOG image.

There are also some additional camera profiles (found in the Additional Profiles folder) that help you shoot using colour tones of the standard camera profiles like Faithful, Fine Detail (depending on camera), Landscape, Neutral, Portrait and Standard. There is also a couple of more defined Monotone profiles.

Both the main profiles have corresponding LUT looks and for many options. All profiles designed around Canon captured imagery shot over the last 3 years.

There is also a separate folder ‘DELUTS Neutral Film Looks’ that contains LUT looks allowing you to over grade existing Standard shot profiles in several film tones.

There are around 120 Lut looks across the camera profiles to download.

How to Bring out Colors & Details in Your Photos

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In this video tutorial we will use advanced color grading techniques to create a tone mapping effect without the use of any plugins or 3rd party software, we'll only be using Photoshop and what comes with it. We will start out with a photo taken with the aid of an off-the-camera flash and turn it into some sort of "reality show" poster ad. Taking a photo while using an additional fill-light or reflectors helpl us retain a lot of details in the shadows and highlights which make it easier in post-production to really push the color grading.

http://www.learnphotoediting.net/photoshop-tutorial-girls.html

DELUTS Canon DSLR LOG & LOOKS (by porcini)

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DELUTS Canon DSLR LOG & LOOKS
DELUTS Canon DSLR camera profiles and Lut looks.
Version 1.1 Oct/16


There are several LOG type profiles for the Canon DSLR cameras and I first made one 7 years ago. Things have moved on since then and LOG camera profiles have really moved on.

I have developed 2 main profiles for the Canon DSLR and around 120 Lut looks across the camera profiles to download.

• CLOG Neutral (v1.0 & v2.0)

• CLOG 3 Samples https://vimeo.com/182394450/0d109c1bcd

CLOG Neutral comes in two options, one with a highlight roll off knee that stays below clipping (v1) and one where its a little more pronounced (v2).

CLOG 3 gives you a more Canon style modern LOG image.

There are also some additional camera profiles (found in the Additional Profiles folder) that help you shoot using colour tones of the standard camera profiles like Faithful, Fine Detail (depending on camera), Landscape, Neutral, Portrait and Standard. There is also a couple of more defined Monotone profiles.

Both the main profiles have corresponding LUT looks and for many options. All profiles designed around Canon captured imagery shot over the last 3 years.

There is also a separate folder ‘DELUTS Neutral Film Looks’ that contains LUT looks allowing you to over grade existing Standard shot profiles in several film tones.

There are around 120 Lut looks across the camera profiles to download.

DELUTS Canon DSLR LOG & LOOKS (by porcini)

0
0
DELUTS Canon DSLR LOG & LOOKS
DELUTS Canon DSLR camera profiles and Lut looks.
Version 1.1 Oct/16


There are several LOG type profiles for the Canon DSLR cameras and I first made one 7 years ago. Things have moved on since then and LOG camera profiles have really moved on.

I have developed 2 main profiles for the Canon DSLR and around 120 Lut looks across the camera profiles to download.

• CLOG Neutral (v1.0 & v2.0)

• CLOG 3 Samples https://vimeo.com/182394450/0d109c1bcd

CLOG Neutral comes in two options, one with a highlight roll off knee that stays below clipping (v1) and one where its a little more pronounced (v2).

CLOG 3 gives you a more Canon style modern LOG image.

There are also some additional camera profiles (found in the Additional Profiles folder) that help you shoot using colour tones of the standard camera profiles like Faithful, Fine Detail (depending on camera), Landscape, Neutral, Portrait and Standard. There is also a couple of more defined Monotone profiles.

Both the main profiles have corresponding LUT looks and for many options. All profiles designed around Canon captured imagery shot over the last 3 years.

There is also a separate folder ‘DELUTS Neutral Film Looks’ that contains LUT looks allowing you to over grade existing Standard shot profiles in several film tones.

There are around 120 Lut looks across the camera profiles to download.

Cover Action Pro 3.0

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http://www.coveractionpro.com/

Make Your Product Shots
POP and CONVERT
with 3D Mockups You Won’t
Find Anywhere Else

The Ultimate Marketing Toolkit for Adobe Photoshop Just Got Better

Now Anyone Can Make Dazzling 3D Product Shots With Ease...
Even if you have little or no experience with Photoshop!

Cover Action Pro 3.0

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0
Make Your Product Shots
POP and CONVERT
with 3D Mockups You Won’t
Find Anywhere Else

The Ultimate Marketing Toolkit for Adobe Photoshop Just Got Better

Now Anyone Can Make Dazzling 3D Product Shots With Ease...

http://www.coveractionpro.com/

Pluralsight – Onshape Drawing Fundamentals

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After modeling a part in Onshape, the next step of taking the part to production is the drawing phase. In this course, Onshape Drawing Fundamentals, you'll learn the fundamentals necessary to create a 2D Onshape drawing from a 3D model. First, you'll cover how to create a drawing and how to choose a template. Next, you'll explore adding views and organizing the layout of the drawing. Then, you'll explore dimensioning and annotating. Finally, you'll learn how to populate the title block, exporting, and sharing the drawing. By the end of this course, you'll be ready to create complete production drawings of your own, to accompany your Onshape geometry.

Software required: Onshape.

https://www.pluralsight.com/courses/onshape-drawing-fundamentals

Tool development and Plugin in 3ds

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best for tool development in 3ds software..

MAGIX Video Pro X8 v15.0.3.138 x64- Full

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MAGIX Video Pro X8 15.0.3.138 (x64)

MAGIX Video Pro X is the perfect editing software for intuitive and powerful video production. This multi-award-winning video editing suite is geared towards the unique requirements of ambitious and professional users, and offers an unrivaled range of powerful post-production tools.

Professional video editing
Access detailed editing options, outstanding performance and cinematic effects in top image and sound quality.

Video production
Choose from a wide range of tools to perfect your footage, such as GPU-optimized video effects, precise measurement instruments and multicam editing.

Audio editing
A real-time audio mixer, keyframe control and sample-precise editor as well as a ton of broadcast-quality effects provide everything you need for optimizing sound.

Extras
Access all the extras — such as plug-in package NewBlue Looks, which includes impressive color filters and effect transitions, or proDAD Mercalli V2 for perfect image stabilization.

The most important features:
- Professional format support (ProRes, AVC-Intra etc.)
- Scalable proxy editing for smooth editing of 4K videos
- Primary and secondary 3-way color correction
- Multicam editing on up to nine tracks simultaneously
- Comprehensive action cam support
- Surround sound editing in broadcast quality
- Hardware-based decoding for HD and UHD (H.264, H.265)
- NewBlue Looks: Top quality color filters for unforgettable films

What's New in MAGIX Video Pro X8:
Shot match
Transfer the visual characteristics of one video to another. The program matches the colors and tonal values of two separate videos fully automatically.

360 degree camera editing
Video Pro X provides a wide range of options for editing footage from the latest 360 degree cameras.

4K/Section animation
Use 4K material to create sections and image details in lower-resolution footage.

NewBlue Looks Film Color:
- Modify color and light to give your film a classic look.
- Color Fixer Pro: Adjust the color balance, saturation and brightness of images.
- Gradient Tint: Intensify image colors using a wide range of filters.
- Spotlight: Set an area of an image under a spotlight.
- Glow Pro: Create a warm light by adding highlights to the original image.

Advanced exposure features
Detailed color and tonal value correction enables you to edit luminance and individual RGB channels precisely.

Modern title templates
The over 250 brand new title templates have been completely redesigned and feature a modern look and structure.

OpenFX support
You can now use OpenFX standard plug-ins as a video effect from directly within the Mediapool.

HEVC/H.265 decoding
Video Pro X is the world's first video editing program to support Intel HEVC/H.265 with ultra-fast hardware acceleration.

GameGuru.v1.132-NEWiSO

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Have you always dreamed of making a game but have no wish to
delve into the mystical realms of programming or 3D art creation?

GameGuru allows you to fulfil your dreams in a non-technical,
fun and extremely easy to share way. Create games that you can
play and enjoy with others in minutes.
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