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How to easily face swap on images using Fooocus

image face swapping made easy with Fooocus

If you would like to know how to quickly and easily swap the face of one model to another in an image or advertising campaign. You will be pleased to know the world of digital imagery is taking an impressive leap forward with the advent of face swapping technology such as Fooocus. This sophisticated software is blending the lines between what’s real and what’s computer-generated, allowing users to insert AI-created faces into actual photographs with stunning accuracy.

Leading the charge in this field is the seamless integration of faces, either from a collection of AI-generated options or from your own uploaded images. To achieve the best possible outcome when using real-life photos, it’s essential to start with high-resolution and well-lit pictures. These high-quality images help to avoid common problems that can arise during the face swapping process, such as mismatched textures or visible seams.

Image face swapping made easy with Fooocus

The key to a successful face swap lies in the careful adjustment of the software’s settings. Paying close attention to the ‘stop at’ and ‘weight’ options is crucial, as they control how much of the swap is applied and how the original and new faces blend together. By experimenting with these settings, users can find the perfect balance that results in a natural-looking integration of the new face into the existing photo.

Here are some other articles you may find of interest on the subject of AI art generators :

To refine the swapped image further, the use of control nets, like canny, is indispensable. These tools help adjust the pose and the outlines of the face, ensuring that the new face fits perfectly within the context of the base photo. This attention to detail is what maintains the natural look of the image, matching the edges and contours to make the swap believable.

After the initial swap, some post-swap touch-ups might be necessary to achieve a flawless result. Adjusting the lighting, contrast, or color balance can help the new face blend in more convincingly. The goal is to create an image that not only looks authentic but also retains the essence of the original photo.

Using multiple reference images can greatly enhance the quality of the final product. By providing the software with various angles and expressions of the face, the AI can develop a more detailed understanding, which in turn improves the accuracy and realism of the swapped face.

When choosing the base photo and the face to swap, it’s important to consider the compatibility of factors such as lighting, resolution, and perspective. This careful selection is what makes the difference between a face swap that looks artificial and one that’s indistinguishable from reality.

It’s also vital to be aware of the potential biases present in AI image generation. These biases can affect how accurately the likeness is reproduced, especially when dealing with a diverse range of faces. Being conscious of and addressing these biases is crucial for ensuring that the representations are fair and accurate.

The Fooocus face swapping software is a fascinating blend of artificial intelligence and real-world imagery, offering users the ability to alter images in ways that are both creative and captivating. By following these guidelines, you can refine your settings, perfect your images, and tackle biases to produce exceptional face-swapped photos. Whether you’re looking to entertain or to enhance your professional toolkit, becoming adept at face swapping opens up a world of imaginative possibilities.

Image Credit : Monzon Media

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Runway AI makes AI video animations even easier and partners with Getty Images

Runway AI makes AI video animations even easier and partners with Getty Images

AI is swiftly altering the video production landscape, empowering creators to animate and optimize content in ways previously unimaginable. This amazing new technology is enabling those with limited technical skills to produce intricate animations and even full-length films and we are only at the start of the very beginning of the journey.

We’re witnessing a wave of innovative features and collaborations that are reshaping the animation industry, making it an exciting time for content creators and audiences alike. At the forefront of this shift is Runway AI , which has introduced a motion brush tool that animates parts of an image with remarkable precision.

This new AI animation tool, along with new motion and camera angle options, is streamlining the process of creating vibrant videos. Runway’s collaboration with Getty Images enhances this capability by allowing users to train custom AI models tailored to their video projects.

Runway AI partners with Getty Images

Runway AI is collaborating with Getty Images to introduce a novel video model tailored for enterprise clients. This initiative responds to the increasing demand for premium, personalized content among businesses. By integrating Runway’s capabilities with the extensive, fully licensed creative content library of Getty Images, the model offers an innovative solution for crafting and enlivening stories and concepts through video. This approach ensures readiness and safety for enterprise use.

Runway is joining forces with Getty Images to introduce an innovative video model designed for enterprise clients. This new initiative is aimed at meeting the growing demands of companies for top-tier, tailor-made content. The model leverages Runway’s technology in tandem with the extensive, fully licensed creative content library from Getty Images. It offers a fresh approach to realizing ideas and narratives through video, ensuring that the end product is both enterprise-ready and secure.

Runway Getty Images Model (RGM)

Runway for Enterprise: The collaboration brings forth the Runway <> Getty Images Model (RGM), which serves as a foundational model that companies can customize to generate video content. Runway’s enterprise clients can refine the RGM using their unique datasets. This adaptability makes the model particularly valuable for a variety of sectors, including Hollywood studios, advertising agencies, media houses, broadcasting, and more. It empowers these industries to boost their creative potential, paving the way for novel content creation workflows. This model facilitates the production of engaging experiences that resonate with the distinct style, brand identity, and audience of each enterprise.

Cristóbal Valenzuela, CEO and co-founder of Runway, commented on the partnership: “Our collaboration with Getty Images elevates our mission to equip creators with next-gen AI tools to a higher level of creative freedom and personalization. This partnership will unveil new commercial opportunities and video products for companies, and we eagerly anticipate the outcomes.”

Grant Farhall, Chief Product Officer at Getty Images, shared his enthusiasm: “We’re thrilled to collaborate with Runway to enhance enterprise creativity and AI-driven exploration responsibly. Merging human talent and advanced technology opens up immense possibilities, especially in the realm of video creation.”

Together, Runway and Getty Images are set to redefine the limits of AI and video generation, simplifying the process for enterprises to create professional, compelling, and brand-aligned content. The RGM will soon be available for commercial use in the upcoming months.

Here are some other articles you may find of interest on the subject of Runway AI and video animations

Source : RAI

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Create amazing “Make It More” images with DallE 3 & Midjourney

Create amazing Make It More images combing DallE 3 and Midjourney

The emergence of a new trend that’s captivating the internet known as “Make it More”. Where the boundaries of AI image generation are pushed to create visuals that are as absurd as they are entertaining. It’s a digital playground where the mundane becomes extraordinary, and the results are as unpredictable as they are delightful.

Imagine taking a simple image—a cat, for instance—and asking an AI to enhance its features. But the fun doesn’t stop there. With each subsequent request, the AI takes the cat’s cuteness to new, almost unbelievable levels. This is made possible by the AI’s advanced understanding of context, where it remembers your previous prompts and knows that you’re seeking an increasingly adorable cat. This contextual memory is the key to creating a series of images that become progressively more whimsical.

Make It More images made easy

learn how to combine the powers of both OpenAI’s DallE 3 and Midjourney AI art generator is to create some amazing Make It More images. Transforming mundane everyday images or objects into something amazing.

The excitement grows as you use more imaginative adjectives to challenge the AI. You might say, “make it the cutest cat in the cosmos,” and the AI will respond with images that are as humorous as they are imaginative, perhaps showing a cat with eyes that sparkle like stars or fur that seems to be made of clouds.

Another AI tool, MidJourney, adds a new layer to this creative process. It allows users to take the initial image and explore various outrageous possibilities. This feature encourages users to steer the AI’s output into even more creative realms, resulting in a diverse array of fantastical images.

The “Make It More” trend has found a natural home on social media, where these AI-generated images are shared and celebrated. It’s a space where users compete to showcase their creativity and humor, leveraging the AI’s capabilities to produce images that are as shareable as they are surprising. This isn’t just a display of AI’s potential; it’s a celebration of human ingenuity in coming up with the prompts that guide the AI.

At its core, the “Make It More” trend is a playful exploration of AI’s creative potential. By using comparative adjectives and understanding the AI’s grasp of conversational context, users can generate a whimsical variety of images that push the limits of the imagination. Whether you’re using ChatGPT DallE 3, MidJourney, or another AI platform, the possibilities are limited only by your own creativity. This is an invitation to share your most imaginative and outlandish AI-generated images and to discover just how far you can stretch a simple concept.

Here are some other articles you may find of interest on the subject of Midjourney styles and creating amazing artwork using DallE 3 and other AI generators

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How to use ChatGPT Vision to read & understand images in automations

How to use ChatGPT Vision to read and understand images in Zapier automations

Have you ever wanted to create an automation capable of reading and understanding images and ultimately taking actions upon what it sees to help improve your productivity or business workflow? Perhaps upload a photo to your Google Drive, a system instantly kicks into gear, analyzing every detail of that image and setting off a chain of actions based on what it finds. This isn’t a glimpse into a distant future; it’s a reality you can create today using OpenAI’s ChatGPT Vision image analysis technology and Zapier’s automation platform. This guide will show you how to combine these powerful tools to streamline your workflow and make your digital life infinitely more efficient.

Thanks to the launch of ChatGPT Vision you can now create AI automations that can read and understanding images and deciding autonomously. To begin, you’ll need to get familiar with OpenAI’s API, which is a sophisticated tool that can dissect the contents of an image, spot patterns, and generate useful metadata. To harness this power, you’ll integrate the OpenAI API with Zapier. Start by securing an OpenAI account and obtaining your API key. Then, you’ll create a new “Zap,” which is what Zapier calls an automated workflow. This Zap will connect your Google Drive to OpenAI, setting the stage for the magic to happen.

Creating automations with ChatGPT Vision

The next step is to set up a trigger in Zapier. This trigger prompts the system to spring into action whenever you upload a new image to a specific Google Drive folder. To do this, you’ll select Google Drive as the trigger app and choose the “New File in Folder” option. You’ll need to pinpoint the exact folder you want to monitor and make sure Zapier has the permissions to access it.

Other articles we have written that you may find of interest on the subject of  OpenAI’s new AI vision model  which is available in ChatGPT  and through its API system :

Once your trigger is in place, you’ll need to configure the action that calls upon OpenAI’s API. When the conditions for your trigger are met—meaning a new image has been uploaded—Zapier will send a request to the API. This request will include your API key and a data payload that contains the image URL from Google Drive, all formatted according to OpenAI’s specifications.

Supported image formats

It’s important to note that OpenAI’s API can work with several image formats, including PNG, JPEG, GIF, and WEBP. You’ll want to ensure that the images you’re uploading to Google Drive are in one of these formats. If they’re not, you’ll have to convert them before they can be analyzed. For OpenAI’s API to examine your images, the URLs must be properly structured. They need to be accessible to the API, which might mean changing the sharing settings in Google Drive to allow access. Additionally, the URLs must be encoded in a way that the API can recognize.

Permissions are key in this automation process. You’ll need to adjust your Google Drive sharing options to enable OpenAI’s API to retrieve and analyze the images. This might involve setting the images to “public” or sharing them with a service account that’s connected to the API. If you find that your images are not in a compatible format, you’ll need to convert them. This can be done manually, or you can set up an automated process within Zapier, which can use other apps or its own tools to get the images ready for OpenAI’s API.

Automating the process with Zapier

Testing your setup is an essential step. You should upload various images to your designated Google Drive folder and observe the Zap in action. This will trigger the analysis process. Pay close attention to the output from OpenAI’s API to ensure that the system is working as expected and that the analysis meets your needs. Maintaining the quality of your API-driven automation is crucial. You should regularly test your Zaps and keep an eye on the performance of the OpenAI API to ensure that the image analysis remains accurate and reliable. Be aware of any updates to the API or changes in the supported formats, and adjust your automation as needed.

By following this guide, you can create an advanced system that leverages the strengths of Google Drive’s image management, OpenAI’s analytical capabilities, and Zapier’s automation efficiency. Whether you’re using it for work or personal projects, automating image analysis with OpenAI through Zapier can free up your time and provide valuable insights. This allows you to focus on more strategic tasks and creative endeavors. With this setup, you’re not just optimizing your workflow; you’re unlocking a new level of productivity and insight that can transform the way you handle digital images.

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Invisible watermarking for AI generated images – Stability AI

Stable Fine Tuning for AI models enters private preview

Stability AI has this week unveiled a number of new advances in artificial intelligence including its new Stable 3D AI technology that allows users to create 3D models from text prompts. As well as its handy Sky Replacer AI tool perfect for real estate agents looking to transform photographs with gloomy skies into beautiful clear blue vistas.

In another announcement Stable Fine Tuning offers businesses and developers the ability to fine-tune pictures, objects, and styles at record speed, all with the ease of a turnkey integration for their applications. Stable FineTuning AI technology is currently in private preview and has been specifically designed to offer enterprises and developers an easy and quick way to fine-tune a wide variety of digital assets. For more information jump over to the Stability AI website and contact form.

Watermarking AI images

Stable FineTuning gives users the ability to customize pictures into modern digital art, including the addition of stunning landscapes, avatars, and other imaginative creations. This is valuable for employees in the entertainment, gaming, advertising, and marketing industries, which often rely on visuals for sales and brand-building, providing them with a more personalized customer experience.

In addition to its core functionality, Stable FineTuning’s private preview comes with added features that enhance the overall user experience. One of these is the integration of Content Credentials and invisible watermarking for images generated via their API. This feature underscores Stability AI’s commitment to transparency in AI-generated content. It ensures that users can confidently use the tool without worrying about copyright issues or authenticity of the AI-generated content.

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Invisible watermarking in AI-generated images offers a multifaceted approach to solving problems related to intellectual property, data security, and content traceability. One of the most immediate benefits is the protection of intellectual property rights.

Intellectual Property Rights

An invisible watermark can act as a digital signature that certifies the origin of the image. This is particularly valuable for artists or organizations that produce unique visual content, as it provides a way to prove ownership. Additionally, the watermark can contain metadata about the licensing terms, making it easier to manage how the image is used and shared.

  • Ownership Proof: The invisible watermark can serve as a digital signature, certifying the origin of the image. This is crucial for artists and organizations that generate unique visual content.
  • Licensing: The watermark can hold metadata about how the image can be used, simplifying licensing arrangements.

Data Security

In terms of data security, invisible watermarking serves as a tool for both tamper detection and unauthorized use prevention. Some watermarks are designed to be fragile, so any alterations like cropping or rotation will disrupt the watermark, thereby flagging the image as tampered. This feature can be critical in legal or secure environments where the integrity of the image is paramount. Moreover, the watermark can be configured to trigger alerts if the image is used in unauthorized settings, providing an additional layer of security against data leaks or misuse.

  • Tamper Detection: Invisible watermarks can be designed to be fragile. Any alteration to the image (like cropping, rotation, etc.) can disrupt the watermark, indicating that the image has been tampered with.
  • Unauthorized Use: A watermark can trigger alarms or notifications if the image appears in an unauthorized setting, aiding in immediate action against data leaks or misuse.

Content Traceability

Content traceability is another area where invisible watermarking shines. It allows for source tracking and the creation of audit trails. In workflows involving multiple iterations or versions of an image, being able to trace an image back to its original version or source can be invaluable. Similarly, for regulatory compliance in certain industries, an invisible watermark can serve as an effective way to log when, where, and by whom an image was accessed or modified.

  • Source Tracking: In scenarios involving multiple iterations or versions of an image, watermarks can help trace the image back to its original version or source.
  • Audit Trails: For regulatory compliance, an invisible watermark can serve as a log entry, verifying when, where, and by whom the image was accessed or modified.

User Experience

User experience is also enhanced through invisible watermarking. Because the watermark is invisible, it does not interfere with the visual quality of the image. This is especially important in professional or artistic settings where the integrity and appearance of the image are critical. Finally, in the context of machine-to-machine communication, invisible watermarks can embed additional metadata that can be read by other AI systems. This facilitates seamless interactions between different systems without requiring human intervention.

  • Non-Intrusiveness: Since the watermark is invisible, it does not interfere with the viewer’s experience of the image, which is particularly important in professional settings where image integrity is crucial.

Machine-to-Machine Communication:

  • Metadata Embedding: Invisible watermarks can hold additional data that can be read by other AI systems, helping in seamless machine-to-machine interactions without human intervention.

Adding hidden watermarks to images made by AI has many advantages. It helps protect who owns the image, makes the image more secure, lets you track where the image goes, makes it better for users to look at, and even helps different computer systems work together.

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New Google features to verify online images and sources

New Google features to verify online images and sources

In an era where misinformation and disinformation are rife, verifying the authenticity of online images and sources has become increasingly crucial. Google has this week launched three new features to tackle this issue. These features include the ‘About this image‘ tool, the expansion of the Fact Check Explorer, and the introduction of the Search Generative Experience (SGE). Each feature is designed to provide users with more context and information about the images and sources they encounter online, ultimately promoting a more reliable and trustworthy digital environment.

About this image

The first feature, About this image, is a tool designed to provide users with comprehensive information about an image’s history, usage, and metadata. This tool, now available to English language users globally, gives indications of AI generation or enhancement, helping users discern whether an image has been altered or manipulated in any way. To access this feature, users can click on the three dots on an image in the Google Images results or click “more about this page” in the About this result tool on search results. This tool effectively provides a backstory for each image, allowing users to better understand its origins and context.

Fact Check Explorer

The second feature Google has introduced is the expansion of the Fact Check Explorer. This tool allows users to upload or copy the URL of an image to see if it has been featured in an existing fact check. It also provides an overview of the different contexts associated with the image and their evolution over time, giving users a more comprehensive understanding of the image’s credibility. In addition to this, Google is introducing a beta of Image Search functionality in FactCheck Claim Search API, which will allow approved journalists and fact checkers to search the fact-check image corpus on Fact Check Explorer via an API and integrate the knowledge into their own solutions. This extension of the Fact Check Explorer not only benefits individual users but also empowers journalists and fact-checkers in their mission to combat misinformation.

Search Generative Experience (SGE)

The third feature, the Search Generative Experience (SGE), uses generative AI to provide descriptions of some sources, supported by information on high-quality sites that talk about that website. These descriptions will appear in the “more about this page” section of About this result for some sources where there isn’t an existing overview from Wikipedia or the Google Knowledge Graph. This innovative use of AI technology helps fill in the gaps where traditional information sources may be lacking, providing users with a more complete picture of the source’s credibility.

Other articles we have written that you may find of interest on the subject of Search Generative Experience :

Misinformation and disinformation

These features are part of Google’s ongoing efforts to help users verify the authenticity and reliability of online images and sources. This initiative comes in response to a 2023 study by the Poynter Institute’s MediaWise, which found that 70% of respondents were not confident in their ability to tell when online images are authentic and reliable. By providing users with more tools to verify the credibility of online images and sources, Google is taking a significant step towards creating a more trustworthy digital environment.

These new features from Google represent a significant stride in the fight against misinformation and disinformation online. By giving users the tools to verify the authenticity of online images and sources, Google is fostering a more informed and discerning digital community. It’s a reminder that as we navigate the digital landscape, it’s not just about consuming information—it’s also about understanding its origins, context, and credibility.

Verify online images and sources

In today’s digital world, information travels faster than ever before, but not all of it is accurate or trustworthy. That’s why verifying online images and sources is so important. Think of it like this: when you’re doing research for a project or trying to understand a current event, you want to make sure you’re getting the whole picture, not just someone’s twisted version of it. Incorrect or misleading information can lead to misunderstandings, spread false rumors, and even have serious consequences in some situations.

For example, let’s say you come across a viral image on social media that claims to depict a major event like a protest or a natural disaster. If that image is doctored or taken out of context, it could dramatically alter your perception of the event. You might end up forming an opinion based on false premises, and that’s a problem. Tools that help verify the authenticity of images and sources enable you to separate fact from fiction, giving you a clearer understanding of the world around you.

Additionally, the credibility of sources is key when it comes to academic work. If you’re writing an essay or giving a presentation, you want to base your arguments on reliable information. Using verified sources adds weight to your points and makes your work more persuasive. And beyond the classroom, being able to discern reliable information from unreliable sources is a critical skill for participating in civic matters, like voting or community organizing. Overall, verifying online images and sources empowers you to make more informed decisions and be a more responsible digital citizen.

Image Credit : Google

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Convert 2D images into 3D models you can use in Blender

Convert flat AI images into 3D models you can use in Blender

If your creative workflow requires you to build 3D models you might be interested in a new AI tool currently in its early stages of development. Harnessing the power of AI and machine learning you can now  transform simple flat 2D images into 3D models. Enabling you to take any images you may have created with AI image generators such as Midjourney, Stable Diffusion or even the new DallE 3 into 3D models. That you can then take into 3D modelling software such as Blender.

But before you start you have to remember that this machine learning AI tool is still in early development and doesn’t completely transform any flat 2D image into a fantastic 3D model ready to take to production. However in its latest version it is still capable of creating 3D models from clean and simple flat images you can see a few examples here. Although a more complex 3D images it currently does struggle. Although more complicated 3D images, that may not have worked perfectly will still be capable of being modified further in Blender perhaps give you a starting point for scale and at least a 3D model that you can then manipulate further.

The application is called the DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation which is quite a mouthful. It is available to use for free over on the Hugging Face website and the online application has been built using Gradio. If you have not come across Gradio, it has been specifically designed to provide an easy way to build and demonstrate your machine learning models, enabling you to incorporate a user-friendly web interface so that anyone can use it. Check out the demonstration video below to learn more about its capabilities and limitations.

Converting 2D images into 3D models using AI

DreamGaussian is a 3D content generation framework AI tool has been designed to be user-friendly, requiring users to simply drag and drop an image and click Generate 3D to start the process rolling.

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Transforming 2D images into 3D models

The transition from 2D images to manipulable 3D models would represent a quantum leap in the workflow for 3D designers, modelers, and production teams. In traditional 3D modeling, the process often begins with a concept sketch or a 2D image. Designers then have to manually interpret these flat visuals and reconstruct them in a 3D environment. This involves a significant amount of time and expertise to ensure that the 3D model accurately represents the original concept. The manual process is not only labor-intensive but can also introduce errors or inconsistencies that may require further revisions.

With the capability to automatically convert 2D images into 3D models, you essentially remove a large chunk of the manual labor involved. Imagine simply importing a 2D sketch into software like Blender and having it automatically converted into a 3D model that’s ready for manipulation. This would dramatically accelerate the initial stages of design and modeling, allowing professionals to focus more on refining and enhancing the model rather than constructing it from scratch. It would also make the entire design process more accessible to those who may be skilled in concept creation but not necessarily experts in 3D modeling software.

Furthermore, this advancement could streamline collaboration across different teams in a production pipeline. For instance, concept artists, modelers, and animators could work more cohesively, as they would all be dealing with the same automatically-generated base model. This ensures that everyone is on the same page from the get-go, thereby reducing misunderstandings and back-and-forths. In industries like film, gaming, and virtual reality, where time is often of the essence, such efficiencies could translate into significant cost savings and quicker time-to-market for products.

Despite these limitations, the potential of DreamGaussian is undeniable. The tool could potentially be a fantastic AI service to create 3D models from images. This could open up an entirely new avenue for digital artists and graphic designers, providing them with a new way to improve their workflows. Obviously the machine learning tool requires more work, yet provides a fantastic glimpse at what we can expect in the future for the creation of 3D models. Now that 2D images so easy to create converting them to 3D models seems to be the next logical step.

DreamGaussian represents a significant advancement in the field of 3D content creation, harnessing the power of AI. Enabling users to create 3D models from 2D images. While there are areas for improvement, the tool’s potential for enhancing the efficiency of 3D creation and opening up new opportunities is undeniable.

Image Credit : Mr Lemon

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New Midjourney upscalers 2x 4x now available to enlarge images

New Midjourney upscaler now available to enlarge your images even further

Further to its previous teases of a new image upscalers being rolled out to Midjourney. It’s development team have today announced the availability of two new Midjourney 2x and 4x upscalers. Both of which are now available to use are accessible under any standard V5 or Niji job after clicking on the U1/U2/U3/U4 buttons. Once you have initially upscaled your original image you will see two new buttons as shown in the image below.

They can also be used on older jobs using the /show jobid command. The upscalers are designed to be subtle, striving to keep the details as close as possible to the original image. However, it’s important to note that they may not rectify glitches or issues present in the original image.

Midjourney 2x and 4x Upscalers

Midjourney 2x and 4x upscalers demonstrated

In terms of cost, the 4x upscaler requires approximately three times more GPU minutes than the 2x upscaler. This is an important consideration for users as they balance their need for higher resolution with their available resources.

Currently, both upscalers are compatible only with fast-GPU time. Midjourney has not yet determined whether there are sufficient GPUs to enable the upscalers in relax mode. Over the coming week, the company plans to conduct load tests to assess the feasibility of this.

Despite the excitement surrounding the release of these new Midjourney 2x and 4x upscaler features, it’s important to acknowledge some known issues. On very rare occasions, users may encounter a black or corrupted image when using the 4x upscale. Furthermore, a blurry low-resolution image will not be ‘unblurred’ by the upscalers, and images might sometimes be slightly darkened by the upscalers.

Other articles we have written that you may find of interest on the subject of Midjourney AI art generator :

Midjourney is fully aware of these issues and is actively working on solutions. The company is also considering enabling the new upscalers on relax mode to test the server capacity. While this is not a guarantee, it indicates Midjourney’s commitment to continuously improving its offerings.

In response to user feedback that the 4x upscaler is a bit soft, Midjourney is exploring improvements that could enhance the upscaler’s performance. This means that the upscaler settings may change suddenly over the next week without warning as the company tweaks and optimizes the system.

The release of the new Midjourney upscalers presents an exciting development in the field of image processing. While there are some known issues and potential changes in the pipeline, the introduction of these tools opens up new possibilities for enhancing and enlarging images. As always, users are encouraged to provide feedback and report any issues to help Midjourney continue to improve its offerings.

Midjourney upscaler announcement

“We are going to try enabling the new upscalers on relax mode for a bit, we aren’t 100% sure if our servers can handle it, but there’s only one way to find out. In the meantime, enjoy! We’re also hearing everyone’s feedback that the 4x upscaler is a bit soft and we’re looking at improvements which may further improve things. This means the upscaler settings may change suddenly over the next week without warning as we tweak things. Just wanted to let everyone know.”

  • You can see 2x and 4x upscale buttons under any normal V5 or Niji job after clicking U1/U2/U3/U4
  • You can use it on old jobs using /show jobid
  • The upscaler is subtle and tries to keep details as close as possible to the original image

(but may not fix glitches or issues with the old image)

  • The 4x upscaler costs roughly 3x more GPU minutes than the 2x upscaler

Please Note:

  • Both upscalers only work with fast-gpu time right now
  • We don’t know if we have enough GPUs yet to enable it in relax mode.
  • We may do brief load tests over the coming week where we enable it on relax mode and see what happens.

Known issues:

  • Under very rare occasions you may see get a black or corrupted image on 4x upscales (we are investigating)
  • A blurry low resolution image will not be ‘unblurred’ by upscales
  • Images might get slightly slightly darkened sometimes by upscalers

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Analyzing and creating images in ChatGPT DallE 3

introduction to working with images in ChatGPT DallE 3

The image interaction capabilities of ChatGPT Plus and Enterprise plans have transformed the way users interact with visual data and images. OpenAI has recently released its third-generation AI art generator which it has integrated into both  Microsoft’s Bing  Image Creator and its own ChatGPT AI. These capabilities range from image description and analysis to artistic style identification, image captioning for social media, and even advanced data analysis for non-text data interaction. As well as the ability to now ask ChatGPT to create pictures, images and infographics and more using the DallE 3 image generator.

This guide will provide an introduction to these features, providing an introduction to analyzing and creating images in ChatGPT DallE 3. One of the most basic yet powerful features of ChatGPT is its ability to describe images. This feature allows users to gain a deeper understanding of the visual content they are dealing with. For instance, Janet, a user of ChatGPT 4 on a Plus account, frequently uses this feature to interact with images. She finds it particularly useful when dealing with complex images that require a detailed description.

Analyzing  images in ChatGPT DallE 3

In addition to describing images, ChatGPT can also identify their artistic style. This feature is particularly useful for art enthusiasts and professionals who want to gain insights into the artistic elements of an image. The AI tool can suggest artists who create similar art, providing users with a broader perspective on the art world.

 

Social media managers will find the image captioning feature of ChatGPT particularly useful. The AI tool can generate captions for images, making it easier for users to create engaging social media posts. This feature not only saves time but also ensures that the captions are relevant and engaging.

ChatGPT’s ability to compare two images is another feature that sets it apart. The AI tool provides a description and comparison of each image, allowing users to understand the similarities and differences between them. This feature can be particularly useful in fields like design and photography, where comparative analysis is often required.

The Advanced Data Analysis mode of ChatGPT is a game-changer for users who interact with non-text data. This feature allows users to interact with data, including images and videos. For instance, users can ask ChatGPT to analyze a PDF file and provide bullet points summarizing the content. This feature simplifies the process of data analysis, making it accessible to a wider audience.

Creating images using ChatGPT DallE 3

Image editing, transformation, and analysis are other areas where ChatGPT shines. The AI tool offers various filters and edits, allowing users to enhance their images. Users can ask ChatGPT to download an edited image, which it provides via a link. This feature makes it easier for users to manage their edited images.

ChatGPT also excels in creating GIFs and MP4s. Users can ask the AI tool to adjust the size of images and create GIFs or MP4s. This feature is particularly useful for users who want to create engaging visual content for their social media platforms or websites. Face detection in images is another feature that ChatGPT offers. While the AI tool can detect faces in images, it struggles with abstract faces.

OpenAI’s introduction to ChatGPT  DallE 3

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The image interaction capabilities of ChatGPT Plus and Enterprise plans offer a wide range of features that can revolutionize the way users interact with visual data. From image description and analysis to artistic style identification, image captioning for social media, and even advanced data analysis for non-text data interaction, these features provide users with a comprehensive tool for dealing with visual data. As Janet encourages, users should continue exploring the capabilities of ChatGPT and other large language models to fully leverage their potential.

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How to upload images to ChatGPT for analysis

How to upload images to ChatGPT for analysis

Recently OpenAI rolled out a new feature to its ChatGPT AI model allowing users to upload images of practically anything for the large language model to then analyze. This enables users to use images in their prompts and ask questions about photographs, diagrams or reports. ChatGPT will then examine the uploaded image and provide feedback answering any questions users may ask about it. For instance you could upload a math’s question from an old exam paper and ChatGPT would be able to analyze it and tell you how to answer the question without you having to type in any of the equations, fractions or graphs.

The ChatGPT image input feature allows users to upload images, which the model can then analyze and respond to. This feature extends the capabilities of text-based interactions, enabling a variety of use-cases such as image description, object recognition, and even some level of visual analysis.

ChatGPT image analysis

The technology relies on a multimodal approach, combining text and image data during processing. While the image analysis is not as advanced as specialized computer vision models, it provides a reasonable level of accuracy for general purposes.

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You can use it to get descriptions of images, ask for the identification of objects within images, or even seek artistic interpretations, among other functionalities. Keep in mind that the quality and usefulness of the output can vary based on the clarity and complexity of the image in question.

Uploading images to ChatGPT for analysis and response can be a straightforward process, but it’s important to consider several key elements, including file type, size, and the specific requirements of the task you want the model to accomplish. Here’s a comprehensive guide on how to do it effectively.

Before you begin, ensure you’re using a platform or service that has enabled the ChatGPT image upload feature. This feature might not be available on all implementations of the ChatGPT API. Additionally, be prepared with the image you intend to upload. The image should ideally be clear, well-lit, and relevant to the query you intend to make.

File types and sizes

ChatGPT generally supports common image file types like JPG, PNG, and GIF. While there may not be an officially stated file size limit, keeping your images to a reasonable size (a few megabytes) is advisable for faster processing. If you need to analyse PDF documents you will need to use a plugin at the current time which will allow ChatGPT to analyze the text and images within the PDF and answer any prompts you ask.

How to upload an image to ChatGPT

The specific steps for uploading an image will vary depending on the platform you are using to interact with ChatGPT. However, the general process usually involves:

  1. Make sure that you are in the ChatGPT Default mode,  by selecting this at the top selecting GPT-4 in the first selection in the drop down ” Default”
  2. Once this is selected you will see a small square icon appear on the left-hand side of the text entry box. It looks like a line drawing of a mountain in the sun in a square frame.
  3. Click on the icon button and you will be asked to select an image file to upload
  4. Browsing your device’s file system to select the image you wish to upload.
  5. Confirming the upload and waiting for the image to be processed
  6. Once the images uploaded you can then asked ChatGPT to confirm it understand the image, diagram or photograph and ask questions about it.

For example, you could ask, “What’s in this image?” or “Describe the artistic style of this painting.” Be explicit about what you want to know. The model will attempt to analyze the image based on your query and respond accordingly.

AI model limitations

While ChatGPT does possess image analysis capabilities, it’s worth noting that these are not as advanced as those found in specialized computer vision models. Therefore, while it can identify common objects and provide general descriptions, it may not be able to perform more complex analyses like emotion recognition in faces or detecting minute details. But it is still very impressive all the same and is a fantastic addition to the ChatGPT service for Plus users.

Optimising your prompt better results

  • Clarity: Make sure the image is clear and the object or scene you are interested in is easily distinguishable.
  • Context: If the image is part of a set or sequence, or if it requires context, provide that information in your text query.
  • Specificity: Be specific in your queries. Instead of asking, “What do you see?”, you might ask, “What is the breed of the dog in this image?”

If you receive an unsatisfactory response, try refining your question or uploading a clearer image. Keep in mind that ChatGPT, while versatile, is not infallible and has its limitations in terms of visual recognition and analysis.

Uploading images to ChatGPT opens up a range of possibilities for interaction and query that go beyond text-based communication. By following best practices in file preparation, upload procedure, and query formulation, you can optimize the quality of the responses you receive. While the system’s capabilities in this area are not as specialized as those in dedicated computer vision applicat

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