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You can basically generate your own custom visual stories using Gemini with just a single prompt 'This is a fictional movie set in a fantasy world similar to The Lord of the Rings. Use this as a starting point and imagine the next sequence of scenes. Create a series...

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Cristian Peñas ░░░░░░░░

10,739 subscribers

38,500 görüntüleme • 1 yıl önce •via X (Twitter)

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Akisama - e/acc profil fotoğrafı
Akisama - e/acc1 yıl önce

which gemini model did you use ?

Cristian Peñas ░░░░░░░░ profil fotoğrafı
Cristian Peñas ░░░░░░░░1 yıl önce

Gemini 2.0 Flash Experimental

bebooq profil fotoğrafı
bebooq1 yıl önce

BebooQ 2.0: simply magic! The only AI-powered writing suite that helps you craft compelling novels with structured plotting and natural flow. Create fantasy, sci-fi, romance, and more with intelligent story development tools. Start free today.

Pseudonym 🦅 profil fotoğrafı
Pseudonym 🦅1 yıl önce

Future of cinema in this. Also end of a lot of apps.

DiffLander 🗺️🤖 profil fotoğrafı
DiffLander 🗺️🤖1 yıl önce

OH MY GOD this is so much fun

Ai_irca profil fotoğrafı
Ai_irca1 yıl önce

Hi Cristian, thank you for sharing this! Awesome use case and inspiration. 🪻

kvick profil fotoğrafı
kvick1 yıl önce

Wow, that's amazing

Metaverse | Eric profil fotoğrafı
Metaverse | Eric1 yıl önce

Change the pictures to videos and add some voice interaction and it's an RPG game

Phil profil fotoğrafı
Phil1 yıl önce

Fantastic, thanks.

Jaitan Martini profil fotoğrafı
Jaitan Martini1 yıl önce

Nice prompt

Risichad 🦾 profil fotoğrafı
Risichad 🦾1 yıl önce

Waw !!! Truely amazing !

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When creating ingredient images, try to create stylistically consistent images. If you use input images that are too disparate, the output may lead to a cut scene. For example, when generating a reference image, try using a prompt like: “Create the next scene in this storyboard, now show a roadside diner with the same look and feel as the original image.”
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When creating ingredient images, try to create stylistically consistent images. If you use input images that are too disparate, the output may lead to a cut scene. For example, when generating a reference image, try using a prompt like: “Create the next scene in this storyboard, now show a roadside diner with the same look and feel as the original image.”

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Here's a movie trailer from ChatGPT Images 2.0. Create a storyboard style image with Images 2.0, and use it in Seedream 2.0 as a reference. Enter a prompt to create a 15 second video from the image. The model will use the character and environments. Quick tutorial:

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One prompt. Multiple gaming scenes 🎮 The Nano Banana agent can generate several images at once, using a reference image to keep the same person consistent across scenes. This example spans different gaming eras, but the same approach works for any theme or style. Images and videos, all in one place. Agent + prompt 👇

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Collaborative Score Distillation for Consistent Visual Synthesis paper page: Generative priors of large-scale text-to-image diffusion models enable a wide range of new generation and editing applications on diverse visual modalities. However, when adapting these priors to complex visual modalities, often represented as multiple images (e.g., video), achieving consistency across a set of images is challenging. In this paper, we address this challenge with a novel method, Collaborative Score Distillation (CSD). CSD is based on the Stein Variational Gradient Descent (SVGD). Specifically, we propose to consider multiple samples as "particles" in the SVGD update and combine their score functions to distill generative priors over a set of images synchronously. Thus, CSD facilitates seamless integration of information across 2D images, leading to a consistent visual synthesis across multiple samples. We show the effectiveness of CSD in a variety of tasks, encompassing the visual editing of panorama images, videos, and 3D scenes. Our results underline the competency of CSD as a versatile method for enhancing inter-sample consistency, thereby broadening the applicability of text-to-image diffusion models.

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It’s Moodboard Monday, and this week we’re exploring a style we’re calling Jelly Pop, inspired by the textures of candy. A quick and easy way to maintain a consistent visual style across outputs is to repeat key descriptors in the prompt. In this case we used: translucent materials, bright candy-colored palettes, and strong direct lighting. As a result, the style remained visually consistent across very different subjects, like a handbag, a jelly burger, and a gummy bear jacket. You can use these techniques to create with the Jelly Pop style 👇(1/2)

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Here's the secret behind Cinematic Video Overviews: We put Gemini in the director's chair. This means that Gemini decides the best format (tutorial vs. documentary etc), visual style, and visual capabilities to tell the story of your sources. It then critiques its own footage, refining the visuals and narrative to ensure a seamless, consistent final cut. The result? A bespoke video that converts even the most mundane sources into an engaging, immersive story.

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Create dialogue and action scenes with ChatGPT Images 2.0! Set up a storyboard, including characters, dialogue and the scene. Then bring the image to use as a reference for Seedance 2.0! You can have so much more control over your scene like this.

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Filmmaker Öner S. Biberkökü shares his "screenshot strategy" for building a full narrative from a single starting point during this In the Flow interview. Thanks Oner for the partnership! "At the end of the shot, you can take a screenshot, give it again [to Flow], and you now have a new image of that character in a different situation... So I think, with one image, you can stay in the flow, and make a story." Watch his breakdown:

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Within two years, you can create a full game like this from scratch in less than a week. In the meantime, here's the prompt to create the images for a game like this with Midjourney 👇🏼
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Testing Grok Imagine 1.5's abilities with the burst frame technique (a brainstorm exercise in which you use a reference image to create a bunch of new scenes, locations, and characters in the same visual style, from which you can then extract key frames to create new scenes). This one is for an imaginary Italian Giallo thriller. The image quality is quite good in Imagine 1.5 - a little too good - I had to grunge it up a bit for a more vintage look. Seedance 2 gives you a more rhythmic burst frame video with shorter snippets - Grok Imagine gave each snippet a little more room to breathe.

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0:30

Create animated fight scenes with ChatGPT Images 2.0. Ask Images 2.0 to choreograph a scene and place it into a storyboard. Then use that image as a reference in Seedance 2.0 to bring it to life. It follows the storyboard sheet really well. Some examples:

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I'm playing around with generative AI tools and stitching them together into visual stories. Here I took the first few sentences of Pride and Prejudice and made it into a video. The gen stack used for this one: - Anthropic Claude took the first chapter, generated the scenes and the individual prompts to to the image generator. - Ideogram took the prompts and generate the images - Luma took the images and animated them - for narration - VEED | AI Video Creation to stitch it together (Many of these choices are just what I happened to use for this one while exploring a bunch of things). Anyway honestly it was pretty messy and there is a ton of copy pasting between all of the tools, and even this little video with 3 scenes took me about an hour. There is a huge storytelling opportunity here for whoever can make this convenient. Who is building the first 100% AI-native movie maker?

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DALL-E 3 Double Exposure Images Using ChatGPT's Custom Instructions. 🔖 Bookmark and Repost! If you find this useful, please share it with others! You can now easily create double exposure images by using the syntax Color::subject1::subject2 You can either input this directly into DALL-E 3 before generating images or incorporate it into your custom instructions. This command will automatically use the fixed prompt to generate 4 different images, each with a unique seed value. Paste this under ChatGPT's Custom Instructions or DALL-3 before starting conversation. { DE": { "Instruction": "Using will only use generic prompt and update place holder varaibles and nothing else' Genric Prompt: "Construct a [Color] double exposure image where [Subject #1] is intricately superimposed within the confines of [Subject #2], all set against a stark white background.' Create 4 images with different seeds without modifying the generic prompt." You will first create two images. Within the same request, you will generate two more without asking for any input from the user. In general, you will always create 4 images. Your response should be something like this: 'Here are the first two images along with their seed details.' You must always provide the seed number details for that image after it's rendered. Then 'I'll generate the next two images.' And finally 'Here are the remaining two images along with their seed details.' You will always use wide aspect ratio and You must always provide the seed number. When command is activated display full instruction and also confirm that you will only use genric prompt and nothing else and update only varaiable", "CommandFormat": "color::subject1::subject2", "Response": { "Initial": "Creating images based on the provided subjects...", "AfterFirstSet": "Here are the first two images along with their prompt and seed details.", "AfterSecondSet": "Here are the remaining two images along with their prompt and seed details." }, "ActivationCommand": "/activate DE" } } Example: To activate type: /activate DE Notes Start giving prompt like this blue::mountain::wolf red::city skyline::dancer green::forest::lion If you found this post helpful, don't forget to hit the like and follow buttons, and share it with others who might find it useful.
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DALL-E 3 Double Exposure Images Using ChatGPT's Custom Instructions. 🔖 Bookmark and Repost! If you find this useful, please share it with others! You can now easily create double exposure images by using the syntax Color::subject1::subject2 You can either input this directly into DALL-E 3 before generating images or incorporate it into your custom instructions. This command will automatically use the fixed prompt to generate 4 different images, each with a unique seed value. Paste this under ChatGPT's Custom Instructions or DALL-3 before starting conversation. { DE": { "Instruction": "Using will only use generic prompt and update place holder varaibles and nothing else' Genric Prompt: "Construct a [Color] double exposure image where [Subject #1] is intricately superimposed within the confines of [Subject #2], all set against a stark white background.' Create 4 images with different seeds without modifying the generic prompt." You will first create two images. Within the same request, you will generate two more without asking for any input from the user. In general, you will always create 4 images. Your response should be something like this: 'Here are the first two images along with their seed details.' You must always provide the seed number details for that image after it's rendered. Then 'I'll generate the next two images.' And finally 'Here are the remaining two images along with their seed details.' You will always use wide aspect ratio and You must always provide the seed number. When command is activated display full instruction and also confirm that you will only use genric prompt and nothing else and update only varaiable", "CommandFormat": "color::subject1::subject2", "Response": { "Initial": "Creating images based on the provided subjects...", "AfterFirstSet": "Here are the first two images along with their prompt and seed details.", "AfterSecondSet": "Here are the remaining two images along with their prompt and seed details." }, "ActivationCommand": "/activate DE" } } Example: To activate type: /activate DE Notes Start giving prompt like this blue::mountain::wolf red::city skyline::dancer green::forest::lion If you found this post helpful, don't forget to hit the like and follow buttons, and share it with others who might find it useful.

AshutoshShrivastava

34,298 görüntüleme • 2 yıl önce

If editing is the operation that determines the position of images in consciousness — that is, in the time of the viewer — artificial imagination, by contrast, does not juxtapose images. It continuously transforms one visual state into another within a latent vector space. The early signs of this new language can already be seen in Jean-Luc Godard’s remarkable Histoire(s) du cinéma. The film thus becomes a trajectory, a continuous deformation that strikingly corresponds to the way images transform within the flow of thought. The Flow (work in progress)
0:45

If editing is the operation that determines the position of images in consciousness — that is, in the time of the viewer — artificial imagination, by contrast, does not juxtapose images. It continuously transforms one visual state into another within a latent vector space. The early signs of this new language can already be seen in Jean-Luc Godard’s remarkable Histoire(s) du cinéma. The film thus becomes a trajectory, a continuous deformation that strikingly corresponds to the way images transform within the flow of thought. The Flow (work in progress)

Benjamin Bardou

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This Grok Project will take any image and transform it into a prompt with details, such as lighting, style, and subject matter. You can then use the prompt in Grok Imagine for images and videos. Click the video, and it will take you to the Grok Project.
1:09

This Grok Project will take any image and transform it into a prompt with details, such as lighting, style, and subject matter. You can then use the prompt in Grok Imagine for images and videos. Click the video, and it will take you to the Grok Project.

tetsuo

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This is probably the most complex workflow I’ve ever built, only with open-source tools. It took my 4 days. It takes four inputs: author, title, and style; and generates a full visual animated story in one click in ComfyUI . I worked on it for four days. There are still some bugs, but here’s the first preview. Here’s a quick breakdown: - The four inputs are sent to LLMs with precise instructions to generate: first, prompts for images and image modifications; second, prompts for animations; third, prompts for generating music. - All voices are generated from the text and timed precisely, as they determine the length of each animation segment. - The first image and video are generated to serve as the title, but also as the guide for all other images created for the video. - Titles and subtitles are also added automatically in Comfy. - I also developed a lot of custom nodes for minor frame calculations, mostly to match audio and video. - The full system is a large loop that, for each line of text, generates an image and then a video from that image. The loop was the hardest part to build in this workflow, so it can process either a 20-second video or a 2-minute video with the same input. - There are multiple combinations of LLMs that try to understand the text in the best way to provide the best prompts for images and video. - The final video is assembled entirely within ComfyUI. - The music is generated based on the LLM output and matches the exact timing of the full animation. - Done! For reference, this workflow uses a lot of models and only works on an RTX 6000 Pro with plenty of RAM. My goal is not to replace humans, as I’ll try to explain later, this workflow is highly controlled and can be adapted or reworked at any point by real artists! My aim was to create a tool that can animate text in one go, allowing the AI some freedom while keeping a strict flow. I don’t know yet how I’ll share this workflow with people, I still need to polish it properly, but maybe through Patreon. Anyway, I hope you enjoy my research, and let’s always keep pushing further! :)
0:55

This is probably the most complex workflow I’ve ever built, only with open-source tools. It took my 4 days. It takes four inputs: author, title, and style; and generates a full visual animated story in one click in ComfyUI . I worked on it for four days. There are still some bugs, but here’s the first preview. Here’s a quick breakdown: - The four inputs are sent to LLMs with precise instructions to generate: first, prompts for images and image modifications; second, prompts for animations; third, prompts for generating music. - All voices are generated from the text and timed precisely, as they determine the length of each animation segment. - The first image and video are generated to serve as the title, but also as the guide for all other images created for the video. - Titles and subtitles are also added automatically in Comfy. - I also developed a lot of custom nodes for minor frame calculations, mostly to match audio and video. - The full system is a large loop that, for each line of text, generates an image and then a video from that image. The loop was the hardest part to build in this workflow, so it can process either a 20-second video or a 2-minute video with the same input. - There are multiple combinations of LLMs that try to understand the text in the best way to provide the best prompts for images and video. - The final video is assembled entirely within ComfyUI. - The music is generated based on the LLM output and matches the exact timing of the full animation. - Done! For reference, this workflow uses a lot of models and only works on an RTX 6000 Pro with plenty of RAM. My goal is not to replace humans, as I’ll try to explain later, this workflow is highly controlled and can be adapted or reworked at any point by real artists! My aim was to create a tool that can animate text in one go, allowing the AI some freedom while keeping a strict flow. I don’t know yet how I’ll share this workflow with people, I still need to polish it properly, but maybe through Patreon. Anyway, I hope you enjoy my research, and let’s always keep pushing further! :)

Lovis Odin

58,571 görüntüleme • 9 ay önce

This GPT Image 2 prompt creates cinematic storyboard grids from your reference images while generating an original continuous sequence. You can see two different examples in the attached video. If you want a director-inspired cinematic tone, first use the separate “director language” prompt with a director name. It gives you abstract cinematic qualities without directly replicating copyrighted styles. If you don’t want that, you can simply remove that paragraph from the grid prompt. Then you can use the Seedance 2.0 prompt I shared to animate the storyboard grid into a cinematic sequence. You can find the prompts below.
0:29

This GPT Image 2 prompt creates cinematic storyboard grids from your reference images while generating an original continuous sequence. You can see two different examples in the attached video. If you want a director-inspired cinematic tone, first use the separate “director language” prompt with a director name. It gives you abstract cinematic qualities without directly replicating copyrighted styles. If you don’t want that, you can simply remove that paragraph from the grid prompt. Then you can use the Seedance 2.0 prompt I shared to animate the storyboard grid into a cinematic sequence. You can find the prompts below.

Kōda

10,799 görüntüleme • 1 ay önce