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We came across a really interesting tool that fixes a pretty common problem inside AI video workflows: extending AI cinematic scenes with seamless continuity. Using Omni models, you can take the last frame from an existing video clip and prompt something like: “show me what happens next in the... video, use the last frame as the start frame” and it actually creates a second clip with surprisingly good continuity from the original shot. But you know how when you try stitching two clips together in Premiere Pro, you can usually spot the exact transition point? The exposure shifts slightly, the lighting bounces, or something just feels off enough that you can tell the clips don’t fully belong together. Well this new tool called SeeDance 2 Stitcher from TomLikesRobots🤖 automatically blends the two clips together in a much more seamless way and honestly the results are pretty impressive.show more

Curious Refuge

22,577 subscribers

14,282 次观看 • 4 个月前 •via X (Twitter)

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TomLikesRobots🤖 的头像

TomLikesRobots🤖4 个月前

Hey thanks for sharing. I'm happy that I built a tool to help my workflows that other people are finding useful too. Here are the links Webtool: Github repo for local install: BTW it also improves the join in a couple of other ways. - scans for and removes any overlapping frames. - micro cross-fades the audio to avoid that pfft or click sound at joins.

IcecoldAI 的头像

IcecoldAI4 个月前

$Omnimals 🌓🚀🚀🚀

Kol Tregaskes 的头像

Kol Tregaskes4 个月前

With Gemini Omni I found I didn't need to do this, I just asked it to continue and it did, not perfect though. Colouring changes.

AI Mastery Guide 的头像

AI Mastery Guide4 个月前

The lighting bounce at the stitch point has ruined so many AI video timelines, this solves the most annoying part of the workflow

Kevin Bankston 的头像

Kevin Bankston4 个月前

Thanks for your excellent and helpful posting about Omni, I cited y'all in my roundup of reaction to the model in today's issue of my media & tech newsletter Converger:

Ege 的头像

Ege4 个月前

Thanks for this, gonna try it

Zack Millsaps 的头像

Zack Millsaps4 个月前

Literally was trying to solve this today. Amazing

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So Runway Aleph 2.0 just dropped, and it introduces a pretty interesting workflow for AI video footage editing. Rather than repeatedly prompting a video model and hoping it makes the change you want, you can edit a specific frame first, then use that frame to guide the video generation. For this test, I take an existing footage inside Runway: • Picked a frame from the original video • Used Nano Banana Pro to add a new effect/object • Brought that frame into Aleph 2.0 to generate the updated video It feels like a more controllable and potentially cheaper way to make targeted edits to existing footage than current AI video omni models available like Seedance and Gemini.

So Runway Aleph 2.0 just dropped, and it introduces a pretty interesting workflow for AI video footage editing. Rather than repeatedly prompting a video model and hoping it makes the change you want, you can edit a specific frame first, then use that frame to guide the video generation. For this test, I take an existing footage inside Runway: • Picked a frame from the original video • Used Nano Banana Pro to add a new effect/object • Brought that frame into Aleph 2.0 to generate the updated video It feels like a more controllable and potentially cheaper way to make targeted edits to existing footage than current AI video omni models available like Seedance and Gemini.

Curious Refuge

11,410 次观看 • 3 个月前

Notch Clips. every other ad tool ignores the footage sitting in your dropbox and generates new clips from a prompt. notch opens your library instead. it watches every clip you have ever shot and understands what is inside each one. the mood. who is in frame. what they are doing. the quality. so when you ask it to build an ad, it does not start from scratch. it reaches into your past shoots, finds the clip that fits, and slots it into the exact moment that needs it. here is what that looks like. you had thirteen versions of one reaction shot. notch picked the one that worked and left the other twelve. not by filename. not by guessing from a reference image. it watched all thirteen and could tell the difference. that is the whole idea. the right clip was already in your library. every other tool was about to make a worse one. footage you already shot, turned into every ad you still need. drop your site and a few clips you have. notch builds the first ad from them.

Notch Clips. every other ad tool ignores the footage sitting in your dropbox and generates new clips from a prompt. notch opens your library instead. it watches every clip you have ever shot and understands what is inside each one. the mood. who is in frame. what they are doing. the quality. so when you ask it to build an ad, it does not start from scratch. it reaches into your past shoots, finds the clip that fits, and slots it into the exact moment that needs it. here is what that looks like. you had thirteen versions of one reaction shot. notch picked the one that worked and left the other twelve. not by filename. not by guessing from a reference image. it watched all thirteen and could tell the difference. that is the whole idea. the right clip was already in your library. every other tool was about to make a worse one. footage you already shot, turned into every ad you still need. drop your site and a few clips you have. notch builds the first ad from them.

Vinay Jain

406,286 次观看 • 3 个月前

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.

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

11,369 次观看 • 4 个月前

I've been experimenting with Seedance 2.0 to create seamless extensions. I created this sequence called UBUMBE FOREST. Seamless extensions can actually be quite tricky to do and requires some precise magic with editing to connect them. There is no shortcut here, you must experiment until you find the sweet spot to make the transition seamless. Ubumbe Forest - During a routine foraging trip deep in the Ubumbe forest in Tanzania, a father guides his daughter off the beaten path. Here, hidden from the rest of their tribe, she steps into a breathtaking new world and comes face-to-face with insects and creatures she has never seen before, even encountering a rare Peafox. 🟢Extending a scene however is fairly simple: - Generate your first sequence. - Upload that video as an Omni reference. - Type this at the start of the prompt "Naturally continue the movement and momentum from the previous clip. Keep the exact same art style, lighting, character appearance, and physics." and then explain what happens next in this sequence. - Congrats, you now have a scene extension that naturally flows from where the last video ended. However this is only the start of the puzzle, you need to join these clips so they're seamless. Seedance 2.0 is able to match the pacing, remember the characters and even their voices using this technique. The hard part is the extension but check my second post to see how I'm doing it in Capcut.

I've been experimenting with Seedance 2.0 to create seamless extensions. I created this sequence called UBUMBE FOREST. Seamless extensions can actually be quite tricky to do and requires some precise magic with editing to connect them. There is no shortcut here, you must experiment until you find the sweet spot to make the transition seamless. Ubumbe Forest - During a routine foraging trip deep in the Ubumbe forest in Tanzania, a father guides his daughter off the beaten path. Here, hidden from the rest of their tribe, she steps into a breathtaking new world and comes face-to-face with insects and creatures she has never seen before, even encountering a rare Peafox. 🟢Extending a scene however is fairly simple: - Generate your first sequence. - Upload that video as an Omni reference. - Type this at the start of the prompt "Naturally continue the movement and momentum from the previous clip. Keep the exact same art style, lighting, character appearance, and physics." and then explain what happens next in this sequence. - Congrats, you now have a scene extension that naturally flows from where the last video ended. However this is only the start of the puzzle, you need to join these clips so they're seamless. Seedance 2.0 is able to match the pacing, remember the characters and even their voices using this technique. The hard part is the extension but check my second post to see how I'm doing it in Capcut.

Travis Davids

14,162 次观看 • 3 个月前

First frame + Last frame = Fashion ads in minutes. Here’s how I generated this U.S. Polo sequence using Kling 3.0 + Calico AI: → The Input: A start frame and an end frame to lock in the subject and composition. → The Prompt: Don't just ask for a "cool video." Specifically prompted for "slow cinematic push-in," "shallow depth of field," and "micro-parallax" to get that premium brand-film look. → The Output: Motion that looks like a high-budget fashion shoot. Studio shoots are expensive, but AI is leveling the playing field. Comment 'PROMPT' if you want me to send you all of the prompts and the system I used to build this. (must be following so I can dm you!)

David Roberts

26,405 次观看 • 7 个月前

Grok Imagine gives you complete control over your videos, letting you direct the camera's movement, control your character's actions, script their dialogue, and manage how objects in the scene interact. Your characters can smash objects, swing a bat, or walk out of a room. To build seamless videos, start by extracting the last frame from your current clip and using it as the starting frame for the next one.

Grok Imagine gives you complete control over your videos, letting you direct the camera's movement, control your character's actions, script their dialogue, and manage how objects in the scene interact. Your characters can smash objects, swing a bat, or walk out of a room. To build seamless videos, start by extracting the last frame from your current clip and using it as the starting frame for the next one.

tetsuo

27,443 次观看 • 11 个月前

this guy built an AI video pipeline that turns one prompt into a finished short. he barely opens editing software. give Claude a simple idea. in the demo: a puppy rescue story. Claude runs the entire production from there: → generates the images with Nano Banana 2 → turns them into motion with Kinovi / Seedance 2.0 → stitches the clips together with FFmpeg → uploads the finished video no manually generating every frame. no dragging clips around a timeline for an hour. no stitching together the edit by hand. here’s the actual shift, and it’s bigger than “AI made a video”: Claude isn’t just one tool in the chain anymore. it’s coordinating the whole chain deciding what goes where, which tool handles which step, and executing it end to end. idea → images → video clips → edit → final render. one prompt in, finished short out. most people are still using AI one tool at a time generate an image here, cut it there, stitch it somewhere else, doing the coordination themselves. the bigger unlock isn’t a better individual tool. it’s connecting the tools so nothing needs a human in between steps. give it an idea. let the system make the video.

this guy built an AI video pipeline that turns one prompt into a finished short. he barely opens editing software. give Claude a simple idea. in the demo: a puppy rescue story. Claude runs the entire production from there: → generates the images with Nano Banana 2 → turns them into motion with Kinovi / Seedance 2.0 → stitches the clips together with FFmpeg → uploads the finished video no manually generating every frame. no dragging clips around a timeline for an hour. no stitching together the edit by hand. here’s the actual shift, and it’s bigger than “AI made a video”: Claude isn’t just one tool in the chain anymore. it’s coordinating the whole chain deciding what goes where, which tool handles which step, and executing it end to end. idea → images → video clips → edit → final render. one prompt in, finished short out. most people are still using AI one tool at a time generate an image here, cut it there, stitch it somewhere else, doing the coordination themselves. the bigger unlock isn’t a better individual tool. it’s connecting the tools so nothing needs a human in between steps. give it an idea. let the system make the video.

RUX

11,269 次观看 • 1 个月前

I used 7 AI tools to make one commercial. And honestly, generating the clips was the easy part. The real problem started after I had 30+ clips sitting in different folders. Different versions. Different scenes. Different takes. Different AI tools. At some point, I had plenty of footage… but no actual film. That’s where Filmora TV came in. If you’re new to Filmora TV, you can download it here: New users who download through this link can get 40% off video creation using the Wan 3.0 model. Instead of constantly jumping between different tools and trying to figure out which clip belongs where, I could bring the whole production into one canvas. I could organize my characters and scenes, compare different versions, arrange the shots, connect the story, and build the rough cut on the timeline. The biggest difference for me? It changes the workflow from: Prompt → Clip → Prompt → Clip → repeat to: Clips → Story → Rough Cut → Film And that’s really the part of AI video creation that I think gets overlooked. AI can generate incredible individual shots. But 30 amazing clips don’t automatically make a film. You still need to decide: → Which shots belong together? → Which version works best? → Does the character stay consistent? → Does the story actually flow? → What should stay and what should be cut? Filmora TV puts that process into one creative workspace. So instead of having AI-generated clips scattered everywhere, you can actually start turning them into something watchable. 7 AI tools. 30+ clips. 1 canvas. 1 finished commercial. From Clips to Film. 🎬

I used 7 AI tools to make one commercial. And honestly, generating the clips was the easy part. The real problem started after I had 30+ clips sitting in different folders. Different versions. Different scenes. Different takes. Different AI tools. At some point, I had plenty of footage… but no actual film. That’s where Filmora TV came in. If you’re new to Filmora TV, you can download it here: New users who download through this link can get 40% off video creation using the Wan 3.0 model. Instead of constantly jumping between different tools and trying to figure out which clip belongs where, I could bring the whole production into one canvas. I could organize my characters and scenes, compare different versions, arrange the shots, connect the story, and build the rough cut on the timeline. The biggest difference for me? It changes the workflow from: Prompt → Clip → Prompt → Clip → repeat to: Clips → Story → Rough Cut → Film And that’s really the part of AI video creation that I think gets overlooked. AI can generate incredible individual shots. But 30 amazing clips don’t automatically make a film. You still need to decide: → Which shots belong together? → Which version works best? → Does the character stay consistent? → Does the story actually flow? → What should stay and what should be cut? Filmora TV puts that process into one creative workspace. So instead of having AI-generated clips scattered everywhere, you can actually start turning them into something watchable. 7 AI tools. 30+ clips. 1 canvas. 1 finished commercial. From Clips to Film. 🎬

Aryan Rakib

62,976 次观看 • 9 天前

Seriously, I watched the clip expecting the usual AI-video trick: a few beautiful seconds, then an obvious break in continuity. But ONEIRIC is attempting something much harder: A 20-minute drama made entirely with AI, with enough atmosphere, performance, and story to carry you beyond a single scroll! What makes this release especially compelling, though, is that it does not stop at the finished film. The prompts and assets are public too, so you can look inside the production instead of guessing how it came together 👀

Seriously, I watched the clip expecting the usual AI-video trick: a few beautiful seconds, then an obvious break in continuity. But ONEIRIC is attempting something much harder: A 20-minute drama made entirely with AI, with enough atmosphere, performance, and story to carry you beyond a single scroll! What makes this release especially compelling, though, is that it does not stop at the finished film. The prompts and assets are public too, so you can look inside the production instead of guessing how it came together 👀

Charly Wargnier

60,402 次观看 • 1 个月前

MiniMax H3 is native in ComfyUI, day zero with the weights. Model highlights: → Text-to-video, prompt only → Image-to-video → First-and-last-frame - control the opening frame, the closing frame, or both → Reference-to-video - carry a subject, a motion, or a voice through the clip → In-place editing - modify a shot you already have instead of regenerating it The capability MiniMax (official) leads with is multimodal context understanding, and it's what collapses those five tasks into one model. H3 takes images, audio, and video together and resolves them against a prompt that explains how they relate. Download the workflows & learn more in our blog 👇

MiniMax H3 is native in ComfyUI, day zero with the weights. Model highlights: → Text-to-video, prompt only → Image-to-video → First-and-last-frame - control the opening frame, the closing frame, or both → Reference-to-video - carry a subject, a motion, or a voice through the clip → In-place editing - modify a shot you already have instead of regenerating it The capability MiniMax (official) leads with is multimodal context understanding, and it's what collapses those five tasks into one model. H3 takes images, audio, and video together and resolves them against a prompt that explains how they relate. Download the workflows & learn more in our blog 👇

ComfyUI

234,529 次观看 • 1 个月前

AI video is quietly shifting from generation to direction. After testing Ray 3.2 on a restaurant launch concept, that became pretty obvious. I started with two static images: one exterior shot, one interior dining scene. A few minutes later, I had a cinematic sequence that actually felt connected. The biggest improvement isn't just realism. It's control. Most AI video workflows still look like this: prompt → generate → regenerate → regenerate again. You're mostly hoping the model understands what you want. Ray 3.2 feels different. Instead of generating isolated clips, you can guide how one scene evolves into the next. You can shape transitions, control camera movement, preserve visual consistency, and build sequences that feel intentionally directed. For a simple restaurant commercial, that makes a huge difference. The exterior naturally flows into the dining experience. The pacing feels deliberate. The motion feels cinematic. The story feels connected. And that's what stood out to me most. For the first time, AI video felt less like prompting and more like directing. Every frame, yours to direct. Try Luma today using my link:

AI video is quietly shifting from generation to direction. After testing Ray 3.2 on a restaurant launch concept, that became pretty obvious. I started with two static images: one exterior shot, one interior dining scene. A few minutes later, I had a cinematic sequence that actually felt connected. The biggest improvement isn't just realism. It's control. Most AI video workflows still look like this: prompt → generate → regenerate → regenerate again. You're mostly hoping the model understands what you want. Ray 3.2 feels different. Instead of generating isolated clips, you can guide how one scene evolves into the next. You can shape transitions, control camera movement, preserve visual consistency, and build sequences that feel intentionally directed. For a simple restaurant commercial, that makes a huge difference. The exterior naturally flows into the dining experience. The pacing feels deliberate. The motion feels cinematic. The story feels connected. And that's what stood out to me most. For the first time, AI video felt less like prompting and more like directing. Every frame, yours to direct. Try Luma today using my link:

SONIA

41,651 次观看 • 3 个月前

This is how you build the next generation of AI applications. You need an idea, a good model architecture, and a great harness. That's what MUZIM did. It's an app that runs local multimodal and vision models offline to parse and index your images, videos, and documents frame by frame. • Super fast on-device processing • On-device video & image understanding • You can also bring your API keys for heavy reasoning • Your data stays where it is / nothing goes to the cloud You can do a couple of things with this: 1. Vibe searching for whatever you remember in photos or raw video clips. The app will jump straight to the exact frame and timestamp of the video. This is search as it should be. 2. Use local-running agents to perform tasks on your files. I show a couple of examples in my video. You can check it out here: Thanks to the MUZIM by OpenSoul team for showing me the tool and partnering with me on this post.

This is how you build the next generation of AI applications. You need an idea, a good model architecture, and a great harness. That's what MUZIM did. It's an app that runs local multimodal and vision models offline to parse and index your images, videos, and documents frame by frame. • Super fast on-device processing • On-device video & image understanding • You can also bring your API keys for heavy reasoning • Your data stays where it is / nothing goes to the cloud You can do a couple of things with this: 1. Vibe searching for whatever you remember in photos or raw video clips. The app will jump straight to the exact frame and timestamp of the video. This is search as it should be. 2. Use local-running agents to perform tasks on your files. I show a couple of examples in my video. You can check it out here: Thanks to the MUZIM by OpenSoul team for showing me the tool and partnering with me on this post.

Santiago

65,953 次观看 • 1 个月前

You can now create long form AI Videos. Introducing Multi-Frame by Dreamina AI! Upload up to 10 images to be stitched together for a longer AI video output. You can control the duration of each transition and guide with a text prompt. Tutorial in the comments 🔽

You can now create long form AI Videos. Introducing Multi-Frame by Dreamina AI! Upload up to 10 images to be stitched together for a longer AI video output. You can control the duration of each transition and guide with a text prompt. Tutorial in the comments 🔽

Jerrod Lew

31,762 次观看 • 10 个月前

google flow + claude + gpt image is actually f*cking cracked i figured out how to lock one AI character across an entire video. same face, same voice, same outfit, every single shot. zero drift. everyone making AI video right now hits the same wall. the character looks different in every clip so you can never tell an actual story. you get 5 second clips, not films. the fix isn't better prompting. it's building the character ONCE before you ever touch video, then referencing it everywhere. here's the workflow: > build the character inside Flow's character section, not a per-clip prompt > design the voice + personality one time and reuse it across every clip > generate a full turnaround sheet (Claude writes the prompt, GPT image renders the angles) > pull the character into any scene with a single @ tag > ingredients vs frames: when to let a shot float vs lock it to your source image > the end-frame loop that chains 4-10 sec clips into one seamless scene > stitch + trim in the timeline editor and export the whole thing as one film i packaged the entire thing. every prompt, the exact tool order, the character sheet template, and the continuity loop nobody actually explains. RT + reply "FLOW" and i'll send it over (must be following so i can dm)

google flow + claude + gpt image is actually f*cking cracked i figured out how to lock one AI character across an entire video. same face, same voice, same outfit, every single shot. zero drift. everyone making AI video right now hits the same wall. the character looks different in every clip so you can never tell an actual story. you get 5 second clips, not films. the fix isn't better prompting. it's building the character ONCE before you ever touch video, then referencing it everywhere. here's the workflow: > build the character inside Flow's character section, not a per-clip prompt > design the voice + personality one time and reuse it across every clip > generate a full turnaround sheet (Claude writes the prompt, GPT image renders the angles) > pull the character into any scene with a single @ tag > ingredients vs frames: when to let a shot float vs lock it to your source image > the end-frame loop that chains 4-10 sec clips into one seamless scene > stitch + trim in the timeline editor and export the whole thing as one film i packaged the entire thing. every prompt, the exact tool order, the character sheet template, and the continuity loop nobody actually explains. RT + reply "FLOW" and i'll send it over (must be following so i can dm)

Sulfur

35,866 次观看 • 2 个月前

AI video started with a simple promise: Type a prompt. Get a video. Now the interesting problem is what happens after that. A film isn’t one impressive clip. It’s dozens of connected decisions, actions, characters, camera movements, and consequences. So the next phase of AI video may be less about making prettier clips and more about building systems that can understand and control complex scenes. Rhapsody 1.0 ( Induce AI ) is an interesting step in that direction, with reasoning, story-state tracking, and verification built around the generation process. The future of AI filmmaking probably isn’t just better generation. It’s better control. You must give it a try: Mahesh KMB

AI video started with a simple promise: Type a prompt. Get a video. Now the interesting problem is what happens after that. A film isn’t one impressive clip. It’s dozens of connected decisions, actions, characters, camera movements, and consequences. So the next phase of AI video may be less about making prettier clips and more about building systems that can understand and control complex scenes. Rhapsody 1.0 ( Induce AI ) is an interesting step in that direction, with reasoning, story-state tracking, and verification built around the generation process. The future of AI filmmaking probably isn’t just better generation. It’s better control. You must give it a try: Mahesh KMB

Charles Roman

31,412 次观看 • 24 天前

Every time an AI video goes viral, someone asks the same thing: what was the prompt? Usually nobody knows. So I built a tool that finds out: It runs on MOSS-VL, open-weight 11B model (open source on GitHub: Upload a reference clip, it watches it frame by frame and reverse-engineers a generation prompt from what's actually in the video, not a guess. Refine it for a style, then generate something new from it. MOSS-VL is built for continuous video streams. Quantized versions deploy locally on a single RTX 4090, and it can be fine-tuned through LlamaFactory if you need it to understand something specific, like your own product's UI. I used the hosted API here, analyzing an uploaded clip instead of a live stream. Two ways to use it yourself: deploy it locally for real-time stream processing, or grab a free API key and use the hosted API on your own clips. API:

Every time an AI video goes viral, someone asks the same thing: what was the prompt? Usually nobody knows. So I built a tool that finds out: It runs on MOSS-VL, open-weight 11B model (open source on GitHub: Upload a reference clip, it watches it frame by frame and reverse-engineers a generation prompt from what's actually in the video, not a guess. Refine it for a style, then generate something new from it. MOSS-VL is built for continuous video streams. Quantized versions deploy locally on a single RTX 4090, and it can be fine-tuned through LlamaFactory if you need it to understand something specific, like your own product's UI. I used the hosted API here, analyzing an uploaded clip instead of a live stream. Two ways to use it yourself: deploy it locally for real-time stream processing, or grab a free API key and use the hosted API on your own clips. API:

Manish Kumar Shah

65,991 次观看 • 22 天前

Get any camera move you want, using just your phone. Frame the shot, hit record, and move your camera exactly how you want it - a simple pan, a push-in and swirl, whatever. Load that clip into Agent One and tell it what you want in the shot. Your recorded video drives the camera move, Agent One runs it through Seedance, and you sit back and watch. Pro tip - match your phone frame to your first generated frame. The closer it lines up, the better it lands. Watch the video to see exactly how we did it.

Get any camera move you want, using just your phone. Frame the shot, hit record, and move your camera exactly how you want it - a simple pan, a push-in and swirl, whatever. Load that clip into Agent One and tell it what you want in the shot. Your recorded video drives the camera move, Agent One runs it through Seedance, and you sit back and watch. Pro tip - match your phone frame to your first generated frame. The closer it lines up, the better it lands. Watch the video to see exactly how we did it.

Invideo

30,820 次观看 • 2 个月前

i built a tool that lets you clone ANY video with AI saw a movie scene you want to recreate? a commercial? a music video? just upload it to this tool and get the exact structured prompt to generate it in sora 2 you no longer need to guess how to describe what you want to generate. show the tool the reference and it engineers the prompt for you. the tool analyzes: - camera movements and angles - lighting and color grading - scene composition and timing then converts everything into sora-optimized prompt structure this is how you recreate any visual style without prompt engineering experience RT + reply 'TOOL' and i'll send you access (must follow so i can dm)

i built a tool that lets you clone ANY video with AI saw a movie scene you want to recreate? a commercial? a music video? just upload it to this tool and get the exact structured prompt to generate it in sora 2 you no longer need to guess how to describe what you want to generate. show the tool the reference and it engineers the prompt for you. the tool analyzes: - camera movements and angles - lighting and color grading - scene composition and timing then converts everything into sora-optimized prompt structure this is how you recreate any visual style without prompt engineering experience RT + reply 'TOOL' and i'll send you access (must follow so i can dm)

Miko

43,121 次观看 • 11 个月前

Here are the floor votes from the last day McConnell voted. As you can see in both clips, he never appears in the camera frame. A lot of times senators just come to the Senate floor door, give a thumb up or thumb down and leave, but if you don’t have the mental capacity of voting, someone can easily roll you in, tell you to give a thumb up or thumb down, then roll you out.

Here are the floor votes from the last day McConnell voted. As you can see in both clips, he never appears in the camera frame. A lot of times senators just come to the Senate floor door, give a thumb up or thumb down and leave, but if you don’t have the mental capacity of voting, someone can easily roll you in, tell you to give a thumb up or thumb down, then roll you out.

Desirée Townsend

50,492 次观看 • 2 个月前