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Machine Learning Guide

MLA 027 AI Video End-to-End Workflow

Machine Learning Guide

OCDevel

Artificial, Introduction, Learning, Courses, Technology, Ml, Intelligence, Ai, Machine, Education

4.9848 Ratings

🗓️ 14 July 2025

⏱️ 72 minutes

🧾️ Download transcript

Summary

How to maintain character consistency, style consistency, etc in an AI video. Prosumers can use Google Veo 3’s "High-Quality Chaining" for fast social media content. Indie filmmakers can achieve narrative consistency by combining Midjourney V7 for style, Kling for lip-synced dialogue, and Runway Gen-4 for camera control, while professional studios gain full control with a layered ComfyUI pipeline to output multi-layer EXR files for standard VFX compositing.

Links

AI Audio Tool Selection

  • Music: Use Suno for complete songs or Udio for high-quality components for professional editing.
  • Sound Effects: Use ElevenLabs' SFX for integrated podcast production or SFX Engine for large, licensed asset libraries for games and film.
  • Voice: ElevenLabs gives the most realistic voice output. Murf.ai offers an all-in-one studio for marketing, and Play.ht has a low-latency API for developers.
  • Open-Source TTS: For local use, StyleTTS 2 generates human-level speech, Coqui's XTTS-v2 is best for voice cloning from minimal input, and Piper TTS is a fast, CPU-friendly option.

I. Prosumer Workflow: Viral Video

Goal: Rapidly produce branded, short-form video for social media. This method bypasses Veo 3's weaker native "Extend" feature.

  • Toolchain
    • Image Concept: GPT-4o (API: GPT-Image-1) for its strong prompt adherence, text rendering, and conversational refinement.
    • Video Generation: Google Veo 3 for high single-shot quality and integrated ambient audio.
    • Soundtrack: Udio for creating unique, "viral-style" music.
    • Assembly: CapCut for its standard short-form editing features.
  • Workflow
    1. Create Character Sheet (GPT-4o): Generate a primary character image with a detailed "locking" prompt, then use conversational follow-ups to create variations (poses, expressions) for visual consistency.
    2. Generate Video (Veo 3): Use "High-Quality Chaining."
      • Clip 1: Generate an 8s clip from a character sheet image.
      • Extract Final Frame: Save the last frame of Clip 1.
      • Clip 2: Use the extracted frame as the image input for the next clip, using a "this then that" prompt to continue the action. Repeat as needed.
    3. Create Music (Udio): Use Manual Mode with structured prompts ([Genre: ...], [Mood: ...]) to generate and extend a music track.
    4. Final Edit (CapCut): Assemble clips, layer the Udio track over Veo's ambient audio, add text, and use "Auto Captions." Export in 9:16.

II. Indie Filmmaker Workflow: Narrative Shorts

Goal: Create cinematic short films with consistent characters and storytelling focus, using a hybrid of specialized tools.

  • Toolchain
    • Visual Foundation: Midjourney V7 to establish character and style with --cref and --sref parameters.
    • Dialogue Scenes: Kling for its superior lip-sync and character realism.
    • B-Roll/Action: Runway Gen-4 for its Director Mode camera controls and Multi-Motion Brush.
    • Voice Generation: ElevenLabs for emotive, high-fidelity voices.
    • Edit & Color: DaVinci Resolve for its integrated edit, color, and VFX suite and favorable cost model.
  • Workflow
    1. Create Visual Foundation (Midjourney V7): Generate a "hero" character image. Use its URL with --cref --cw 100 to create consistent character poses and with --sref to replicate the visual style in other shots. Assemble a reference set.
    2. Create Dialogue Scenes (ElevenLabs -> Kling):
      • Generate the dialogue track in ElevenLabs and download the audio.
      • In Kling, generate a video of the character from a reference image with their mouth closed.
      • Use Kling's "Lip Sync" feature to apply the ElevenLabs audio to the neutral video for a perfect match.
    3. Create B-Roll (Runway Gen-4): Use reference images from Midjourney. Apply precise camera moves with Director Mode or add localized, layered motion to static scenes with the Multi-Motion Brush.
    4. Assemble & Grade (DaVinci Resolve): Edit clips and audio on the Edit page. On the Color page, use node-based tools to match shots from Kling and Runway, then apply a final creative look.

III. Professional Studio Workflow: Full Control

Goal: Achieve absolute pixel-level control, actor likeness, and integration into standard VFX pipelines using an open-source, modular approach.

  • Toolchain
    • Core Engine: ComfyUI with Stable Diffusion models (e.g., SD3, FLUX).
    • VFX Compositing: DaVinci Resolve (Fusion page) for node-based, multi-layer EXR compositing.
  • Control Stack & Workflow
    1. Train Character LoRA: Train a custom LoRA on a 15-30 image dataset of the actor in ComfyUI to ensure true likeness.
    2. Build ComfyUI Node Graph: Construct a generation pipeline in this order:
      • Loaders: Load base model, custom character LoRA, and text prompts (with LoRA trigger word).
      • ControlNet Stack: Chain multiple ControlNets to define structure (e.g., OpenPose for skeleton, Depth map for 3D layout).
      • IPAdapter-FaceID: Use the Plus v2 model as a final reinforcement layer to lock facial identity before animation.
      • AnimateDiff: Apply deterministic camera motion using Motion LoRAs (e.g., v2_lora_PanLeft.ckpt).
      • KSampler -> VAE Decode: Generate the image sequence.
    3. Export Multi-Layer EXR: Use a node like mrv2SaveEXRImage to save the output as an EXR sequence (.exr). Configure for a professional pipeline: 32-bit float, linear color space, and PIZ/ZIP lossless compression. This preserves render passes (diffuse, specular, mattes) in a single file.
    4. Composite in Fusion: In DaVinci Resolve, import the EXR sequence. Use Fusion's node graph to access individual layers, allowing separate adjustments to elements like color, highlights, and masks before integrating the AI asset into a final shot with a background plate.

Transcript

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0:00.0

Welcome back to Machine Learning Applied. This is the last segment of the mini series on multimedia generative AI, image generation, video generation, and stringing them all together.

0:13.9

This is the most important episode, and it's the one that I'm going to be linking out on socials because it's very practical. It teaches you

0:20.9

how to make a movie or an ad using the tools that we've discussed. The last two episodes had

0:26.5

sample workflows, total theoreticals. This episode has three real workflows, workflows used by

0:33.4

professionals in the wild. In fact, I might go back and remove the sample workflows from the

0:38.3

previous episodes. I think they were more distracting than helpful. If you land on this episode

0:43.4

first and you haven't listened to the last two episodes, those are what are these tools and how

0:49.7

do they compare? So you only need to listen to them if you don't know what the value prop difference is

0:55.1

between GPT40 versus Mid Journey or VO3 versus SORA. And especially if you don't know much about

1:02.5

the stable diffusion ecosystem because Workflow 3 will be stable diffusion heavy. And you'll

1:08.6

want some background information on stable diffusion.

1:18.0

So prompt engineering, my friends, I'm afraid I had to exclude it. The content of this episode got too long. And there's something in my DNA that requires miniseries to be in

1:22.7

threes, as well as I don't want to dilute this podcast series too much. The whole series about

1:26.8

AI and machine learning. I don't want a pigeonhole this podcast series too much. The whole series about AI and machine learning.

1:28.0

I don't want a pigeonhole multimedia for too long.

1:30.8

So I had to exclude it.

1:32.3

I'm so sorry.

1:33.4

I may do a super episode on prompt engineering across various domains in the future.

1:39.4

This would include obviously image and video generation

1:42.3

because prompt engineering for image and video gen is the

1:45.7

most important where prompt engineering is applicable is very nuanced and specific the types of words

1:51.8

and flags and parameters you use but i would also maybe include prompt engineering for vibe coding

...

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