Flux 1 Dev With Realism Lora Create Cinematic AI Video Scenes - Tutorial Guide
TLDRThis tutorial introduces an updated workflow for generating cinematic AI video scenes using Flux, a realistic AI model. It guides through downloading and implementing the FP8 checkpoint versions for simplified integration with Comfy UI. The video demonstrates creating AI scenery from images, using the new Flux Realism Lora models for photorealistic styles, and refining images with segmentation detailers. The process includes generating scenes with character descriptions, refining artifacts, and upscaling for final output, showcasing a workflow that's efficient and effective for AI video creation.
Takeaways
- 😀 The tutorial is an update on using the Flux image generation workflow with a focus on integrating it with Comfy UI.
- 📂 Download the FP8 checkpoint versions of AI model files for Flux, which are a compressed version of the developer models, resulting in a 17 GB file size.
- 📁 Save the downloaded checkpoint into the Comfy UI models folder, specifically the checkpoints subfolder, similar to the process with Stable Diffusion 1.5 or SDXL.
- ⚙️ Ensure the CFG in the sampling steps custom nodes is set to one to prepare for using the FP8 checkpoint versions.
- 🎨 The tutorial covers the use of Flux AI for creating AI video scenery from images, including characters, backgrounds, and various scenarios.
- 🔍 An update on Flux Realism Lora models is available on Hugging Face, which works with Flux developer models to produce photorealistic image styles.
- 🖼️ The workflow involves setting aspect ratios, using the K sampler, and custom notes to create conditions for image generation with Flux.
- 🔍 The process includes refining images using segmentation detailers to enhance characters and remove artifacts, followed by upscaling for the final result.
- 📹 The tutorial demonstrates creating AI short stories and videos, emphasizing the importance of character interaction and emotion in AI videos.
- 📝 The script provides an example of a text prompt format for generating AI characters and scenes, including character descriptions and event locations.
- 🔄 The workflow is noted to be faster and smoother than the Flux developer FP16, requiring less memory consumption and allowing for up to four images per batch.
- 🛠️ The tutorial concludes with a mention of future videos that will cover editing image scenes for more consistent characters and fixed faces.
Q & A
What is the latest update from The Comfy UI team regarding the flux image generation workflow?
-The latest update allows for a simpler way to implement flux into Comfy UI by downloading the FP8 checkpoint versions of AI model files, which are a compressed version of the flux developer versions, resulting in a 17 GB file size.
Where should the downloaded FP8 checkpoint versions be saved in the Comfy UI models folder?
-The FP8 checkpoint versions should be saved in the 'checkpoints' subfolder within the Comfy UI models folder.
What setting in the sampling steps custom nodes should be adjusted to use the FP8 checkpoint versions?
-The setting in the sampling steps custom nodes that should be adjusted is the CFG, which needs to be set to one.
Why are FP8 checkpoint versions being used according to the video?
-FP8 checkpoint versions are used to create AI video scenery from images, allowing for the generation of ongoing stories with photorealistic image styles using flux AI and cling AI.
What is the significance of the new flux realism Laura models from xlabs AI?
-The new flux realism Laura models work with the flux developer models to produce photorealistic image styles, enhancing the quality of the generated images.
How does the workflow differ when using the checkpoint models compared to previous flux workflows?
-The workflow is simplified, using the checkpoint Laura models and the CLIP text, with no need for negative CLIP text, making it more streamlined and similar to stable diffusion and sdxl text to image workflows.
What is the recommended batch size when generating images for each Q prompt in the workflow?
-It is recommended to set the batch size to one or two images for each Q prompt in the workflow.
What is the role of the K sampler in the flux workflow?
-The K sampler is used to set the CFG and steps for the image generation process, with the CFG set to 0.1 and steps ranging from 20 to 30, depending on preference.
How is the segmentation detailer used in the workflow to enhance the images?
-The segmentation detailer is used to refine the character, excluding areas like the hands if not needed, to get rid of artifacts and improve the skin or plastic texture of the character.
What is the purpose of using sdxl checkpoint models to refine the character in the workflow?
-Sdxl checkpoint models are used to refine the character as a whole image segment region, improving the overall quality and consistency of the character in the final image.
How does the tutorial guide address the issue of clothing and face inconsistencies in generated images?
-The tutorial mentions that clothing and face inconsistencies are common and will be addressed in a future tutorial, where techniques like face swap or in-paint will be discussed to fix these issues.
Outlines
🔧 Flux Image Generation Workflow Update
The script discusses updates to the Flux image generation workflow, particularly the integration with Comfy UI. It highlights the availability of FP8 checkpoint versions of AI model files, which consolidate the C text and unet models into a single 17 GB file. Users are instructed to download and save these files in the checkpoints folder within Comfy UI's models directory. The script also covers the use of these FP8 models to create AI video scenery from images, the introduction of the first Flux Laura models for photorealistic image styles, and the new workflow for setting aspect ratios and using the K sampler. The process involves generating images with the checkpoint models, refining them with segmentation detailers, and upscaling for the final output.
🎨 Creating AI Short Stories and Videos
This paragraph details the creative process of producing AI short stories and videos using the updated Flux workflow. It describes how the author used the workflow to create interactive and emotional AI characters, moving away from static and robotic portrayals. The author shares their experience with testing and refining AI images into videos, the time investment involved, and the use of text prompts to guide the generation process. The paragraph also touches on the use of chatbots and AI tools like Llama 3 or Chat GPT for story and character creation, and the importance of well-defined text prompts for generating realistic and consistent character images.
🛠️ Refining and Upscaling AI Generated Images
The final paragraph focuses on the technical aspects of refining and upscaling AI-generated images to create more consistent characters and fixed facial features. It discusses the use of segmentation detailers to address issues like plastic-looking skin and the process of upscaling to improve image quality. The author acknowledges the challenges of maintaining consistent clothing styles and facial features across generated images and promises a future tutorial on how to address these issues. The paragraph concludes with a demonstration of the generated image scenes and an invitation for viewers to explore AI video creation, inspiring them to use Flux for realistic image generation.
Mindmap
Keywords
💡Flux Image Generation Workflow
💡Comfy UI
💡FP8 Checkpoint
💡Stable Diffusion 1.5
💡CFG
💡Flux Realism Laura Models
💡Aspect Ratios
💡K Sampler
💡Batch Size
💡Segmentation Detailer
💡Cling AI
Highlights
Introduction of a simplified workflow to implement Flux into Comfy UI.
Availability of FP8 checkpoint versions of AI model files for Flux.
Compression of C text models and U-Net models into a single 17 GB checkpoint file.
Instructions on saving the checkpoint file into the Comfy UI models folder.
Requirement to set the CFG in sampling steps to one for readiness.
Use of FP8 developer versions for creating AI video scenery from images.
Introduction of Flux Realism Lora models for photorealistic image styles.
Integration of Lora models with Flux developer models.
Setting aspect ratios using the SDXL landscape ratios.
Differences in workflow compared to previous Flux AI and SDXL methods.
Utilization of the K sampler with CFG set to 0.1 and customizable step numbers.
Technique of generating one or two images per batch for each text prompt.
Use of image sharpening and detailers for enhancing character images.
Refinement process using segmentation detailer and SDXL checkpoint models.
Upscaling images for final results and saving in the output folder.
Creating AI short stories and videos using the described workflow.
Importance of testing and trial and error in AI image to video conversion.
Efficiency of the new workflow compared to the Flux developer FP16.
Capability of Flux to follow complex text prompts with multiple objects.
Future tutorial on editing image scenes for consistency and fixing character issues.
Encouragement for users to create AI movies and music videos using Flux.