Trained a Kotext LoRA that transforms Google Earth screenshots into realistic drone photography - mostly for architecture design context visualisation purposes.

Hey everyone! We're releasing a beta version of our new ZenCtrl Inpainting Playground and would love your feedback! You can try the demo here : https://huggingface.co/spaces/fotographerai/Zenctrl-Inpaint You can: Upload any subject image (e.g., a sofa, chair, etc.) Sketch a rough placement region Type a short prompt like "add the sofa" → and the model will inpaint it directly into the background, keeping lighting and shadows consistent. i added some examples on how it could be used We're especially looking for feedback on: Visual realism Context placement if you will like this would be useful in production and in comfyui? This is our first release, trained mostly on interior scenes and rigid objects. We're not yet releasing the weights(we want to hear your feedbacks first), but once we train on a larger dataset, we plan to open them. Please, Let me know: Is the result convincing? Would you use this for product placement / design / creative work? Any weird glitches? Hope you like it

Workflow links

Standard Model:

My Patreon (free!!) - https://www.patreon.com/posts/flux-modular-wf-134530869

CivitAI - https://civitai.com/models/1129063?modelVersionId=2029206

Openart - https://openart.ai/workflows/tenofas/flux-modular-wf/bPXJFFmNBpgoBt4Bd1TB

GGUF Models:

My Patreon (free!!) - https://www.patreon.com/posts/flux-modular-wf-134530869

CivitAI - https://civitai.com/models/1129063?modelVersionId=2029241

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The new Flux Modular WF v6.0 is a ComfyUI workflow that works like a "Swiss army knife" and is based on FLUX Dev.1 model by Black Forest Labs.

The workflow comes in two different edition:

1) the standard model edition that uses the BFL original model files (you can set the weight_dtype in the “Load Diffusion Model” node to fp8 which will lower the memory usage if you have less than 24Gb Vram and get Out Of Memory errors);

2) the GGUF model edition that uses the GGUF quantized files and allows you to choose the best quantization for your GPU's needs.

Press "1", "2" and "3" to quickly navigate to the main areas of the workflow.

You will need around 14 custom nodes (but probably a few of them are already installed in your ComfyUI). I tried to keep the number of custom nodes to the bare minimum, but the ComfyUI core nodes are not enough to create workflow of this complexity. I am also trying to keep only Custom Nodes that are regularly updated.

Once you installed the missing (if any) custom nodes, you will need to config the workflow as follow:

1) load an image (like the COmfyUI's standard example image ) in all three the "Load Image" nodes at the top of the frontend of the wf (Primary image, second and third image).

2) update all the "Load diffusion model", "DualCLIP LOader", "Load VAE", "Load Style Model", "Load CLIP Vision" or "Load Upscale model". Please press "3" and read carefully the red "READ CAREFULLY!" note for 1st time use in the workflow!

In the INSTRUCTIONS note you will find all the links to the model and files you need if you don't have them already.

This workflow let you use Flux model in any way it is possible:

1) Standard txt2img or img2img generation;

2) Inpaint/Outpaint (with Flux Fill)

3) Standard Kontext workflow (with up to 3 different images)

4) Multi-image Kontext workflow (from a single loaded image you will get 4 images consistent with the loaded one);

5) Depth or Canny;

6) Flux Redux (with up to 3 different images) - Redux works with the "Flux basic wf".

You can use different modules in the workflow:

1) Img2img module, that will allow you to generate from an image instead that from a textual prompt;

2) HiRes Fix module;

3) FaceDetailer module for improving the quality of image with faces;

4) Upscale module using the Ultimate SD Upscaler (you can select your preferred upscaler model) - this module allows you to enhance the skin detail for portrait image, just turn On the Skin enhancer in the Upscale settings;

5) Overlay settings module: will write on the image output the main settings you used to generate that image, very useful for generation tests;

6) Saveimage with metadata module, that will save the final image including all the metadata in the png file, very useful if you plan to upload the image in sites like CivitAI.

You can now also save each module's output image, for testing purposes, just enable what you want to save in the "Save WF Images".

Before starting the image generation, please remember to set the Image Comparer choosing what will be the image A and the image B!

Once you have choosen the workflow settings (image size, steps, Flux guidance, sampler/scheduler, random or fixed seed, denoise, detail daemon, LoRAs and batch size) you can press "Run" and start generating you artwork!

Post Production group is always enabled, if you do not want any post-production to be applied, just leave the default values.

I'm open-sourcing my production management tool SHOTBUDDY, built specifically for AI video creation workflows. Get it here on GitHub.

Here's what it does:

Core Functionality:

• Project Setup & Organization: Drag and drop images to automatically generate shot numbers, thumbnails, and organized folder structures in the background. It automatically renames messy AI-generated files (those "generation_img2343_heres-half-your-prompt" nightmares)
• Version Management: Replace old generations with new ones while automatically archiving previous versions throughout the entire pipeline

After trying out traditional film production tools like Autodesk Flow/Shotgrid, I decided they are way to expensive and break down with AI workflows that generate large amounts of versions.

I hope this is valuable to you!

- Albert

Totally newbie here. It all started discovering still images that were screaming to be animated. So after a lot of exploration I ended landing in a wan web generator: Half of the times flf2v fails miserably but if you play the dice consistently some are decent. Or glitchy decent and everything in between. So everytime I get a good looking one, I capture the last fotogram, choose a new still to keep the morphing animation and let it flow playing the wan roulette once more. Insert coin.

Yeah, its glithy as hell, the context/coherence is mostly lost and most of the transitions are obvious, but it´s kind of addicting to see where the animation will go in every generation. I also find a bit boring all that perfect veo 3, real as life shoots. At least here theres a infinite space to explore, between pure fantasy, geometry the glitchness and to witness how the model is going to interpolate 2 totally non related frames It takes a good amount of imagination to do it with any consistency. SO kudos to Wan. I also used Luma in some shoots and probably some other freemium model, so finally its a collage.

In the process I have been devouring everything about comfy, nodes, ksamplers, eulers, attention masks and all that jazz and Im hooked. There´s a 3060 arriving home this week so I can properly keep exploring all this space.

And yeah, I know there´s the wan logo appearing nonstop. The providers wanted me to pay extra for downloading non watermarked videos... lol

I wonder how sophisticated their workflows are because it still seems like a ton of work just to ripoff other people’s videos.

I tend to use multiple models and feed one to the other, problem being there is lots of waste in unloading and loading the models into RAM and VRAM.

Made some very simple stack style nodes to be able to efficiently batch images that can easily get fed into another workflow later, along with the prompts used in the first workflow.

If there's any interest I may make it a bit better and less slapped together.

https://preview.redd.it/oxwwxycmuzdf1.png?width=2048&format=png&auto=webp&s=1cbc7d5e3a79d3a9abefdd6c2d8affe40e745f20

https://preview.redd.it/59ftxmmyuzdf1.png?width=2048&format=png&auto=webp&s=d8611d10fc765836570d6f5df437e8e4c6413ae5

Flux Kontext Dev lacks some capabilities compared to ChatGPT.

So I've built a simple open-source tool to generate image pairs for Kontext training.

This first version uses LetzAI and OpenAI APIs for Image Generation and Editing.

I'm currently using it myself to create a Kontext Lora for isometric tiny worlds, something Kontext struggles with out of the box, but ChatGPT is very good at.

Hope some people will find this useful ✌️