
- Prompt
- Remove the highlighted object from the scene

- Prompt
- Remove the highlighted object from the scene

- Prompt
- Remove the highlighted object from the scene

- Prompt
- Remove the highlighted object from the scene
๐ฏ What does this model do?
This LoRA removes highlighted objects from images and fills the area naturally with contextually appropriate content. Simply mark the object you want to remove, and the model will erase it seamlessly.
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ โ
โ ๐ ๐ณ [๐] ๐ณ ๐ โ Highlighted object
โ โ โ gets removed
โ ๐ ๐ณ ~~~~ ๐ณ ๐ โ and filled naturally
โ โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Perfect for cleaning up photos, removing distractions, and creating seamless backgrounds.
๐ผ๏ธ Examples
| Input (with highlighted object) | Output (object removed) |
|---|---|
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๐ Quick Start
Prompt
Remove the highlighted object from the scene
Highlighting Requirements
- Mark the object to remove with a visible highlight/mask
- The highlight should clearly cover the object boundaries
- Works best with distinct, isolated objects
๐ป Usage
Try it Live on fal.ai
โถ๏ธ Open Playground
With fal.ai SDK
import fal_client
def on_queue_update(update):
if isinstance(update, fal_client.InProgress):
for log in update.logs:
print(log["message"])
result = fal_client.subscribe(
"fal-ai/flux-2-klein/4b/base/edit/lora",
arguments={
"prompt": "Remove the highlighted object from the scene",
"model_name": None,
"loras": [{
"path": "https://huggingface.co/ilkerzgi/flux-object-remove-lora/resolve/main/flux-object-remove-lora.safetensors",
"scale": 1.1
}],
"embeddings": [],
"image_urls": ["https://your-image-with-highlighted-object.png"]
},
with_logs=True,
on_queue_update=on_queue_update,
)
print(result)
๐ฆ Model Files
| File | Use Case |
|---|---|
flux-object-remove-lora.safetensors |
fal.ai |
kDEkt5q7tDLKOpQJIVMPx_pytorch_lora_weights_comfy_converted.safetensors |
ComfyUI |
๐ Training Details
Click to expand
Dataset
- Size: 100 image pairs
- Content: Diverse scenes with objects to remove including:
- People: individuals, groups in various settings
- Objects: furniture, vehicles, electronics
- Animals: pets, wildlife
- Text: signs, watermarks, logos
- Nature: plants, debris, unwanted elements
- Highlighting: Objects marked for removal
- Aspect ratios: Various (1:1, 16:9, 9:16, 4:3, 3:4, etc.)
Training
- Base Model: FLUX.2-Klein 4B
- Platform: fal.ai
- Method: LoRA training
- Steps: 4000
- Learning Rate: 0.00005
๐ฎ Use Cases
- Photo Cleanup: Remove photobombers, trash, or unwanted objects
- Product Photography: Clean backgrounds for e-commerce
- Real Estate: Remove furniture or personal items from property photos
- Social Media: Create cleaner, more focused compositions
โ ๏ธ Limitations
- Works best with clearly highlighted/masked objects
- Very large objects may leave visible artifacts
- Complex backgrounds may require multiple passes
- Reflections and shadows of removed objects may persist
๐ License
Model tree for fal/flux-2-klein-4B-object-remove-lora
Base model
black-forest-labs/FLUX.2-klein-4B







