File size: 12,083 Bytes
d681ba2 487476b d681ba2 8c4f04a 487476b d681ba2 46016bd 3cac608 46016bd 0cc736e d681ba2 d56905a 1b717b8 82e63f8 71befc6 0cc736e 8a504ac d681ba2 df27955 48707c1 46016bd 48707c1 82e63f8 551779e 71befc6 48707c1 71befc6 8aea897 48707c1 8aea897 71befc6 48707c1 71befc6 487476b 71befc6 b2b24ef 82e63f8 d681ba2 3cac608 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 |
---
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
- Watermark-Remover
base_model: black-forest-labs/FLUX.1-Kontext-dev
instance_prompt: >-
[photo content], remove any watermark text or logos from the image while
preserving the background, texture, lighting, and overall realism. Ensure the
edited areas blend seamlessly with surrounding details, leaving no visible
traces of watermark removal.
license: apache-2.0
pipeline_tag: image-to-image
library_name: diffusers
language:
- en
---
# **Kontext-Watermark-Remover**
<Gallery />
The Kontext-Watermark-Remover is an adapter for black-forest-lab's FLUX.1-Kontext-dev, designed to precisely remove watermarks and textual content from images while maintaining the original image quality and context. The model was trained on 150 image pairs (75 start images and 75 end images) to ensure accurate and artifact-free watermark removal.
> [!note]
[photo content], remove any watermark text or logos from the image while preserving the background, texture, lighting, and overall realism. Ensure the edited areas blend seamlessly with surrounding details, leaving no visible traces of watermark removal.
---
## **Sample Inferences : Demo**
<table style="width:100%; border-collapse:collapse;">
<tr>
<td style="width:50%; text-align:center;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/dp8EVqVH4WeKg6WkbbVMX.webp"
alt="watermark-the-milk-poster" style="width:100%; height:auto;"/>
</td>
<td style="width:50%; text-align:center;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/yju8FXDqOezu6gjOFEiUw.webp"
alt="watermark-the-milk-poster" style="width:100%; height:auto;"/>
</td>
</tr>
</table>
<table style="width:100%; border-collapse:collapse;">
<tr>
<td style="width:50%; text-align:center; vertical-align:middle;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/HSZO9JojEPuEXWmWHGXK2.png"
alt="22" style="width:100%; height:auto;"/>
</td>
<td style="width:50%; text-align:center; vertical-align:middle;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/iP4YB-lmnvMb8hvdnGaVY.webp"
alt="2222" style="width:100%; height:auto;"/>
</td>
</tr>
</table>
<table style="width:100%; border-collapse:collapse;">
<tr>
<td style="width:50%; text-align:center; vertical-align:middle;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/oANOI60kg5DcurcJFFtRO.png"
alt="image" style="width:100%; height:auto;"/>
</td>
<td style="width:50%; text-align:center; vertical-align:middle;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/mmmUTBMRpcdgfoPqZWlxF.webp"
alt="2234" style="width:100%; height:auto;"/>
</td>
</tr>
</table>
<table style="width:100%; border-collapse:collapse;">
<tr>
<td style="width:50%; text-align:center; vertical-align:middle;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/LIZZDkD74YOhsQswZ_baO.jpeg"
alt="signature-logo" style="width:100%; height:auto;"/>
</td>
<td style="width:50%; text-align:center; vertical-align:middle;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/RTa3OxGXI5FrNbtyG75E_.webp"
alt="555555555" style="width:100%; height:auto;"/>
</td>
</tr>
</table>
<table style="width:100%; border-collapse:collapse;">
<tr>
<td style="width:50%; text-align:center; vertical-align:middle;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/vX3rLx6gMzEJJu1pfERWD.jpeg"
alt="wmr-west-before1.2b600d3b" style="width:100%; height:auto;"/>
</td>
<td style="width:50%; text-align:center; vertical-align:middle;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/86MrcB1Y9pOzTW16n-0-T.webp"
alt="555" style="width:100%; height:auto;"/>
</td>
</tr>
</table>
---
# **Quick start with diffusers🧨**
### **Required Packages**
```
!pip install diffusers torch gradio transformers
!pip install pillow gradio-imageslider huggingface_hub
!pip install sentencepiece spaces peft torchvision accelerate
```
## **Run Demo**
```py
import os
import gradio as gr
import numpy as np
import spaces
import torch
import random
from PIL import Image
from typing import Iterable
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image
from huggingface_hub import hf_hub_download
from gradio_imageslider import ImageSlider
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# --- Main Model Initialization ---
MAX_SEED = np.iinfo(np.int32).max
pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16).to("cuda")
# --- Load New Adapter ---
pipe.load_lora_weights("prithivMLmods/Kontext-Watermark-Remover", weight_name="Kontext-Watermark-Remover.safetensors", adapter_name="watermark_remover")
@spaces.GPU
def infer(input_image, prompt, seed=42, randomize_seed=False, guidance_scale=2.5, steps=28, progress=gr.Progress(track_tqdm=True)):
"""
Perform image editing, returning a pair for the ImageSlider.
"""
if not input_image:
raise gr.Error("Please upload an image for editing.")
pipe.set_adapters(["watermark_remover"], adapter_weights=[1.0])
if randomize_seed:
seed = random.randint(0, MAX_SEED)
original_image = input_image.copy().convert("RGB")
image = pipe(
image=original_image,
prompt=prompt,
guidance_scale=guidance_scale,
width = original_image.size[0],
height = original_image.size[1],
num_inference_steps=steps,
generator=torch.Generator().manual_seed(seed),
).images[0]
return (original_image, image), seed, gr.Button(visible=True)
css="""
#col-container {
margin: 0 auto;
max-width: 960px;
}
#main-title h1 {font-size: 2.1em !important;}
"""
with gr.Blocks(css=css) as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown("# **Photo-Mate-i2i: Watermark Remover**", elem_id="main-title")
gr.Markdown("Image manipulation with FLUX.1 Kontext. This demo focuses on watermark removal.")
with gr.Row():
with gr.Column():
input_image = gr.Image(label="Upload Image with Watermark", type="pil", height="300")
with gr.Row():
prompt = gr.Text(
label="Edit Prompt",
show_label=False,
max_lines=1,
placeholder="e.g., 'Remove the watermark'",
container=False,
value="[photo content], remove any watermark text or logos from the image while preserving the background, texture, lighting, and overall realism. Ensure the edited areas blend seamlessly with surrounding details, leaving no visible traces of watermark removal."
)
run_button = gr.Button("Run", variant="primary", scale=0)
with gr.Accordion("Advanced Settings", open=False):
seed = gr.Slider(
label="Seed",
minimum=0,
maximum=MAX_SEED,
step=1,
value=0,
)
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
guidance_scale = gr.Slider(
label="Guidance Scale",
minimum=1,
maximum=10,
step=0.1,
value=2.5,
)
steps = gr.Slider(
label="Steps",
minimum=1,
maximum=30,
value=28,
step=1
)
with gr.Column():
output_slider = ImageSlider(label="Before / After", show_label=False, interactive=False)
reuse_button = gr.Button("Reuse this image", visible=False)
gr.on(
triggers=[run_button.click, prompt.submit],
fn=infer,
inputs=[input_image, prompt, seed, randomize_seed, guidance_scale, steps],
outputs=[output_slider, seed, reuse_button]
)
reuse_button.click(
fn=lambda images: images[1] if isinstance(images, (list, tuple)) and len(images) > 1 else images,
inputs=[output_slider],
outputs=[input_image]
)
demo.launch(mcp_server=True, ssr_mode=False, show_error=True)
```
---
## Parameter Settings
| Setting | Value |
| ------------------------ | ------------------------ |
| Module Type | Adapter |
| Base Model | FLUX.1 Kontext Dev - fp8 |
| Trigger Words | [photo content], remove any watermark text or logos from the image while preserving the background, texture, lighting, and overall realism. Ensure the edited areas blend seamlessly with surrounding details, leaving no visible traces of watermark removal. |
| Image Processing Repeats | 50 |
| Epochs | 25 |
| Save Every N Epochs | 1 |
Labeling: florence-community/Florence-2-large-ft (natural language & English)
Total Images Used for Training : 150 Image Pairs (75 Start, 75 End)
## Training Parameters
| Setting | Value |
| --------------------------- | --------- |
| Seed | - |
| Clip Skip | - |
| Text Encoder LR | 0.00001 |
| UNet LR | 0.00005 |
| LR Scheduler | constant |
| Optimizer | AdamW8bit |
| Network Dimension | 64 |
| Network Alpha | 32 |
| Gradient Accumulation Steps | - |
## Label Parameters
| Setting | Value |
| --------------- | ----- |
| Shuffle Caption | - |
| Keep N Tokens | - |
## Advanced Parameters
| Setting | Value |
| ------------------------- | ----- |
| Noise Offset | 0.03 |
| Multires Noise Discount | 0.1 |
| Multires Noise Iterations | 10 |
| Conv Dimension | - |
| Conv Alpha | - |
| Batch Size | - |
| Steps | 2900 & 400(warm up) |
| Sampler | euler |
---
## **Sample Inferences : Inference Providers**
---
## Trigger words
You should use `[photo content]` to trigger the image generation.
You should use `remove any watermark text or logos from the image while preserving the background` to trigger the image generation.
You should use `texture` to trigger the image generation.
You should use `lighting` to trigger the image generation.
You should use `and overall realism. Ensure the edited areas blend seamlessly with surrounding details` to trigger the image generation.
You should use `leaving no visible traces of watermark removal.` to trigger the image generation.
## Download model
[Download](/prithivMLmods/Kontext-Watermark-Remover/tree/main) them in the Files & versions tab. |