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Running
on
Zero
| import gradio as gr | |
| import numpy as np | |
| import spaces | |
| import torch | |
| import random | |
| from PIL import Image | |
| from diffusers import FluxKontextPipeline | |
| from diffusers.utils import load_image | |
| MAX_SEED = np.iinfo(np.int32).max | |
| pipe = FluxKontextPipeline.from_pretrained( | |
| "black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16 | |
| ).to("cuda") | |
| def infer( | |
| input_image, | |
| prompt, | |
| seed=42, | |
| randomize_seed=False, | |
| guidance_scale=2.5, | |
| steps=28, | |
| progress=gr.Progress(track_tqdm=True), | |
| ): | |
| """ | |
| Edit an image using AI based on text instructions. | |
| Args: | |
| input_image (optional): Path to the image file to edit (if None, generates from text only) | |
| prompt (required): Text describing what to change (e.g. "remove glasses", "add a hat", "change background to beach") | |
| seed (optional): Random seed for reproducibility (default: 42) | |
| randomize_seed (optional): Use random seed instead of fixed seed (default: False) | |
| guidance_scale (optional): How closely to follow the prompt, 1.0-10.0 (default: 2.5) | |
| steps (optional): Number of generation steps, 1-30 (default: 28) | |
| progress (optional): Gradio progress tracker (automatically provided) | |
| Returns: | |
| tuple: (edited_image, seed_used, gradio_update) | |
| Example: | |
| infer(input_image="/path/to/photo.jpg", prompt="Add sunglasses") | |
| """ | |
| if randomize_seed: | |
| seed = random.randint(0, MAX_SEED) | |
| if input_image: | |
| input_image = input_image.convert("RGB") | |
| image = pipe( | |
| image=input_image, | |
| prompt=prompt, | |
| guidance_scale=guidance_scale, | |
| num_inference_steps=steps, | |
| generator=torch.Generator().manual_seed(seed), | |
| ).images[0] | |
| else: | |
| image = pipe( | |
| prompt=prompt, | |
| guidance_scale=guidance_scale, | |
| num_inference_steps=steps, | |
| generator=torch.Generator().manual_seed(seed), | |
| ).images[0] | |
| return image, seed, gr.update(visible=True) | |
| css = """ | |
| #col-container { | |
| margin: 0 auto; | |
| max-width: 960px; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| with gr.Column(elem_id="col-container"): | |
| gr.Markdown( | |
| f"""# FLUX.1 Kontext [dev] | |
| Image editing and manipulation model guidance-distilled from FLUX.1 Kontext [pro], [[blog]](https://bfl.ai/announcements/flux-1-kontext-dev) [[model]](https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev) | |
| """ | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| input_image = gr.Image(label="Upload the image for editing", type="pil") | |
| with gr.Row(): | |
| prompt = gr.Text( | |
| label="Prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter your prompt for editing (e.g., 'Remove glasses', 'Add a hat')", | |
| container=False, | |
| ) | |
| run_button = gr.Button("Run", 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(): | |
| result = gr.Image(label="Result", 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=[result, seed, reuse_button], | |
| ) | |
| reuse_button.click(fn=lambda image: image, inputs=[result], outputs=[input_image]) | |
| demo.launch(mcp_server=True) | |