| 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 gradio.themes import Soft
|
| from gradio.themes.utils import colors, fonts, sizes
|
|
|
| colors.steel_blue = colors.Color(
|
| name="steel_blue",
|
| c50="#EBF3F8",
|
| c100="#D3E5F0",
|
| c200="#A8CCE1",
|
| c300="#7DB3D2",
|
| c400="#529AC3",
|
| c500="#4682B4",
|
| c600="#3E72A0",
|
| c700="#36638C",
|
| c800="#2E5378",
|
| c900="#264364",
|
| c950="#1E3450",
|
| )
|
|
|
| class SteelBlueTheme(Soft):
|
| def __init__(
|
| self,
|
| *,
|
| primary_hue: colors.Color | str = colors.gray,
|
| secondary_hue: colors.Color | str = colors.steel_blue,
|
| neutral_hue: colors.Color | str = colors.slate,
|
| text_size: sizes.Size | str = sizes.text_lg,
|
| font: fonts.Font | str | Iterable[fonts.Font | str] = (
|
| fonts.GoogleFont("Outfit"), "Arial", "sans-serif",
|
| ),
|
| font_mono: fonts.Font | str | Iterable[fonts.Font | str] = (
|
| fonts.GoogleFont("IBM Plex Mono"), "ui-monospace", "monospace",
|
| ),
|
| ):
|
| super().__init__(
|
| primary_hue=primary_hue,
|
| secondary_hue=secondary_hue,
|
| neutral_hue=neutral_hue,
|
| text_size=text_size,
|
| font=font,
|
| font_mono=font_mono,
|
| )
|
| super().set(
|
| background_fill_primary="*primary_50",
|
| background_fill_primary_dark="*primary_900",
|
| body_background_fill="linear-gradient(135deg, *primary_200, *primary_100)",
|
| body_background_fill_dark="linear-gradient(135deg, *primary_900, *primary_800)",
|
| button_primary_text_color="white",
|
| button_primary_text_color_hover="white",
|
| button_primary_background_fill="linear-gradient(90deg, *secondary_500, *secondary_600)",
|
| button_primary_background_fill_hover="linear-gradient(90deg, *secondary_600, *secondary_700)",
|
| slider_color="*secondary_500",
|
| slider_color_dark="*secondary_600",
|
| block_title_text_weight="600",
|
| block_border_width="3px",
|
| block_shadow="*shadow_drop_lg",
|
| )
|
|
|
| steel_blue_theme = SteelBlueTheme()
|
|
|
| from diffusers import FlowMatchEulerDiscreteScheduler
|
| from qwenimage.pipeline_qwenimage_edit_plus import QwenImageEditPlusPipeline
|
| from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
|
| from qwenimage.qwen_fa3_processor import QwenDoubleStreamAttnProcessorFA3
|
|
|
| dtype = torch.bfloat16
|
| device = "cuda" if torch.cuda.is_available() else "cpu"
|
|
|
| pipe = QwenImageEditPlusPipeline.from_pretrained(
|
| "Qwen/Qwen-Image-Edit-2509",
|
| transformer=QwenImageTransformer2DModel.from_pretrained(
|
| "linoyts/Qwen-Image-Edit-Rapid-AIO",
|
| subfolder='transformer',
|
| torch_dtype=dtype,
|
| device_map='cuda'
|
| ),
|
| torch_dtype=dtype
|
| ).to(device)
|
|
|
| pipe.load_lora_weights("autoweeb/Qwen-Image-Edit-2509-Photo-to-Anime",
|
| weight_name="Qwen-Image-Edit-2509-Photo-to-Anime_000001000.safetensors",
|
| adapter_name="anime")
|
| pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Multiple-angles",
|
| weight_name="镜头转换.safetensors",
|
| adapter_name="multiple-angles")
|
| pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Light_restoration",
|
| weight_name="移除光影.safetensors",
|
| adapter_name="light-restoration")
|
| pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Relight",
|
| weight_name="Qwen-Edit-Relight.safetensors",
|
| adapter_name="relight")
|
|
|
| pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
|
| MAX_SEED = np.iinfo(np.int32).max
|
|
|
| @spaces.GPU
|
| def infer(
|
| input_image,
|
| prompt,
|
| lora_adapter,
|
| seed,
|
| randomize_seed,
|
| guidance_scale,
|
| steps,
|
| progress=gr.Progress(track_tqdm=True)
|
| ):
|
| if input_image is None:
|
| raise gr.Error("Please upload an image to edit.")
|
|
|
| if lora_adapter == "Photo-to-Anime":
|
| pipe.set_adapters(["anime"], adapter_weights=[1.0])
|
| elif lora_adapter == "Multiple-Angles":
|
| pipe.set_adapters(["multiple-angles"], adapter_weights=[1.0])
|
| elif lora_adapter == "Light-Restoration":
|
| pipe.set_adapters(["light-restoration"], adapter_weights=[1.0])
|
| elif lora_adapter == "Relight":
|
| pipe.set_adapters(["relight"], adapter_weights=[1.0])
|
|
|
| if randomize_seed:
|
| seed = random.randint(0, MAX_SEED)
|
|
|
| generator = torch.Generator(device=device).manual_seed(seed)
|
| negative_prompt = "worst quality, low quality, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, blurry"
|
|
|
| original_image = input_image.convert("RGB")
|
| width, height = original_image.size
|
|
|
| result = pipe(
|
| image=original_image,
|
| prompt=prompt,
|
| negative_prompt=negative_prompt,
|
| height=height,
|
| width=width,
|
| num_inference_steps=steps,
|
| generator=generator,
|
| true_cfg_scale=guidance_scale,
|
| ).images[0]
|
|
|
| return result, seed
|
|
|
| @spaces.GPU
|
| def infer_example(input_image, prompt, lora_adapter):
|
| input_pil = input_image.convert("RGB")
|
| guidance_scale = 1.0
|
| steps = 4
|
| result, seed = infer(input_pil, prompt, lora_adapter, 0, True, guidance_scale, steps)
|
| return result, seed
|
|
|
|
|
| css="""
|
| #col-container {
|
| margin: 0 auto;
|
| max-width: 960px;
|
| }
|
| #main-title h1 {font-size: 2.1em !important;}
|
| """
|
|
|
| with gr.Blocks(css=css, theme=steel_blue_theme) as demo:
|
| with gr.Column(elem_id="col-container"):
|
| gr.Markdown("# **Qwen-Image-Edit-2509-LoRAs-Fast**", elem_id="main-title")
|
| gr.Markdown("Perform diverse image edits using specialized LoRA adapters for the Qwen-Image-Edit model.")
|
|
|
| with gr.Row(equal_height=True):
|
| with gr.Column():
|
| input_image = gr.Image(label="Upload Image", type="pil")
|
|
|
| prompt = gr.Text(
|
| label="Edit Prompt",
|
| show_label=True,
|
| placeholder="e.g., transform into anime",
|
| )
|
|
|
| run_button = gr.Button("Run", variant="primary")
|
|
|
| with gr.Column():
|
| output_image = gr.Image(label="Output Image", interactive=False, format="png", height=290)
|
|
|
| with gr.Row():
|
| lora_adapter = gr.Dropdown(
|
| label="Choose Editing Style",
|
| choices=["Photo-to-Anime", "Multiple-Angles", "Light-Restoration", "Relight"],
|
| value="Photo-to-Anime"
|
| )
|
| 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=1.0, maximum=10.0, step=0.1, value=1.0)
|
| steps = gr.Slider(label="Inference Steps", minimum=1, maximum=50, step=1, value=4)
|
|
|
| gr.Examples(
|
| examples=[
|
| ["examples/1.jpg", "Transform into anime.", "Photo-to-Anime"],
|
| ["examples/5.jpg", "Remove shadows and relight the image using soft lighting.", "Light-Restoration"],
|
| ["examples/4.jpg", "Relight the image using soft, diffused lighting that simulates sunlight filtering.", "Relight"],
|
| ["examples/2.jpeg", "Move the camera left.", "Multiple-Angles"],
|
| ["examples/2.jpeg", "Move the camera right.", "Multiple-Angles"],
|
| ["examples/2.jpeg", "Rotate the camera 45 degrees to the left.", "Multiple-Angles"],
|
| ["examples/3.jpg", "Rotate the camera 45 degrees to the right.", "Multiple-Angles"],
|
| ["examples/3.jpg", "Switch the camera to a top-down view.", "Multiple-Angles"],
|
| ["examples/3.jpg", "Switch the camera to a wide-angle lens.", "Multiple-Angles"],
|
| ["examples/3.jpg", "Switch the camera to a close-up lens.", "Multiple-Angles"],
|
| ],
|
| inputs=[input_image, prompt, lora_adapter],
|
| outputs=[output_image, seed],
|
| fn=infer_example,
|
| cache_examples=False,
|
| label="Examples"
|
| )
|
|
|
| run_button.click(
|
| fn=infer,
|
| inputs=[input_image, prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps],
|
| outputs=[output_image, seed]
|
| )
|
|
|
| demo.launch(mcp_server=True, ssr_mode=False, show_error=True) |
