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| import os | |
| import gc | |
| import gradio as gr | |
| import numpy as np | |
| import spaces | |
| import torch | |
| import random | |
| import io | |
| # torch.cuda.empty_cache() | |
| from io import BytesIO | |
| from PIL import Image | |
| from PIL import Image | |
| from typing import Iterable | |
| from gradio.themes import Soft | |
| from gradio.themes.utils import colors, fonts, sizes | |
| colors.orange_red = colors.Color( | |
| name="orange_red", | |
| c50="#FFF0E5", | |
| c100="#FFE0CC", | |
| c200="#FFC299", | |
| c300="#FFA366", | |
| c400="#FF8533", | |
| c500="#FF4500", | |
| c600="#E63E00", | |
| c700="#CC3700", | |
| c800="#B33000", | |
| c900="#992900", | |
| c950="#802200", | |
| ) | |
| class OrangeRedTheme(Soft): | |
| def __init__( | |
| self, | |
| *, | |
| primary_hue: colors.Color | str = colors.gray, | |
| secondary_hue: colors.Color | str = colors.orange_red, | |
| 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)", | |
| button_primary_background_fill_dark="linear-gradient(90deg, *secondary_600, *secondary_700)", | |
| button_primary_background_fill_hover_dark="linear-gradient(90deg, *secondary_500, *secondary_600)", | |
| button_secondary_text_color="black", | |
| button_secondary_text_color_hover="white", | |
| button_secondary_background_fill="linear-gradient(90deg, *primary_300, *primary_300)", | |
| button_secondary_background_fill_hover="linear-gradient(90deg, *primary_400, *primary_400)", | |
| button_secondary_background_fill_dark="linear-gradient(90deg, *primary_500, *primary_600)", | |
| button_secondary_background_fill_hover_dark="linear-gradient(90deg, *primary_500, *primary_500)", | |
| slider_color="*secondary_500", | |
| slider_color_dark="*secondary_600", | |
| block_title_text_weight="600", | |
| block_border_width="3px", | |
| block_shadow="*shadow_drop_lg", | |
| button_primary_shadow="*shadow_drop_lg", | |
| button_large_padding="11px", | |
| color_accent_soft="*primary_100", | |
| block_label_background_fill="*primary_200", | |
| ) | |
| orange_red_theme = OrangeRedTheme() | |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| print("CUDA_VISIBLE_DEVICES=", os.environ.get("CUDA_VISIBLE_DEVICES")) | |
| print("torch.__version__ =", torch.__version__) | |
| print("Using device:", device) | |
| 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 | |
| import base64 | |
| dtype = torch.bfloat16 | |
| pipe = QwenImageEditPlusPipeline.from_pretrained( | |
| "Qwen/Qwen-Image-Edit-2511", | |
| transformer=QwenImageTransformer2DModel.from_pretrained( | |
| "linoyts/Qwen-Image-Edit-Rapid-AIO", | |
| subfolder='transformer', | |
| torch_dtype=dtype, | |
| device_map='cuda' | |
| ), | |
| torch_dtype=dtype | |
| ).to(device) | |
| try: | |
| pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3()) | |
| print("Flash Attention 3 Processor set successfully.") | |
| except Exception as e: | |
| print(f"Warning: Could not set FA3 processor: {e}") | |
| MAX_SEED = np.iinfo(np.int32).max | |
| ADAPTER_SPECS = { | |
| "Multiple-Angles": { | |
| "repo": "dx8152/Qwen-Edit-2509-Multiple-angles", | |
| "weights": "镜头转换.safetensors", | |
| "adapter_name": "multiple-angles" | |
| }, | |
| "Photo-to-Anime": { | |
| "repo": "autoweeb/Qwen-Image-Edit-2509-Photo-to-Anime", | |
| "weights": "Qwen-Image-Edit-2509-Photo-to-Anime_000001000.safetensors", | |
| "adapter_name": "photo-to-anime" | |
| }, | |
| "Anime-V2": { | |
| "repo": "prithivMLmods/Qwen-Image-Edit-2511-Anime", | |
| "weights": "Qwen-Image-Edit-2511-Anime-2000.safetensors", | |
| "adapter_name": "anime-v2" | |
| }, | |
| "Light-Migration": { | |
| "repo": "dx8152/Qwen-Edit-2509-Light-Migration", | |
| "weights": "参考色调.safetensors", | |
| "adapter_name": "light-migration" | |
| }, | |
| "Upscaler": { | |
| "repo": "starsfriday/Qwen-Image-Edit-2511-Upscale2K", | |
| "weights": "qwen_image_edit_2511_upscale.safetensors", | |
| "adapter_name": "upscale-2k" | |
| }, | |
| "Style-Transfer": { | |
| "repo": "zooeyy/Style-Transfer", | |
| "weights": "Style Transfer-Alpha-V0.1.safetensors", | |
| "adapter_name": "style-transfer" | |
| }, | |
| "Manga-Tone": { | |
| "repo": "nappa114514/Qwen-Image-Edit-2509-Manga-Tone", | |
| "weights": "tone001.safetensors", | |
| "adapter_name": "manga-tone" | |
| }, | |
| "Anything2Real": { | |
| "repo": "lrzjason/Anything2Real_2601", | |
| "weights": "anything2real_2601.safetensors", | |
| "adapter_name": "anything2real" | |
| }, | |
| "Fal-Multiple-Angles": { | |
| "repo": "fal/Qwen-Image-Edit-2511-Multiple-Angles-LoRA", | |
| "weights": "qwen-image-edit-2511-multiple-angles-lora.safetensors", | |
| "adapter_name": "fal-multiple-angles" | |
| }, | |
| "Polaroid-Photo": { | |
| "repo": "prithivMLmods/Qwen-Image-Edit-2511-Polaroid-Photo", | |
| "weights": "Qwen-Image-Edit-2511-Polaroid-Photo.safetensors", | |
| "adapter_name": "polaroid-photo" | |
| }, | |
| "Unblur-Anything": { | |
| "repo": "prithivMLmods/Qwen-Image-Edit-2511-Unblur-Upscale", | |
| "weights": "Qwen-Image-Edit-Unblur-Upscale_15.safetensors", | |
| "adapter_name": "unblur-anything" | |
| }, | |
| "Midnight-Noir-Eyes-Spotlight": { | |
| "repo": "prithivMLmods/Qwen-Image-Edit-2511-Midnight-Noir-Eyes-Spotlight", | |
| "weights": "Qwen-Image-Edit-2511-Midnight-Noir-Eyes-Spotlight.safetensors", | |
| "adapter_name": "midnight-noir-eyes-spotlight" | |
| }, | |
| "Hyper-Realistic-Portrait": { | |
| "repo": "prithivMLmods/Qwen-Image-Edit-2511-Hyper-Realistic-Portrait", | |
| "weights": "HRP_20.safetensors", | |
| "adapter_name": "hyper-realistic-portrait" | |
| }, | |
| "Ultra-Realistic-Portrait": { | |
| "repo": "prithivMLmods/Qwen-Image-Edit-2511-Ultra-Realistic-Portrait", | |
| "weights": "URP_20.safetensors", | |
| "adapter_name": "ultra-realistic-portrait" | |
| }, | |
| "Pixar-Inspired-3D": { | |
| "repo": "prithivMLmods/Qwen-Image-Edit-2511-Pixar-Inspired-3D", | |
| "weights": "PI3_20.safetensors", | |
| "adapter_name": "pi3" | |
| }, | |
| "Noir-Comic-Book": { | |
| "repo": "prithivMLmods/Qwen-Image-Edit-2511-Noir-Comic-Book-Panel", | |
| "weights": "Noir-Comic-Book-Panel_20.safetensors", | |
| "adapter_name": "ncb" | |
| }, | |
| "Any-light": { | |
| "repo": "lilylilith/QIE-2511-MP-AnyLight", | |
| "weights": "QIE-2511-AnyLight_.safetensors", | |
| "adapter_name": "any-light" | |
| }, | |
| "Studio-DeLight": { | |
| "repo": "prithivMLmods/QIE-2511-Studio-DeLight", | |
| "weights": "QIE-2511-Studio-DeLight-5000.safetensors", | |
| "adapter_name": "studio-delight" | |
| }, | |
| "Cinematic-FlatLog": { | |
| "repo": "prithivMLmods/QIE-2511-Cinematic-FlatLog-Control", | |
| "weights": "QIE-2511-Cinematic-FlatLog-Control-3200.safetensors", | |
| "adapter_name": "flat-log" | |
| }, | |
| "Guided-Head-Face-Swap": { | |
| "repo": "prithivMLmods/QIE-2511-Guided-Head-Face-Swap", | |
| "weights": "QIE-2511-Guided-Head-Face-Swap-3000.safetensors", | |
| "adapter_name": "head-face-swap" | |
| }, | |
| } | |
| LOADED_ADAPTERS = set() | |
| def update_dimensions_on_upload(image): | |
| if image is None: | |
| return 1024, 1024 | |
| original_width, original_height = image.size | |
| if original_width > original_height: | |
| new_width = 1024 | |
| aspect_ratio = original_height / original_width | |
| new_height = int(new_width * aspect_ratio) | |
| else: | |
| new_height = 1024 | |
| aspect_ratio = original_width / original_height | |
| new_width = int(new_height * aspect_ratio) | |
| new_width = (new_width // 8) * 8 | |
| new_height = (new_height // 8) * 8 | |
| return new_width, new_height | |
| def infer( | |
| images, | |
| prompt, | |
| lora_adapter, | |
| seed, | |
| randomize_seed, | |
| guidance_scale, | |
| steps, | |
| progress=gr.Progress(track_tqdm=True) | |
| ): | |
| gc.collect() | |
| torch.cuda.empty_cache() | |
| if not images: | |
| raise gr.Error("Please upload at least one image to edit.") | |
| pil_images = [] | |
| if images is not None: | |
| for item in images: | |
| try: | |
| if isinstance(item, tuple) or isinstance(item, list): | |
| path_or_img = item[0] | |
| else: | |
| path_or_img = item | |
| if isinstance(path_or_img, str): | |
| pil_images.append(Image.open(path_or_img).convert("RGB")) | |
| elif isinstance(path_or_img, Image.Image): | |
| pil_images.append(path_or_img.convert("RGB")) | |
| else: | |
| pil_images.append(Image.open(path_or_img.name).convert("RGB")) | |
| except Exception as e: | |
| print(f"Skipping invalid image item: {e}") | |
| continue | |
| if not pil_images: | |
| raise gr.Error("Could not process uploaded images.") | |
| spec = ADAPTER_SPECS.get(lora_adapter) | |
| if not spec: | |
| raise gr.Error(f"Configuration not found for: {lora_adapter}") | |
| adapter_name = spec["adapter_name"] | |
| if adapter_name not in LOADED_ADAPTERS: | |
| print(f"--- Downloading and Loading Adapter: {lora_adapter} ---") | |
| try: | |
| pipe.load_lora_weights( | |
| spec["repo"], | |
| weight_name=spec["weights"], | |
| adapter_name=adapter_name | |
| ) | |
| LOADED_ADAPTERS.add(adapter_name) | |
| except Exception as e: | |
| raise gr.Error(f"Failed to load adapter {lora_adapter}: {e}") | |
| else: | |
| print(f"--- Adapter {lora_adapter} is already loaded. ---") | |
| pipe.set_adapters([adapter_name], 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" | |
| width, height = update_dimensions_on_upload(pil_images[0]) | |
| try: | |
| result_image = pipe( | |
| image=pil_images, | |
| prompt=prompt, | |
| negative_prompt=negative_prompt, | |
| height=height, | |
| width=width, | |
| num_inference_steps=steps, | |
| generator=generator, | |
| true_cfg_scale=guidance_scale, | |
| ).images[0] | |
| img= result_image | |
| buffered = io.BytesIO() | |
| img.save(buffered, format="WEBP") | |
| img_base64 = base64.b64encode(buffered.getvalue()).decode("utf-8") | |
| img_data_url = f"data:image/webp;base64,{img_base64}" | |
| print(img_data_url) | |
| return result_image, img_data_url | |
| except Exception as e: | |
| raise e | |
| finally: | |
| gc.collect() | |
| torch.cuda.empty_cache() | |
| def infer_example(images, prompt, lora_adapter): | |
| if not images: | |
| return None, 0 | |
| if isinstance(images, str): | |
| images_list = [images] | |
| else: | |
| images_list = images | |
| result, seed = infer( | |
| images=images_list, | |
| prompt=prompt, | |
| lora_adapter=lora_adapter, | |
| seed=0, | |
| randomize_seed=True, | |
| guidance_scale=1.0, | |
| steps=4 | |
| ) | |
| return result, seed | |
| css=""" | |
| #col-container { | |
| margin: 0 auto; | |
| max-width: 1000px; | |
| } | |
| #main-title h1 {font-size: 2.3em !important;} | |
| """ | |
| with gr.Blocks() as demo: | |
| with gr.Column(elem_id="col-container"): | |
| gr.Markdown("# **Qwen-Image-Edit-2511-LoRAs-Fast**", elem_id="main-title") | |
| gr.Markdown("Perform diverse image edits using specialized [LoRA](https://huggingface.co/models?other=base_model:adapter:Qwen/Qwen-Image-Edit-2511) adapters. Upload one or more images.") | |
| with gr.Row(equal_height=True): | |
| with gr.Column(): | |
| images = gr.Gallery( | |
| label="Upload Images", | |
| type="filepath", | |
| columns=2, | |
| rows=1, | |
| height=300, | |
| allow_preview=True | |
| ) | |
| prompt = gr.Text( | |
| label="Edit Prompt", | |
| show_label=True, | |
| placeholder="e.g., transform into anime..", | |
| ) | |
| run_button = gr.Button("Edit Image", variant="primary") | |
| with gr.Column(): | |
| output_image = gr.Image(label="Output Image", interactive=False, format="png", height=363) | |
| with gr.Row(): | |
| lora_adapter = gr.Dropdown( | |
| label="Choose Editing Style", | |
| choices=list(ADAPTER_SPECS.keys()), | |
| value="Photo-to-Anime" | |
| ) | |
| with gr.Accordion("Advanced Settings", open=False, visible=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/B.jpg"], "Transform into anime.", "Photo-to-Anime"], | |
| [["examples/A.jpeg"], "Rotate the camera 45 degrees to the right.", "Multiple-Angles"], | |
| [["examples/U.jpg"], "Upscale this picture to 4K resolution.", "Upscaler"], | |
| [["examples/L1.jpg", "examples/L2.jpg"], "Refer to the color tone, remove the original lighting from Image 1, and relight Image 1 based on the lighting and color tone of Image 2.", "Light-Migration"], | |
| [["examples/P1.jpg", "examples/P2.jpg"], "Make the person in image 1 do the exact same pose of the person in image 2. Changing the style and background of the image of the person in image 1 is undesirable, so don't do it.", "Any-Pose"], | |
| ], | |
| inputs=[images, prompt, lora_adapter], | |
| outputs=[output_image, seed], | |
| fn=infer_example, | |
| cache_examples=False, | |
| label="Examples" | |
| ) | |
| gr.Markdown("[*](https://huggingface.co/spaces/prithivMLmods/Qwen-Image-Edit-2511-LoRAs-Fast)This is still an experimental Space for Qwen-Image-Edit-2511.") | |
| run_button.click( | |
| fn=infer, | |
| inputs=[images, prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps], | |
| outputs=[output_image, seed] | |
| ) | |
| if __name__ == "__main__": | |
| demo.queue(max_size=30).launch(css=css, theme=orange_red_theme, mcp_server=True, ssr_mode=False, show_error=True) |