| 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)", |
| button_primary_background_fill_dark="linear-gradient(90deg, *secondary_600, *secondary_800)", |
| button_primary_background_fill_hover_dark="linear-gradient(90deg, *secondary_500, *secondary_500)", |
| 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", |
| ) |
|
|
| steel_blue_theme = SteelBlueTheme() |
|
|
| 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("torch.version.cuda =", torch.version.cuda) |
| print("cuda available:", torch.cuda.is_available()) |
| print("cuda device count:", torch.cuda.device_count()) |
| if torch.cuda.is_available(): |
| print("current device:", torch.cuda.current_device()) |
| print("device name:", torch.cuda.get_device_name(torch.cuda.current_device())) |
|
|
| 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 |
|
|
| 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.load_lora_weights("eigen-ai-labs/eigen-banana-qwen-image-edit", |
| weight_name="eigen-banana-qwen-image-edit-fp16-lora.safetensors", |
| adapter_name="eigen-banana") |
| pipe.load_lora_weights("tlennon-ie/qwen-edit-skin", |
| weight_name="qwen-edit-skin_1.1_000002750.safetensors", |
| adapter_name="edit-skin") |
| pipe.load_lora_weights("lovis93/next-scene-qwen-image-lora-2509", |
| weight_name="next-scene_lora-v2-3000.safetensors", |
| adapter_name="next-scene") |
|
|
| pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3()) |
| MAX_SEED = np.iinfo(np.int32).max |
|
|
| 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 |
|
|
| @spaces.GPU(duration=30) |
| 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]) |
| elif lora_adapter == "Eigen-Banana": |
| pipe.set_adapters(["eigen-banana"], adapter_weights=[1.0]) |
| elif lora_adapter == "Edit-Skin": |
| pipe.set_adapters(["edit-skin"], adapter_weights=[1.0]) |
| elif lora_adapter == "Next-Scene": |
| pipe.set_adapters(["next-scene"], 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 = update_dimensions_on_upload(original_image) |
|
|
| 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(duration=30) |
| 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](https://huggingface.co/models?other=base_model:adapter:Qwen/Qwen-Image-Edit-2509) adapters for the [Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit-2509) model.") |
|
|
| with gr.Row(equal_height=True): |
| with gr.Column(): |
| input_image = gr.Image(label="Upload Image", type="pil", height=290) |
| |
| 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=350) |
| |
| with gr.Row(): |
| lora_adapter = gr.Dropdown( |
| label="Choose Editing Style", |
| choices=["Photo-to-Anime", "Multiple-Angles", "Light-Restoration", "Relight", "Next-Scene", "Edit-Skin", "Eigen-Banana"], |
| 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/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", "Use a subtle golden-hour filter with smooth light diffusion.", "Relight"], |
| ["examples/2.jpeg", "Rotate the camera 45 degrees to the left.", "Multiple-Angles"], |
| ["examples/2.jpeg", "Switch the camera to a top-down right corner view.", "Multiple-Angles"], |
| ["examples/9.jpg", "The camera moves slightly forward as sunlight breaks through the clouds, casting a soft glow around the character's silhouette in the mist. Realistic cinematic style, atmospheric depth.", "Next-Scene"], |
| ["examples/8.jpg", "Make the subjects skin details more prominent and natural.", "Edit-Skin"], |
| ["examples/6.jpg", "Switch the camera to a bottom-up view.", "Multiple-Angles"], |
| ["examples/7.jpg", "Apply a vintage film aesthetic to the image, featuring a subtle desaturation of colors with a warm, golden-hour tone, introduce a fine and natural-looking film grain across the entire scene, gently reduce overall contrast for a softer appearance, and add a very faint, dark vignette to the edges to mimic an aged photographic print.", "Eigen-Banana"], |
| ["examples/6.jpg", "Rotate the camera 180 degrees upside down.", "Multiple-Angles"], |
| ["examples/4.jpg", "Rotate the camera 45 degrees to the right.", "Multiple-Angles"], |
| ["examples/4.jpg", "Switch the camera to a top-down view.", "Multiple-Angles"], |
| ["examples/4.jpg", "Switch the camera to a wide-angle 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) |
