Delete app.py

app.py

@@ -1,467 +0,0 @@
-import os
-import json
-import time
-import requests
-import random
-import numpy as np
-import spaces
-import torch
-from PIL import Image
-import gradio as gr
-
-# --- Qwen Specific Imports ---
-from diffusers import FlowMatchEulerDiscreteScheduler
-# Assuming the qwenimage package is available in the environment
-from qwenimage.pipeline_qwenimage_edit_plus import QwenImageEditPlusPipeline
-from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
-from qwenimage.qwen_fa3_processor import QwenDoubleStreamAttnProcessorFA3
-
-from huggingface_hub import (
-    hf_hub_download,
-    HfFileSystem,
-    ModelCard
-)
-
-from typing import Iterable
-from gradio.themes import Soft
-from gradio.themes.utils import colors, fonts, sizes
-
-# =========================================
-# THEME CONFIGURATION
-# =========================================
-
-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()
-
-# =========================================
-# LORA CONFIGURATION (The "DLC" List)
-# =========================================
-
-loras = [
-    {
-        "image": "https://huggingface.co/autoweeb/Qwen-Image-Edit-2509-Photo-to-Anime/resolve/main/images/example.jpg", 
-        "title": "Photo to Anime",
-        "repo": "autoweeb/Qwen-Image-Edit-2509-Photo-to-Anime",
-        "weights": "Qwen-Image-Edit-2509-Photo-to-Anime_000001000.safetensors",
-        "trigger_word": "Transform into anime"
-    },
-    {
-        "image": "https://huggingface.co/dx8152/Qwen-Edit-2509-Multiple-angles/resolve/main/images/example.jpg", 
-        "title": "Multiple Angles",
-        "repo": "dx8152/Qwen-Edit-2509-Multiple-angles",
-        "weights": "镜头转换.safetensors",
-        "trigger_word": "Rotate camera"
-    },
-    {
-        "image": "https://huggingface.co/dx8152/Qwen-Image-Edit-2509-Light_restoration/resolve/main/images/example.jpg", 
-        "title": "Light Restoration",
-        "repo": "dx8152/Qwen-Image-Edit-2509-Light_restoration",
-        "weights": "移除光影.safetensors",
-        "trigger_word": "Remove shadows"
-    },
-    {
-        "image": "https://huggingface.co/dx8152/Qwen-Image-Edit-2509-Relight/resolve/main/images/example.jpg", 
-        "title": "Relight",
-        "repo": "dx8152/Qwen-Image-Edit-2509-Relight",
-        "weights": "Qwen-Edit-Relight.safetensors",
-        "trigger_word": "Relight the image"
-    },
-    {
-        "image": "https://huggingface.co/dx8152/Qwen-Edit-2509-Multi-Angle-Lighting/resolve/main/images/example.jpg",
-        "title": "Multi-Angle Lighting",
-        "repo": "dx8152/Qwen-Edit-2509-Multi-Angle-Lighting",
-        "weights": "多角度灯光-251116.safetensors",
-        "trigger_word": "Light source from"
-    },
-    {
-        "image": "https://huggingface.co/tlennon-ie/qwen-edit-skin/resolve/main/images/example.jpg",
-        "title": "Edit Skin",
-        "repo": "tlennon-ie/qwen-edit-skin",
-        "weights": "qwen-edit-skin_1.1_000002750.safetensors",
-        "trigger_word": "Make skin details prominent"
-    },
-    {
-        "image": "https://huggingface.co/lovis93/next-scene-qwen-image-lora-2509/resolve/main/images/example.jpg",
-        "title": "Next Scene",
-        "repo": "lovis93/next-scene-qwen-image-lora-2509",
-        "weights": "next-scene_lora-v2-3000.safetensors",
-        "trigger_word": "Next scene cinematic"
-    },
-    {
-        "image": "https://huggingface.co/vafipas663/Qwen-Edit-2509-Upscale-LoRA/resolve/main/images/example.jpg",
-        "title": "Upscale Image",
-        "repo": "vafipas663/Qwen-Edit-2509-Upscale-LoRA",
-        "weights": "qwen-edit-enhance_64-v3_000001000.safetensors",
-        "trigger_word": "Upscale the image"
-    },
-]
-
-# =========================================
-# MODEL SETUP
-# =========================================
-
-dtype = torch.bfloat16
-device = "cuda" if torch.cuda.is_available() else "cpu"
-base_model = "Qwen/Qwen-Image-Edit-2509"
-
-print(f"Loading {base_model} pipeline...")
-
-# Initialize Pipeline
-pipe = QwenImageEditPlusPipeline.from_pretrained(
-    base_model,
-    transformer=QwenImageTransformer2DModel.from_pretrained(
-        "linoyts/Qwen-Image-Edit-Rapid-AIO",
-        subfolder='transformer',
-        torch_dtype=dtype,
-        device_map=device
-    ),
-    torch_dtype=dtype,
-).to(device)
-
-# Apply Optimization
-try:
-    print("Applying FA3 Processor...")
-    pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
-    print("Optimization applied successfully.")
-except Exception as e:
-    print(f"Optimization warning: {e}. Continuing with standard pipeline.")
-
-MAX_SEED = np.iinfo(np.int32).max
-
-# =========================================
-# HELPER FUNCTIONS
-# =========================================
-
-class calculateDuration:
-    def __init__(self, activity_name=""):
-        self.activity_name = activity_name
-
-    def __enter__(self):
-        self.start_time = time.time()
-        return self
-    
-    def __exit__(self, exc_type, exc_value, traceback):
-        self.end_time = time.time()
-        self.elapsed_time = self.end_time - self.start_time
-        if self.activity_name:
-            print(f"Elapsed time for {self.activity_name}: {self.elapsed_time:.6f} seconds")
-        else:
-            print(f"Elapsed time: {self.elapsed_time:.6f} seconds")
-
-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)
-        
-    # Ensure dimensions are multiples of 8 (Qwen requirement)
-    new_width = (new_width // 8) * 8
-    new_height = (new_height // 8) * 8
-    
-    return new_width, new_height
-
-def update_selection(evt: gr.SelectData, current_prompt):
-    selected_lora = loras[evt.index]
-    trigger = selected_lora.get("trigger_word", "")
-    new_placeholder = f"Type a prompt for {selected_lora['title']}"
-    lora_repo = selected_lora["repo"]
-    updated_text = f"### Selected: [{lora_repo}](https://huggingface.co/{lora_repo}) ✅"
-    
-    # Append trigger word to prompt if not present
-    new_prompt = current_prompt
-    if trigger and trigger not in current_prompt:
-        if current_prompt:
-            new_prompt = f"{trigger} {current_prompt}"
-        else:
-            new_prompt = trigger
-
-    return (
-        gr.update(placeholder=new_placeholder, value=new_prompt),
-        updated_text,
-        evt.index
-    )
-
-def check_custom_model(link):
-    if link.startswith("https://"):
-        if "huggingface.co" in link:
-            parts = link.split("huggingface.co/")
-            repo_part = parts[1].strip()
-            return repo_part, link
-    return link, link
-
-# =========================================
-# INFERENCE LOGIC
-# =========================================
-
-@spaces.GPU(duration=60)
-def run_lora(
-    input_image, 
-    prompt, 
-    steps, 
-    guidance_scale, 
-    selected_index, 
-    randomize_seed, 
-    seed, 
-    custom_lora_path,
-    progress=gr.Progress(track_tqdm=True)
-):
-    if input_image is None:
-        raise gr.Error("Input image is required for Qwen Image Edit.")
-
-    # 1. Clean up previous LoRAs
-    with calculateDuration("Unloading LoRA"):
-        try:
-            pipe.unload_lora_weights()
-        except Exception:
-            pass 
-    
-    # 2. Determine which LoRA to load
-    lora_repo = None
-    weight_name = None
-    adapter_name = "default"
-
-    if custom_lora_path and custom_lora_path.strip() != "":
-        repo, link = check_custom_model(custom_lora_path)
-        lora_repo = repo
-        print(f"Attempting to load custom LoRA: {lora_repo}")
-    elif selected_index is not None and selected_index < len(loras):
-        selected_lora = loras[selected_index]
-        lora_repo = selected_lora["repo"]
-        weight_name = selected_lora.get("weights", None)
-        print(f"Loading Gallery LoRA: {selected_lora['title']}")
-    else:
-        print("No LoRA selected. Running Base Model.")
-
-    # 3. Load LoRA
-    if lora_repo:
-        with calculateDuration(f"Loading LoRA weights"):
-            try:
-                pipe.load_lora_weights(
-                    lora_repo, 
-                    weight_name=weight_name, 
-                    adapter_name=adapter_name
-                )
-                pipe.set_adapters([adapter_name], adapter_weights=[1.0])
-            except Exception as e:
-                print(f"Error loading LoRA: {e}")
-                gr.Warning(f"Failed to load LoRA {lora_repo}. Generating with base model.")
-
-    # 4. Prepare Seed
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-    generator = torch.Generator(device=device).manual_seed(seed)
-
-    # 5. Process Image
-    original_image = input_image.convert("RGB")
-    width, height = update_dimensions_on_upload(original_image)
-    
-    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"
-
-    # 6. Generate
-    with calculateDuration("Generating image"):
-        final_image = pipe(
-            image=original_image,
-            prompt=prompt,
-            negative_prompt=negative_prompt,
-            height=height,
-            width=width,
-            num_inference_steps=int(steps),
-            true_cfg_scale=guidance_scale, 
-            generator=generator,
-        ).images[0]
-        
-    return final_image, seed, gr.update(visible=False)
-
-def add_custom_lora(custom_path):
-    if not custom_path:
-        return gr.update(visible=False), None, "No custom LoRA"
-    
-    repo, _ = check_custom_model(custom_path)
-    card_html = f'''
-    <div class="custom_lora_card" style="border:1px solid #ccc; padding:10px; border-radius:8px; margin-top:10px;">
-        <h3>Custom LoRA Active</h3>
-        <code>{repo}</code>
-    </div>
-    '''
-    return gr.update(visible=True, value=card_html), None, repo
-
-def remove_custom_lora():
-    return gr.update(visible=False), None, ""
-
-# =========================================
-# UI CONSTRUCTION
-# =========================================
-
-css = '''
-#gen_btn{height: 100%}
-#gen_column{align-self: stretch}
-#title{text-align: center}
-#title h1{font-size: 3em; display:inline-flex; align-items:center}
-#title img{width: 100px; margin-right: 0.5em}
-#gallery .grid-wrap{height: 15vh}
-#lora_list{background: var(--block-background-fill);padding: 0 1em .3em; font-size: 90%}
-.card_internal{display: flex;height: 100px;margin-top: .5em}
-.card_internal img{margin-right: 1em}
-#progress{height:30px}
-'''
-
-with gr.Blocks(delete_cache=(60, 60)) as demo:
-    title = gr.HTML(
-        """<h1>Qwen Image Edit 2.5 DLC 🧪</h1>""",
-        elem_id="title",
-    )
-    
-    selected_index = gr.State(None)
-    custom_lora_state = gr.State("") 
-
-    with gr.Row():
-        with gr.Column(scale=3):
-            prompt = gr.Textbox(label="Edit Prompt", lines=2, placeholder="✦︎ Select a LoRA from the gallery below and describe the edit...")
-            
-        with gr.Column(scale=1, elem_id="gen_column"):
-            generate_button = gr.Button("Generate", variant="primary", elem_id="gen_btn")
-            
-    with gr.Row():
-        input_image = gr.Image(label="Upload Input Image (Required)", type="pil", height=300)
-            
-    with gr.Row():
-        with gr.Column():
-            selected_info = gr.Markdown("### No LoRA Selected (Base Model)")
-            
-            gallery = gr.Gallery(
-                [(item.get("image", ""), item["title"]) for item in loras],
-                label="Available LoRAs",
-                allow_preview=False,
-                columns=4,
-                elem_id="gallery",
-            )
-            
-            with gr.Group():
-                custom_lora_input = gr.Textbox(label="Load Custom LoRA", placeholder="Enter HuggingFace Repo ID (e.g. autoweeb/Qwen-Image-Edit-...)")
-                gr.Markdown("[See compatible Qwen LoRAs](https://huggingface.co/models?other=base_model:adapter:Qwen/Qwen-Image-Edit-2509)", elem_id="lora_list")
-            
-            custom_lora_info = gr.HTML(visible=False)
-            remove_custom_btn = gr.Button("Remove Custom LoRA", visible=False)
-
-        with gr.Column():
-            progress_bar = gr.Markdown(elem_id="progress", visible=False)
-            result = gr.Image(label="Edited Image", format="png", height=630)
-
-    with gr.Row():
-        with gr.Accordion("Advanced Settings", open=False):
-            with gr.Column():
-                with gr.Row():
-                    guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=10.0, step=0.1, value=1.0)
-                    steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=4)
-                
-                with gr.Row():
-                    randomize_seed = gr.Checkbox(True, label="Randomize seed")
-                    seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, randomize=True)
-
-    # Event Wiring
-    gallery.select(
-        update_selection,
-        inputs=[prompt],
-        outputs=[prompt, selected_info, selected_index]
-    )
-
-    custom_lora_input.submit(
-        add_custom_lora,
-        inputs=[custom_lora_input],
-        outputs=[custom_lora_info, selected_index, custom_lora_state]
-    ).then(
-        lambda: gr.update(visible=True), outputs=[remove_custom_btn]
-    )
-
-    remove_custom_btn.click(
-        remove_custom_lora,
-        outputs=[custom_lora_info, selected_index, custom_lora_state]
-    ).then(
-        lambda: gr.update(visible=False), outputs=[remove_custom_btn]
-    ).then(
-        lambda: "", outputs=[custom_lora_input]
-    )
-
-    gr.on(
-        triggers=[generate_button.click, prompt.submit],
-        fn=run_lora,
-        inputs=[input_image, prompt, steps, guidance_scale, selected_index, randomize_seed, seed, custom_lora_state],
-        outputs=[result, seed, progress_bar]
-    )
-
-demo.queue()
-demo.launch(theme=orange_red_theme, css=css, mcp_server=True, ssr_mode=False, show_error=True)