Deploy Interior AI Designer

README.md

@@ -1,14 +1,65 @@
 ---
 title: Interior AI Designer
 emoji: 🏠
-colorFrom: green
-colorTo: blue
+colorFrom: blue
+colorTo: purple
 sdk: gradio
-sdk_version: 4.37.2
+sdk_version: 5.29.0
 app_file: app.py
-header: mini
-theme: bethecloud/storj_theme
-pinned: true
-license: apache-2.0
-short_description: Ikea could never
----
+pinned: false
+license: mit
+---
+
+# 🏠 Interior AI Designer
+
+Transform any room photo into beautiful interior designs with AI!
+
+## Features
+
+- **16 Design Styles**: From Minimalistic to Japanese to Cyberpunk
+- **Custom Prompts**: Add specific elements to your design
+- **Public API**: Call programmatically from any application
+
+## Quick Start
+
+1. Upload a room photo
+2. Select a design style
+3. Click "Redesign Interior"
+4. Download your transformed image!
+
+## API Usage
+
+```python
+from gradio_client import Client
+
+client = Client("YOUR_USERNAME/interior-ai-designer")
+result = client.predict(
+    image="room.jpg",
+    style="Scandinavian",
+    api_name="/redesign"
+)
+```
+
+## Available Styles
+
+- Minimalistic
+- Boho  
+- Farmhouse
+- Japanese
+- Scandinavian
+- Parisian
+- Hollywood
+- Beach
+- Matrix
+- And more...
+
+## Technology
+
+- Stable Diffusion 1.5
+- ControlNet (NormalBae)
+- Gradio
+
+---
+
+Made with ❤️ using Hugging Face Spaces
+

app.py

@@ -1,39 +1,29 @@
-prod = False
-port = 8080
-show_options = False
-if prod:
-    port = 8081
-    # show_options = False
+"""
+Interior AI Designer API
+Hugging Face Spaces deployment with public API endpoint
+"""
 
 import os
 import random
 import time
 import gradio as gr
 import numpy as np
-import spaces
-import imageio
-from huggingface_hub import HfApi
-import gc
+import spaces  # Required for Hugging Face Spaces GPU
 import torch
-import cv2
+import gc
 from PIL import Image
 from diffusers import (
     ControlNetModel,
     DPMSolverMultistepScheduler,
     StableDiffusionControlNetPipeline,
-    # StableDiffusionInpaintPipeline,
-    # AutoencoderKL,
 )
 from controlnet_aux_local import NormalBaeDetector
 
 MAX_SEED = np.iinfo(np.int32).max
-API_KEY = os.environ.get("API_KEY", None)
-# os.environ['HF_HOME'] = '/data/.huggingface'
 
-print("CUDA version:", torch.version.cuda)
-print("loading everything")
-compiled = False
-api = HfApi()
+# ============================================================
+# Model Loading (runs once at startup)
+# ============================================================
 
 class Preprocessor:
     MODEL_ID = "lllyasviel/Annotators"
@@ -51,26 +41,26 @@ class Preprocessor:
             torch.cuda.empty_cache()
             self.name = name
         else:
-            raise ValueError
-        return
+            raise ValueError(f"Unknown preprocessor: {name}")
 
     def __call__(self, image: Image.Image, **kwargs) -> Image.Image:
         return self.model(image, **kwargs)
 
+
+# Load models at startup
 if gr.NO_RELOAD:
-    # Controlnet Normal
+    print("CUDA version:", torch.version.cuda)
+    print("Loading models...")
+
+    # ControlNet
     model_id = "lllyasviel/control_v11p_sd15_normalbae"
-    print("initializing controlnet")
     controlnet = ControlNetModel.from_pretrained(
         model_id,
         torch_dtype=torch.float16,
-        attn_implementation="flash_attention_2",
     ).to("cuda")
 
     # Scheduler
     scheduler = DPMSolverMultistepScheduler.from_pretrained(
-        # "runwayml/stable-diffusion-v1-5",
-        # "stable-diffusion-v1-5/stable-diffusion-v1-5",
         "ashllay/stable-diffusion-v1-5-archive",
         solver_order=2,
         subfolder="scheduler",
@@ -80,372 +70,126 @@ if gr.NO_RELOAD:
         prediction_type="epsilon",
         thresholding=False,
         denoise_final=True,
-        device_map="cuda",
         torch_dtype=torch.float16,
     )
 
-    # Stable Diffusion Pipeline URL
-    # base_model_url = "https://huggingface.co/broyang/hentaidigitalart_v20/blob/main/realcartoon3d_v15.safetensors"
+    # Stable Diffusion Pipeline
     base_model_url = "https://huggingface.co/Lykon/AbsoluteReality/blob/main/AbsoluteReality_1.8.1_pruned.safetensors"
-    # vae_url = "https://huggingface.co/stabilityai/sd-vae-ft-mse-original/blob/main/vae-ft-mse-840000-ema-pruned.safetensors"
-
-    # print('loading vae')
-    # vae = AutoencoderKL.from_single_file(vae_url, torch_dtype=torch.float16).to("cuda")
-    # vae.to(memory_format=torch.channels_last) 
-
-    print('loading pipe')
+    
     pipe = StableDiffusionControlNetPipeline.from_single_file(
         base_model_url,
         safety_checker=None,
         controlnet=controlnet,
         scheduler=scheduler,
-        # vae=vae,
         torch_dtype=torch.float16,
     ).to("cuda")
-    
-    # print('loading inpainting pipe')
-    # inpaint_pipe = StableDiffusionInpaintPipeline.from_pretrained(
-    #     "runwayml/stable-diffusion-inpainting",
-    #     torch_dtype=torch.float16,
-    # ).to("cuda")
 
-    print("loading preprocessor")
+    # Preprocessor
     preprocessor = Preprocessor()
     preprocessor.load("NormalBae")
-    pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="EasyNegativeV2.safetensors", token="EasyNegativeV2",)
-    pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="badhandv4.pt", token="badhandv4")
-    pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="fcNeg-neg.pt", token="fcNeg-neg")
-    pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="HDA_Ahegao.pt", token="HDA_Ahegao")
-    pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="HDA_Bondage.pt", token="HDA_Bondage")
-    pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="HDA_pet_play.pt", token="HDA_pet_play")
-    pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="HDA_unconventional maid.pt", token="HDA_unconventional_maid")
-    pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="HDA_NakedHoodie.pt", token="HDA_NakedHoodie")
-    pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="HDA_NunDress.pt", token="HDA_NunDress")
-    pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="HDA_Shibari.pt", token="HDA_Shibari")
-    pipe.to("cuda")
 
-    print("---------------Loaded controlnet pipeline---------------") 
+    # Optional: Load textual inversions for better negative prompts
+    try:
+        pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="EasyNegativeV2.safetensors", token="EasyNegativeV2")
+        pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="badhandv4.pt", token="badhandv4")
+        pipe.load_textual_inversion("broyang/hentaidigitalart_v20", weight_name="fcNeg-neg.pt", token="fcNeg-neg")
+    except Exception as e:
+        print(f"Could not load textual inversions: {e}")
+
+    pipe.to("cuda")
     torch.cuda.empty_cache()
     gc.collect()
-    print(f"CUDA memory allocated: {torch.cuda.max_memory_allocated(device='cuda') / 1e9:.2f} GB")
-    print("Model Compiled!")
-    
-def generate_furniture_mask(image, furniture_type):
-    image_np = np.array(image)
-    height, width = image_np.shape[:2]
-        
-    mask = np.zeros((height, width), dtype=np.uint8)
-        
-    if furniture_type == "sofa":
-        cv2.rectangle(mask, (width//4, int(height*0.6)), (width*3//4, height), 255, -1)
-    elif furniture_type == "table":
-        cv2.rectangle(mask, (width//3, height//3), (width*2//3, height*2//3), 255, -1)
-    elif furniture_type == "chair":
-        cv2.circle(mask, (width*3//5, height*2//3), height//6, 255, -1)
-        
-    return Image.fromarray(mask)
+    print(f"Models loaded! CUDA memory: {torch.cuda.max_memory_allocated(device='cuda') / 1e9:.2f} GB")
 
-def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-    return seed
 
-def get_additional_prompt():
-    prompt = "hyperrealistic photography,extremely detailed,(intricate details),unity 8k wallpaper,ultra detailed"
-    top = ["tank top", "blouse", "button up shirt", "sweater", "corset top"]
-    bottom = ["short skirt", "athletic shorts", "jean shorts", "pleated skirt", "short skirt", "leggings", "high-waisted shorts"]
-    accessory = ["knee-high boots", "gloves", "Thigh-high stockings", "Garter belt", "choker", "necklace", "headband", "headphones"]
-    return f"{prompt}, {random.choice(top)}, {random.choice(bottom)}, {random.choice(accessory)}, score_9"
-    # outfit = ["schoolgirl outfit", "playboy outfit", "red dress", "gala dress", "cheerleader outfit", "nurse outfit", "Kimono"]
+# ============================================================
+# Style Definitions
+# ============================================================
 
-def get_prompt(prompt, additional_prompt):
-    interior = "design-style interior designed (interior space),tungsten white balance,captured with a DSLR camera using f/10 aperture, 1/60 sec shutter speed, ISO 400, 20mm focal length"
-    default = "hyperrealistic photography,extremely detailed,(intricate details),unity 8k wallpaper,ultra detailed"
-    default2 = f"professional 3d model {prompt},octane render,highly detailed,volumetric,dramatic lighting,hyperrealistic photography,extremely detailed,(intricate details),unity 8k wallpaper,ultra detailed"
-    randomize = get_additional_prompt()
-    # nude = "NSFW,((nude)),medium bare breasts,hyperrealistic photography,extremely detailed,(intricate details),unity 8k wallpaper,ultra detailed"
-    # bodypaint = "((fully naked with no clothes)),nude naked seethroughxray,invisiblebodypaint,rating_newd,NSFW"
-    lab_girl = "hyperrealistic photography, extremely detailed, shy assistant wearing minidress boots and gloves, laboratory background, score_9, 1girl"
-    pet_play = "hyperrealistic photography, extremely detailed, playful, blush, glasses, collar, score_9, HDA_pet_play"
-    bondage = "hyperrealistic photography, extremely detailed, submissive, glasses, score_9, HDA_Bondage"
-    # ahegao = "((invisible clothing)), hyperrealistic photography,exposed vagina,sexy,nsfw,HDA_Ahegao"
-    ahegao2 = "(invisiblebodypaint),rating_newd,HDA_Ahegao"
-    athleisure = "hyperrealistic photography, extremely detailed, 1girl athlete, exhausted embarrassed sweaty,outdoors, ((athleisure clothing)), score_9"
-    atompunk = "((atompunk world)), hyperrealistic photography, extremely detailed, short hair, bodysuit, glasses, neon cyberpunk background, score_9"
-    maid = "hyperrealistic photography, extremely detailed, shy, blushing, score_9, pastel background, HDA_unconventional_maid"
-    nundress = "hyperrealistic photography, extremely detailed, shy, blushing, fantasy background, score_9, HDA_NunDress"
-    naked_hoodie = "hyperrealistic photography, extremely detailed, medium hair, cityscape, (neon lights), score_9, HDA_NakedHoodie"
-    abg = "(1girl, asian body covered in words, words on body, tattoos of (words) on body),(masterpiece, best quality),medium breasts,(intricate details),unity 8k wallpaper,ultra detailed,(pastel colors),beautiful and aesthetic,see-through (clothes),detailed,solo"
-    # shibari = "extremely detailed, hyperrealistic photography, earrings, blushing, lace choker, tattoo, medium hair, score_9, HDA_Shibari"
-    shibari2 = "octane render, highly detailed, volumetric, HDA_Shibari"
-    
-    if prompt == "":
-        girls = [randomize, pet_play, bondage, lab_girl, athleisure, atompunk, maid, nundress, naked_hoodie, abg, shibari2, ahegao2]
-        prompts_nsfw = [abg, shibari2, ahegao2]
-        prompt = f"{random.choice(girls)}"
-        prompt = f"boho chic"
-        # print(f"-------------{preset}-------------")
-    else:
-        prompt = f"Photo from Pinterest of {prompt} {interior}"
-        # prompt = default2
-    return f"{prompt} f{additional_prompt}"
+STYLE_LIST = [
+    {"name": "None", "prompt": ""},
+    {"name": "Minimalistic", "prompt": "Minimalist interior design,clean lines,neutral colors,uncluttered space,functional furniture,lots of natural light"},
+    {"name": "Boho", "prompt": "Bohemian chic interior,eclectic mix of patterns and textures,vintage furniture,plants,woven textiles,warm earthy colors"},
+    {"name": "Farmhouse", "prompt": "Modern farmhouse interior,rustic wood elements,shiplap walls,neutral color palette,industrial accents,cozy textiles"},
+    {"name": "Saudi Prince", "prompt": "Opulent gold interior,luxurious ornate furniture,crystal chandeliers,rich fabrics,marble floors,intricate Arabic patterns"},
+    {"name": "Neoclassical", "prompt": "Neoclassical interior design,elegant columns,ornate moldings,symmetrical layout,refined furniture,muted color palette"},
+    {"name": "Eclectic", "prompt": "Eclectic interior design,mix of styles and eras,bold color combinations,diverse furniture pieces,unique art objects"},
+    {"name": "Parisian", "prompt": "Parisian apartment interior,all-white color scheme,ornate moldings,herringbone wood floors,elegant furniture,large windows"},
+    {"name": "Hollywood", "prompt": "Hollywood Regency interior,glamorous and luxurious,bold colors,mirrored surfaces,velvet upholstery,gold accents"},
+    {"name": "Scandinavian", "prompt": "Scandinavian interior design,light wood tones,white walls,minimalist furniture,cozy textiles,hygge atmosphere"},
+    {"name": "Beach", "prompt": "Coastal beach house interior,light blue and white color scheme,weathered wood,nautical accents,sheer curtains,ocean view"},
+    {"name": "Japanese", "prompt": "Traditional Japanese interior,tatami mats,shoji screens,low furniture,zen garden view,minimalist decor,natural materials"},
+    {"name": "Midcentury Modern", "prompt": "Mid-century modern interior,1950s-60s style furniture,organic shapes,warm wood tones,bold accent colors,large windows"},
+    {"name": "Retro Futurism", "prompt": "Neon (atompunk world) retro cyberpunk background"},
+    {"name": "Texan", "prompt": "Western cowboy interior,rustic wood beams,leather furniture,cowhide rugs,antler chandeliers,southwestern patterns"},
+    {"name": "Matrix", "prompt": "Futuristic cyberpunk interior,neon accent lighting,holographic plants,sleek black surfaces,advanced gaming setup,transparent screens,Blade Runner inspired decor,high-tech minimalist furniture"},
+]
 
-style_list = [
-    {
-        "name": "None",
-        "prompt": ""
-    },
-    {
-        "name": "Minimalistic",
-        "prompt": "Minimalist interior design,clean lines,neutral colors,uncluttered space,functional furniture,lots of natural light"
-    },
-    {
-        "name": "Boho",
-        "prompt": "Bohemian chic interior,eclectic mix of patterns and textures,vintage furniture,plants,woven textiles,warm earthy colors"
-    },
-    {
-        "name": "Farmhouse",
-        "prompt": "Modern farmhouse interior,rustic wood elements,shiplap walls,neutral color palette,industrial accents,cozy textiles"
-    },
-    {
-        "name": "Saudi Prince",
-        "prompt": "Opulent gold interior,luxurious ornate furniture,crystal chandeliers,rich fabrics,marble floors,intricate Arabic patterns"
-    },
-    {
-        "name": "Neoclassical",
-        "prompt": "Neoclassical interior design,elegant columns,ornate moldings,symmetrical layout,refined furniture,muted color palette"
-    },
-    {
-        "name": "Eclectic",
-        "prompt": "Eclectic interior design,mix of styles and eras,bold color combinations,diverse furniture pieces,unique art objects"
-    },
-    {
-        "name": "Parisian",
-        "prompt": "Parisian apartment interior,all-white color scheme,ornate moldings,herringbone wood floors,elegant furniture,large windows"
-    },
-    {
-        "name": "Hollywood",
-        "prompt": "Hollywood Regency interior,glamorous and luxurious,bold colors,mirrored surfaces,velvet upholstery,gold accents"
-    },
-    {
-        "name": "Scandinavian",
-        "prompt": "Scandinavian interior design,light wood tones,white walls,minimalist furniture,cozy textiles,hygge atmosphere"
-    },
-    {
-        "name": "Beach",
-        "prompt": "Coastal beach house interior,light blue and white color scheme,weathered wood,nautical accents,sheer curtains,ocean view"
-    },
-    {
-        "name": "Japanese",
-        "prompt": "Traditional Japanese interior,tatami mats,shoji screens,low furniture,zen garden view,minimalist decor,natural materials"
-    },
-    { 
-        "name": "Midcentury Modern",
-        "prompt": "Mid-century modern interior,1950s-60s style furniture,organic shapes,warm wood tones,bold accent colors,large windows"
-    },
-    {
-        "name": "Retro Futurism",
-        "prompt": "Neon (atompunk world) retro cyberpunk background",
-    },
-    {
-        "name": "Texan",
-        "prompt": "Western cowboy interior,rustic wood beams,leather furniture,cowhide rugs,antler chandeliers,southwestern patterns"
-    },
-    {
-        "name": "Matrix",
-        "prompt": "Futuristic cyberpunk interior,neon accent lighting,holographic plants,sleek black surfaces,advanced gaming setup,transparent screens,Blade Runner inspired decor,high-tech minimalist furniture"
-    }
-] 
+STYLES = {s["name"]: s["prompt"] for s in STYLE_LIST}
+STYLE_NAMES = list(STYLES.keys())
 
-styles = {k["name"]: (k["prompt"]) for k in style_list}
-STYLE_NAMES = list(styles.keys())
 
-def apply_style(style_name):
-    if style_name in styles:
-        p = styles.get(style_name, "none")
-    return p
+# ============================================================
+# Core Processing Function (API Endpoint)
+# ============================================================
 
+@spaces.GPU(duration=20)
+@torch.inference_mode()
+def redesign_interior(
+    image: Image.Image,
+    style: str = "Minimalistic",
+    custom_prompt: str = "",
+    num_steps: int = 15,
+    guidance_scale: float = 5.5,
+    seed: int = -1,
+    image_resolution: int = 768,
+) -> Image.Image:
+    """
+    Redesign an interior image with the specified style.
     
-css = """
-h1, h2, h3 {
-    text-align: center;
-    display: block;
-}
-footer {
-    visibility: hidden;
-}
-.gradio-container {
-    max-width: 1100px !important;
-}
-.gr-image {
-    display: flex;
-    justify-content: center; 
-    align-items: center;
-    width: 100%;
-    height: 512px;
-    overflow: hidden;
-}
-.gr-image img {
-    width: 100%;
-    height: 100%; 
-    object-fit: cover;
-    object-position: center;
-}
-"""
-with gr.Blocks(theme="bethecloud/storj_theme", css=css) as demo:
-    #############################################################################
-    with gr.Row():
-        with gr.Accordion("Advanced options", open=show_options, visible=show_options):
-            num_images = gr.Slider(
-                label="Images", minimum=1, maximum=4, value=1, step=1
-            )
-            image_resolution = gr.Slider(
-                label="Image resolution",
-                minimum=256,
-                maximum=1024,
-                value=1024,
-                step=256,
-            )
-            preprocess_resolution = gr.Slider(
-                label="Preprocess resolution",
-                minimum=128,
-                maximum=1024,
-                value=1024,
-                step=1,
-            )
-            num_steps = gr.Slider(
-                label="Number of steps", minimum=1, maximum=100, value=15, step=1
-            )  # 20/4.5 or 12 without lora, 4 with lora
-            guidance_scale = gr.Slider(
-                label="Guidance scale", minimum=0.1, maximum=30.0, value=5.5, step=0.1
-            )  # 5 without lora, 2 with lora
-            seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-            a_prompt = gr.Textbox(
-                label="Additional prompt",
-                value = "design-style interior designed (interior space), tungsten white balance, captured with a DSLR camera using f/10 aperture, 1/60 sec shutter speed, ISO 400, 20mm focal length"
-            )
-            n_prompt = gr.Textbox(
-                label="Negative prompt",
-                value="EasyNegativeV2, fcNeg, (badhandv4:1.4), (worst quality, low quality, bad quality, normal quality:2.0), (bad hands, missing fingers, extra fingers:2.0)",
-            )
-    #############################################################################
-    # input text
-    with gr.Column():
-        prompt = gr.Textbox(
-            label="Custom Design",
-            placeholder="Enter a description (optional)",
-        )
-    # design options
-    with gr.Row(visible=True):
-        style_selection = gr.Radio(
-            show_label=True,
-            container=True,
-            interactive=True,
-            choices=STYLE_NAMES,
-            value="None",
-            label="Design Styles",
-        )
-    # input image
-    with gr.Row(equal_height=True):
-        with gr.Column(scale=1, min_width=300):
-            image = gr.Image(
-                label="Input",
-                sources=["upload"],
-                show_label=True,
-                mirror_webcam=True,
-                type="pil",
-            )
-            # run button
-            with gr.Column():
-                run_button = gr.Button(value="Use this one", size="lg", visible=False)
-        # output image
-        with gr.Column(scale=1, min_width=300):
-            result = gr.Image(  
-                label="Output",
-                interactive=False,
-                type="pil",
-                show_share_button= False,
-            )
-            # Use this image button
-            with gr.Column():
-                use_ai_button = gr.Button(value="Use this one", size="lg", visible=False)
-    config = [
-        image,
-        style_selection,
-        prompt,
-        a_prompt,
-        n_prompt,
-        num_images,
-        image_resolution,
-        preprocess_resolution,
-        num_steps,
-        guidance_scale,
-        seed,
-    ]
-    
-    with gr.Row():
-        helper_text = gr.Markdown("## Tap and hold (on mobile) to save the image.", visible=True)
-    
-    # image processing
-    @gr.on(triggers=[image.upload, prompt.submit, run_button.click], inputs=config, outputs=result, show_progress="minimal")
-    def auto_process_image(image, style_selection, prompt, a_prompt, n_prompt, num_images, image_resolution, preprocess_resolution, num_steps, guidance_scale, seed, progress=gr.Progress(track_tqdm=True)):
-        return process_image(image, style_selection, prompt, a_prompt, n_prompt, num_images, image_resolution, preprocess_resolution, num_steps, guidance_scale, seed)
-    
-    # AI image processing
-    @gr.on(triggers=[use_ai_button.click], inputs=[result] + config, outputs=[image, result], show_progress="minimal")
-    def submit(previous_result, image, style_selection, prompt, a_prompt, n_prompt, num_images, image_resolution, preprocess_resolution, num_steps, guidance_scale, seed, progress=gr.Progress(track_tqdm=True)):
-        # First, yield the previous result to update the input image immediately
-        yield previous_result, gr.update()
-        # Then, process the new input image
-        new_result = process_image(previous_result, style_selection, prompt, a_prompt, n_prompt, num_images, image_resolution, preprocess_resolution, num_steps, guidance_scale, seed)
-        # Finally, yield the new result
-        yield previous_result, new_result
-
-    # Turn off buttons when processing
-    @gr.on(triggers=[image.upload, use_ai_button.click, run_button.click], inputs=None, outputs=[run_button, use_ai_button], show_progress="hidden")
-    def turn_buttons_off():
-        return gr.update(visible=False), gr.update(visible=False)
+    Args:
+        image: Input room/interior image (PIL Image)
+        style: Design style name (e.g., "Minimalistic", "Boho", "Japanese")
+        custom_prompt: Additional custom prompt to append
+        num_steps: Number of inference steps (default: 15)
+        guidance_scale: Guidance scale for generation (default: 5.5)
+        seed: Random seed (-1 for random)
+        image_resolution: Output image resolution (default: 768)
     
-    # Turn on buttons when processing is complete
-    @gr.on(triggers=[result.change], inputs=None, outputs=[use_ai_button, run_button], show_progress="hidden")
-    def turn_buttons_on():
-        return gr.update(visible=True), gr.update(visible=True)
-
-@spaces.GPU(duration=12)
-@torch.inference_mode()
-def process_image(
-    image,
-    style_selection,
-    prompt,
-    a_prompt,
-    n_prompt,
-    num_images,
-    image_resolution,
-    preprocess_resolution,
-    num_steps,
-    guidance_scale,
-    seed,
-):
-    seed = random.randint(0, MAX_SEED)
+    Returns:
+        Redesigned interior image (PIL Image)
+    """
+    # Set seed
+    if seed == -1:
+        seed = random.randint(0, MAX_SEED)
     generator = torch.cuda.manual_seed(seed)
     
+    # Preprocess image with NormalBae
     preprocessor.load("NormalBae")
     control_image = preprocessor(
         image=image,
         image_resolution=image_resolution,
-        detect_resolution=preprocess_resolution,
+        detect_resolution=image_resolution,
     )
     
-    if style_selection is not None and style_selection != "None":
-        prompt = f"Photo from Pinterest of {apply_style(style_selection)} {prompt},{a_prompt}"
+    # Build prompt
+    base_prompt = "Photo from Pinterest of"
+    style_prompt = STYLES.get(style, "")
+    additional_prompt = "design-style interior designed (interior space), tungsten white balance, captured with a DSLR camera using f/10 aperture, 1/60 sec shutter speed, ISO 400, 20mm focal length"
+    
+    if style_prompt:
+        prompt = f"{base_prompt} {style_prompt} {custom_prompt}, {additional_prompt}"
     else:
-        prompt = str(get_prompt(prompt, a_prompt))
-    negative_prompt = str(n_prompt)
-    print(prompt)
+        prompt = f"{base_prompt} {custom_prompt}, {additional_prompt}" if custom_prompt else f"boho chic interior, {additional_prompt}"
+    
+    negative_prompt = "EasyNegativeV2, fcNeg, (badhandv4:1.4), (worst quality, low quality, bad quality, normal quality:2.0), (bad hands, missing fingers, extra fingers:2.0)"
     
-    # Generate the initial room image
-    initial_result = pipe(
+    print(f"Prompt: {prompt}")
+    print(f"Style: {style}, Seed: {seed}")
+    
+    # Generate
+    start = time.time()
+    result = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
         guidance_scale=guidance_scale,
@@ -455,51 +199,109 @@ def process_image(
         image=control_image,
     ).images[0]
     
-    # # Randomly choose whether to add furniture and which type
-    # furniture_types = ["sofa", "table", "chair", "dresser", "bookshelf", "desk", "coffee table"]
-    # furniture_type = random.choice(furniture_types)
+    print(f"Generation completed in {time.time() - start:.2f}s")
+    torch.cuda.empty_cache()
     
+    return result
+
+
+# ============================================================
+# Gradio Interface
+# ============================================================
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 🏠 Interior AI Designer")
+    gr.Markdown("Upload a room photo and select a design style to reimagine your space!")
     
-    # furniture_mask = generate_furniture_mask(initial_result, furniture_type)
-    # furniture_prompt = f"{prompt}, with a {furniture_type} in the style of {style_selection}"
-    # print(furniture_prompt)
+    with gr.Row():
+        with gr.Column():
+            input_image = gr.Image(
+                label="Upload Room Image",
+                type="pil",
+                sources=["upload", "clipboard"],
+            )
+            style_dropdown = gr.Dropdown(
+                label="Design Style",
+                choices=STYLE_NAMES,
+                value="Minimalistic",
+            )
+            custom_prompt = gr.Textbox(
+                label="Custom Prompt (optional)",
+                placeholder="Add specific details like 'with plants' or 'blue accents'",
+            )
+            
+            with gr.Accordion("Advanced Options", open=False):
+                num_steps = gr.Slider(
+                    label="Inference Steps",
+                    minimum=10, maximum=50, value=15, step=1,
+                )
+                guidance_scale = gr.Slider(
+                    label="Guidance Scale",
+                    minimum=1.0, maximum=20.0, value=5.5, step=0.5,
+                )
+                seed = gr.Slider(
+                    label="Seed (-1 for random)",
+                    minimum=-1, maximum=MAX_SEED, value=-1, step=1,
+                )
+                image_resolution = gr.Slider(
+                    label="Resolution",
+                    minimum=512, maximum=1024, value=768, step=128,
+                )
+            
+            generate_btn = gr.Button("🎨 Redesign Interior", variant="primary", size="lg")
+        
+        with gr.Column():
+            output_image = gr.Image(label="Redesigned Interior", type="pil")
     
-    # # Use the inpainting pipeline to add furniture
-    # final_result = inpaint_pipe(
-    #     prompt=furniture_prompt,
-    #     image=initial_result,
-    #     mask_image=furniture_mask,
-    #     negative_prompt=negative_prompt,
-    #     num_inference_steps=num_steps,
-    #     guidance_scale=guidance_scale,
-    #     generator=generator,
-    # ).images[0]
+    # Examples
+    gr.Examples(
+        examples=[
+            ["Minimalistic"],
+            ["Boho"],
+            ["Japanese"],
+            ["Scandinavian"],
+            ["Matrix"],
+        ],
+        inputs=[style_dropdown],
+        label="Try these styles",
+    )
     
-    # Save and upload results
-    timestamp = int(time.time())
-    img_path = f"{timestamp}.jpg"
-    results_path = f"{timestamp}_out.jpg"
-    imageio.imsave(img_path, image)
-    imageio.imsave(results_path, initial_result)
-    api.upload_file(
-        path_or_fileobj=img_path,
-        path_in_repo=img_path,
-        repo_id="broyang/interior-ai-outputs",
-        repo_type="dataset",
-        token=API_KEY,
-        run_as_future=True,
+    # Connect the button to the function
+    generate_btn.click(
+        fn=redesign_interior,
+        inputs=[input_image, style_dropdown, custom_prompt, num_steps, guidance_scale, seed, image_resolution],
+        outputs=output_image,
+        api_name="redesign",  # This enables the API endpoint
     )
-    api.upload_file(
-        path_or_fileobj=results_path,
-        path_in_repo=results_path,
-        repo_id="broyang/interior-ai-outputs",
-        repo_type="dataset",
-        token=API_KEY,
-        run_as_future=True,
+    
+    gr.Markdown("""
+    ---
+    ### 📡 API Usage
+    
+    This app exposes a public API! You can call it programmatically:
+    
+    ```python
+    from gradio_client import Client
+    
+    client = Client("YOUR_USERNAME/interior-ai-designer")
+    result = client.predict(
+        image="path/to/room.jpg",
+        style="Minimalistic",
+        custom_prompt="",
+        num_steps=15,
+        guidance_scale=5.5,
+        seed=-1,
+        image_resolution=768,
+        api_name="/redesign"
     )
-    return initial_result
+    print(result)  # Path to output image
+    ```
+    """)
+
 
-if prod:
-    demo.queue(max_size=20).launch(server_name="localhost", server_port=port)
-else:
-    demo.queue(api_open=False).launch(show_api=False)
+# Launch
+if __name__ == "__main__":
+    demo.queue(max_size=10).launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+    )

requirements.txt

@@ -1,13 +1,12 @@
-torch
-torchvision
-diffusers
-einops
-huggingface-hub
-mediapipe
-opencv-python-headless
-safetensors
-transformers
-xformers
-accelerate
-imageio
-# controlnet-aux
+torch
+torchvision
+diffusers>=0.25.0
+einops
+huggingface-hub
+opencv-python-headless
+safetensors
+transformers>=4.36.0
+accelerate
+timm
+spaces
+