app.py

import gradio as gr
from PIL import Image
import qrcode
from pathlib import Path
import requests
import io
import os
from PIL import Image
import numpy as np
import cv2
from pyzxing import BarCodeReader
from PIL import ImageOps, ImageEnhance, ImageFilter
from huggingface_hub import hf_hub_download, snapshot_download
from PIL import ImageEnhance
import replicate
from dotenv import load_dotenv

# Load environment variables from .env file
load_dotenv()

USERNAME = os.getenv("USERNAME")
PASSWORD = os.getenv("PASSWORD")
REPLICATE_API_TOKEN = os.getenv("REPLICATE_API_TOKEN")

# Set the Replicate API token
os.environ["REPLICATE_API_TOKEN"] = REPLICATE_API_TOKEN

qrcode_generator = qrcode.QRCode(
    version=1,
    error_correction=qrcode.ERROR_CORRECT_H,
    box_size=10,
    border=4,
)


# Define available models
CONTROLNET_MODELS = {
    "QR Code Monster": "monster-labs/control_v1p_sd15_qrcode_monster/v2/",
    "QR Code": "DionTimmer/controlnet_qrcode-control_v1p_sd15",
    # Add more ControlNet models here
}

DIFFUSION_MODELS = {
    "GhostMix": "digiplay/GhostMixV1.2VAE",
    "Stable v1.5": "Jiali/stable-diffusion-1.5",
    # Add more diffusion models here
}

# Global variables to store loaded models
loaded_controlnet = None
loaded_pipe = None

#   def load_models_on_launch():
#    global loaded_controlnet, loaded_pipe
#    print("Loading models on launch...")
    
# Download the main repository
#    main_repo_path = snapshot_download("monster-labs/control_v1p_sd15_qrcode_monster")
    
# Construct the path to the subfolder
#    controlnet_path = os.path.join(main_repo_path, "v2")

#    loaded_controlnet = ControlNetModel.from_pretrained(
#        controlnet_path,
#        torch_dtype=torch.float16
#    ).to("mps")

#    diffusion_path = snapshot_download(DIFFUSION_MODELS["GhostMix"])
#    loaded_pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
#        diffusion_path,
#        controlnet=loaded_controlnet,
#        torch_dtype=torch.float16,
#        safety_checker=None,
#    ).to("mps")
#    print("Models loaded successfully!")

# Modify the load_models function to use global variables
#def load_models(controlnet_model, diffusion_model):
#    global loaded_controlnet, loaded_pipe
#    if loaded_controlnet is None or loaded_pipe is None:
#        load_models_on_launch()
#    return loaded_pipe

# Add new functions for image adjustments
def adjust_image(image, brightness, contrast, saturation):
    if image is None:
        return None
    
    img = Image.fromarray(image) if isinstance(image, np.ndarray) else image
    
    if brightness != 1:
        img = ImageEnhance.Brightness(img).enhance(brightness)
    if contrast != 1:
        img = ImageEnhance.Contrast(img).enhance(contrast)
    if saturation != 1:
        img = ImageEnhance.Color(img).enhance(saturation)
    
    return np.array(img)

def resize_for_condition_image(input_image: Image.Image, resolution: int):
    input_image = input_image.convert("RGB")
    W, H = input_image.size
    k = float(resolution) / min(H, W)
    H *= k
    W *= k
    H = int(round(H / 64.0)) * 64
    W = int(round(W / 64.0)) * 64
    img = input_image.resize((W, H), resample=Image.LANCZOS)
    return img


#   SAMPLER_MAP = {
#    "DPM++ Karras SDE": lambda config: DPMSolverMultistepScheduler.from_config(config, use_karras=True, algorithm_type="sde-dpmsolver++"),
#    "DPM++ Karras": lambda config: DPMSolverMultistepScheduler.from_config(config, use_karras=True),
#    "Heun": lambda config: HeunDiscreteScheduler.from_config(config),
#    "Euler": lambda config: EulerDiscreteScheduler.from_config(config),
#    "DDIM": lambda config: DDIMScheduler.from_config(config),
#    "DEIS": lambda config: DEISMultistepScheduler.from_config(config),
#}

def scan_qr_code(image):
    # Convert gradio image to PIL Image if necessary
    if isinstance(image, np.ndarray):
        image = Image.fromarray(image)
    
    # Convert to grayscale
    gray_image = image.convert('L')
    
    # Convert to numpy array
    np_image = np.array(gray_image)
    
    # Method 1: Using qrcode library
    try:
        qr = qrcode.QRCode()
        qr.add_data('')
        qr.decode(gray_image)
        return qr.data.decode('utf-8')
    except Exception:
        pass
    
    # Method 2: Using OpenCV
    try:
        qr_detector = cv2.QRCodeDetector()
        retval, decoded_info, points, straight_qrcode = qr_detector.detectAndDecodeMulti(np_image)
        if retval:
            return decoded_info[0]
    except Exception:
        pass
    
    # Method 3: Fallback to zxing-cpp
    try:
        reader = BarCodeReader()
        results = reader.decode(np_image)
        if results:
            return results[0].parsed
    except Exception:
        pass
    
    return None

def invert_image(image):
    if image is None:
        return None
    if isinstance(image, np.ndarray):
        return 255 - image
    elif isinstance(image, Image.Image):
        return ImageOps.invert(image.convert('RGB'))
    else:
        raise ValueError("Unsupported image type")

def invert_displayed_image(image):
    if image is None:
        return None
    inverted = invert_image(image)
    if isinstance(inverted, np.ndarray):
        return Image.fromarray(inverted)
    return inverted


#@spaces.GPU()
def inference(
    qr_code_content: str,
    prompt: str,
    negative_prompt: str,
    guidance_scale: float = 9.0,
    qr_conditioning_scale: float = 1.47,
    num_inference_steps: int = 20,
    seed: int = -1,
    image_resolution: int = 512,
    scheduler: str = "K_EULER",
    eta: float = 0.0,
    num_outputs: int = 1,
    low_threshold: int = 100,
    high_threshold: int = 200,
    guess_mode: bool = False,
    disable_safety_check: bool = False,
):
    try:
        progress = gr.Progress()
        progress(0, desc="Generating QR code...")

        # Generate QR code image
        qr = qrcode.QRCode(
            version=1,
            error_correction=qrcode.constants.ERROR_CORRECT_H,
            box_size=10,
            border=4,
        )
        qr.add_data(qr_code_content)
        qr.make(fit=True)
        qr_image = qr.make_image(fill_color="black", back_color="white")

        # Save QR code image to a temporary file
        temp_qr_path = "temp_qr.png"
        qr_image.save(temp_qr_path)

        progress(0.3, desc="Running inference...")

        # Ensure num_outputs is within the allowed range
        num_outputs = max(1, min(num_outputs, 10))

        # Ensure seed is an integer and not null
        seed = int(seed) if seed != -1 else None

        # Ensure high_threshold is at least 1
        high_threshold = max(1, int(high_threshold))

        # Prepare the input dictionary
        input_dict = {
            "prompt": prompt,
            "qr_image": open(temp_qr_path, "rb"),
            "negative_prompt": negative_prompt,
            "guidance_scale": float(guidance_scale),
            "qr_conditioning_scale": float(qr_conditioning_scale),
            "num_inference_steps": int(num_inference_steps),
            "image_resolution": int(image_resolution),
            "scheduler": scheduler,
            "eta": float(eta),
            "num_outputs": num_outputs,
            "low_threshold": int(low_threshold),
            "high_threshold": high_threshold,
            "guess_mode": guess_mode,
            "disable_safety_check": disable_safety_check,
        }

        # Only add seed to input_dict if it's not None
        if seed is not None:
            input_dict["seed"] = seed

        # Run inference using Replicate API
        output = replicate.run(
            "anotherjesse/multi-control:76d8414a702e66c84fe2e6e9c8cbdc12e53f950f255aae9ffa5caa7873b12de0",
            input=input_dict
        )

        progress(0.9, desc="Processing results...")

        # Download the generated image
        response = requests.get(output[0])
        img = Image.open(io.BytesIO(response.content))

        # Clean up temporary file
        os.remove(temp_qr_path)

        progress(1.0, desc="Done!")
        return img, seed if seed is not None else -1
    except Exception as e:
        print(f"Error in inference: {str(e)}")
        return Image.new('RGB', (512, 512), color='white'), -1



def invert_init_image_display(image):
    if image is None:
        return None
    inverted = invert_image(image)
    if isinstance(inverted, np.ndarray):
        return Image.fromarray(inverted)
    return inverted

def adjust_color_balance(image, r, g, b):
    # Convert image to RGB if it's not already
    image = image.convert('RGB')
    
    # Split the image into its RGB channels
    r_channel, g_channel, b_channel = image.split()
    
    # Adjust each channel
    r_channel = r_channel.point(lambda i: i + (i * r))
    g_channel = g_channel.point(lambda i: i + (i * g))
    b_channel = b_channel.point(lambda i: i + (i * b))
    
    # Merge the channels back
    return Image.merge('RGB', (r_channel, g_channel, b_channel))

def apply_qr_overlay(image, original_qr, overlay, opacity):
    if not overlay or original_qr is None:
        return image
    
    # Resize original QR to match the generated image
    original_qr = original_qr.resize(image.size)
    
    # Create a new image blending the generated image and the QR code
    return Image.blend(image, original_qr, opacity)

def apply_edge_enhancement(image, strength):
    if strength == 0:
        return image
    
    # Apply edge enhancement
    enhanced = image.filter(ImageFilter.EDGE_ENHANCE)
    
    # Blend the original and enhanced images based on strength
    return Image.blend(image, enhanced, strength / 5.0)


css = """
h1, h2, h3, h4, h5, h6, p, li, ul, ol, a {
    text-align: left;
}
.centered-image {
    display: block;
    margin-left: auto;
    margin-right: auto;
    max-width: 100%;
    height: auto;
}
"""

def login(username, password):
    if username == USERNAME and password == PASSWORD:
        return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(value="Login successful! You can now access the QR Code Art Generator tab.", visible=True)
    else:
        return gr.update(visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(value="Invalid username or password. Please try again.", visible=True)
    
# Add login elements to the Gradio interface
with gr.Blocks(theme='Hev832/Applio', css=css, fill_width=True, fill_height=True) as blocks:
    generated_images = gr.State([])

    with gr.Tab("Welcome"):
        with gr.Row():
            with gr.Column(scale=2):  
                gr.Markdown(
                    """
                    <img src="https://cdn-uploads.huggingface.co/production/uploads/64740cf7485a7c8e1bd51ac9/29sj9LyPQItG5uBOO2x3r.webp" alt="UGD Logo" width="250" class="centered-image">

                    # Underground Digital's QR Code Art Generator
                
                    ## Transform Your QR Codes into Brand Masterpieces
                    
                    This cutting-edge tool empowers our creative team to craft visually stunning,
                    on-brand QR codes that perfectly blend functionality with artistic expression.
                    ## How It Works:
                    
                    1. **Enter Your QR Code Content**: Start by inputting the URL or text for your QR code.
                    2. **Craft Your Prompt**: Describe the artistic style or theme you envision for your QR code.
                    3. **Fine-tune with Advanced Settings**: Adjust parameters to perfect your creation (see tips below).
                    4. **Generate and Iterate**: Click 'Run' to create your art, then refine as needed.
                    """
                )
                
            with gr.Column(scale=1):

                    with gr.Row():
                        gr.Markdown(
                            """
                            Login below using the internal<br>
                            username and password to access the full app.<br>
                            
                            Once logged in, a new tab will appear named<br>
                            "QR Code Art Generator" allowing you to access.
                            """
                        )
    
                    with gr.Row():
                        username = gr.Textbox(label="Username", placeholder="Enter your username", value="ugd")
                    with gr.Row():
                        password = gr.Textbox(label="Password", type="password", placeholder="Enter your password", value="ugd!")
                    with gr.Row():
                        login_button = gr.Button("Login", size="sm")
                    login_message = gr.Markdown(visible=False)


    with gr.Tab("QR Code Art Generator", visible=False) as app_container:
        with gr.Row():
            with gr.Column():
                qr_code_content = gr.Textbox(
                    label="QR Code Content",
                    placeholder="Enter URL or text for your QR code",
                    info="This is what your QR code will link to or display when scanned.",
                    value="https://www.go-yamamoto.com/",
                    lines=1,
                )

                prompt = gr.Textbox(
                    label="Artistic Prompt",
                    placeholder="Describe the style or theme for your QR code art (For best results, keep the prompt to 75 characters or less as seen below)",
                    value="A high-res, photo-realistic minimalist rendering of Mount Fuji as a sharp, semi-realistic silhouette on the horizon. The mountain conveys strength and motion with clean, crisp lines and natural flow. Features detailed snow textures, subtle ridge highlights, and a powerful yet serene atmosphere. Emphasizes strength with clarity and precision in texture and light.",
                    info="Describe the style or theme for your QR code art (For best results, keep the prompt to 75 characters or less as seen in the example)",
                    lines=8,
                )
                negative_prompt = gr.Textbox(
                    label="Elements to Avoid",
                    placeholder="Describe what you don't want in the image",
                    value="ugly, disfigured, low quality, blurry, nsfw, bad_pictures, poorly drawn, distorted, overexposed, flat shading, bad proportions, deformed, pixelated, messy details, lack of contrast, unrealistic textures, bad anatomy, rough edges, low resolution",
                    info="List elements or styles you want to avoid in your QR code art.",
                    lines=4,
                )

                run_btn = gr.Button("🎨 Create Your QR Art", variant="primary")  

                with gr.Accordion(label="Needs Some Prompting Help?", open=False, visible=True):
                    gr.Markdown(
                        """
                        ## 🌟 Tips for Spectacular Results:
                        - Use concise details in your prompt to help the AI understand your vision.
                        - Use negative prompts to avoid unwanted elements in your image.
                        - Experiment with different ControlNet models and diffusion models to find the best combination for your prompt.
                        ## 🎭 Prompt Ideas to Spark Your Creativity:
                        - "A serene Japanese garden with cherry blossoms and a koi pond"
                        - "A futuristic cityscape with neon lights and flying cars"
                        - "An abstract painting with swirling colors and geometric shapes"
                        - "A vintage-style travel poster featuring iconic landmarks"
                        Remember, the magic lies in the details of your prompt and the fine-tuning of your settings. 
                        Happy creating!
                        """
                    )

                with gr.Accordion("Set Custom QR Code Colors", open=False, visible=False):
                    bg_color = gr.ColorPicker(
                        label="Background Color", 
                        value="#FFFFFF",
                        info="Choose the background color for the QR code"
                    )
                    qr_color = gr.ColorPicker(
                        label="QR Code Color", 
                        value="#000000",
                        info="Choose the color for the QR code pattern"
                    )
                    invert_final_image = gr.Checkbox(
                        label="Invert Final Image", 
                        value=False,
                        info="Check this to invert the colors of the final image",
                        visible=False,
                    )
                with gr.Accordion("AI Model Selection", open=False, visible=False):
                    controlnet_model_dropdown = gr.Dropdown(
                        choices=list(CONTROLNET_MODELS.keys()),
                        value="QR Code Monster",
                        label="ControlNet Model",
                        info="Select the ControlNet model for QR code generation"
                    )
                    diffusion_model_dropdown = gr.Dropdown(
                        choices=list(DIFFUSION_MODELS.keys()),
                        value="GhostMix",
                        label="Diffusion Model",
                        info="Select the main diffusion model for image generation"
                    )
                
            
                with gr.Accordion(label="QR Code Image (Optional)", open=False, visible=False):
                    qr_code_image = gr.Image(
                        label="QR Code Image (Optional). Leave blank to automatically generate QR code",
                        type="pil",
                    )
            
            with gr.Column():
                gr.Markdown("### Your Generated QR Code Art")
                result_image = gr.Image(
                    label="Your Artistic QR Code", 
                    show_download_button=True, 
                    show_fullscreen_button=True, 
                    container=False
                )
                gr.Markdown("💾 Right-click and save the image to download your QR code art. **Note:** Images are currently not stored when generated, meaning each new generation deletes the previous one. Make sure to save your images as you go.")

                scan_button = gr.Button("Verify QR Code Works", visible=False)
                scan_result = gr.Textbox(label="Validation Result of QR Code", interactive=False, visible=False)
                used_seed = gr.Number(label="Seed Used", interactive=False)

                with gr.Accordion(label="Use Your Own Image as a Reference", open=True, visible=True) as init_image_acc:
                    init_image = gr.Image(label="Reference Image", type="pil")
                    with gr.Row():
                        use_qr_code_as_init_image = gr.Checkbox(
                            label="Uncheck to use your own image for generation", 
                            value=True, 
                            interactive=True,
                            info="Allows you to use your own image for generation, otherwise a generic QR Code is created automatically as the base image"
                        )
                        reference_image_strength = gr.Slider(
                            minimum=0.0,
                            maximum=5.0,
                            step=0.05,
                            value=0.6,
                            label="Reference Image Influence",
                            info="Controls how much the reference image influences the final result (0 = ignore, 5 = copy exactly)",
                            visible=False
                        )
                        invert_init_image_button = gr.Button("Invert Init Image", size="sm", visible=False)

    with gr.Tab("Advanced Settings"):
        with gr.Accordion("Advanced Art Controls", open=True):
            with gr.Row():
                qr_conditioning_scale = gr.Slider(
                    minimum=0.0,
                    maximum=5.0,
                    step=0.01,
                    value=1.47,
                    label="QR Code Visibility",
                )
                with gr.Accordion("QR Code Visibility Explanation", open=False):
                    gr.Markdown(
                        """
                        **QR Code Visibility** controls how prominent the QR code is in the final image:
                        
                        - **Low (0.0-1.0)**: QR code blends more with the art, potentially harder to scan.
                        - **Medium (1.0-3.0)**: Balanced visibility, usually scannable while maintaining artistic quality.
                        - **High (3.0-5.0)**: QR code stands out more, easier to scan but less artistic.
                        
                        Start with 1.47 for a good balance between art and functionality.
                        """
                    )
            
            with gr.Row():
                guidance_scale = gr.Slider(
                    minimum=0.1,
                    maximum=30.0,
                    step=0.1,
                    value=9.0,
                    label="Prompt Adherence",
                )
                with gr.Accordion("Prompt Adherence Explanation", open=False):
                    gr.Markdown(
                        """
                        **Prompt Adherence** determines how closely the AI follows your prompt:
                        
                        - **Low (0.1-5.0)**: More creative freedom, may deviate from prompt.
                        - **Medium (5.0-15.0)**: Balanced between prompt and AI creativity.
                        - **High (15.0-30.0)**: Strictly follows the prompt, less creative freedom.
                        
                        A value of 9.0 provides a good balance between creativity and prompt adherence.
                        """
                    )
            
            with gr.Row():
                num_inference_steps = gr.Slider(
                    minimum=1,
                    maximum=100,
                    step=1,
                    value=20,
                    label="Generation Steps",
                )
                with gr.Accordion("Generation Steps Explanation", open=False):
                    gr.Markdown(
                        """
                        **Generation Steps** affects the detail and quality of the generated image:
                        
                        - **Low (1-10)**: Faster generation, less detailed results.
                        - **Medium (11-30)**: Good balance between speed and quality.
                        - **High (31-100)**: More detailed results, slower generation.
                        
                        20 steps is a good starting point for most generations.
                        """
                    )
            
            with gr.Row():
                image_resolution = gr.Slider(
                    minimum=256,
                    maximum=1024,
                    step=64,
                    value=512,
                    label="Image Resolution",
                )
                with gr.Accordion("Image Resolution Explanation", open=False):
                    gr.Markdown(
                        """
                        **Image Resolution** determines the size and detail of the generated image:
                        
                        - **Low (256-384)**: Faster generation, less detailed.
                        - **Medium (512-768)**: Good balance of detail and generation time.
                        - **High (832-1024)**: More detailed, slower generation.
                        
                        512x512 is a good default for most use cases.
                        """
                    )
            
            with gr.Row():
                seed = gr.Slider(
                    minimum=-1,
                    maximum=9999999999,
                    step=1,
                    value=-1,
                    label="Generation Seed",
                )
                with gr.Accordion("Generation Seed Explanation", open=False):
                    gr.Markdown(
                        """
                        **Generation Seed** controls the randomness of the generation:
                        
                        - **-1**: Random seed each time, producing different results.
                        - **Any positive number**: Consistent results for the same inputs.
                        
                        Use -1 to explore various designs, or set a specific seed to recreate a particular result.
                        """
                    )
            
            with gr.Row():
                scheduler = gr.Dropdown(
                    choices=["DDIM", "K_EULER", "DPMSolverMultistep", "K_EULER_ANCESTRAL", "PNDM", "KLMS"],
                    value="K_EULER",
                    label="Sampling Method",
                )
                with gr.Accordion("Sampling Method Explanation", open=False):
                    gr.Markdown(
                        """
                        **Sampling Method** affects the image generation process:
                        
                        - **K_EULER**: Good balance of speed and quality.
                        - **DDIM**: Can produce sharper results but may be slower.
                        - **DPMSolverMultistep**: Often produces high-quality results.
                        - **K_EULER_ANCESTRAL**: Can introduce more variations.
                        - **PNDM**: Another quality-focused option.
                        - **KLMS**: Can produce smooth results.
                        
                        Experiment with different methods to find what works best for your specific prompts.
                        """
                    )

            with gr.Row():
                eta = gr.Slider(
                    minimum=0.0,
                    maximum=1.0,
                    step=0.01,
                    value=0.0,
                    label="ETA (Noise Level)",
                )
                with gr.Accordion("ETA Explanation", open=False):
                    gr.Markdown(
                        """
                        **ETA (Noise Level)** controls the amount of noise in the generation process:
                        
                        - **0.0**: No added noise, more deterministic results.
                        - **0.1-0.5**: Slight variations in output.
                        - **0.6-1.0**: More variations, potentially more creative results.
                        
                        Start with 0.0 and increase if you want more variation in your outputs.
                        """
                    )

            with gr.Row():
                low_threshold = gr.Slider(
                    minimum=1,
                    maximum=255,
                    step=1,
                    value=100,
                    label="Edge Detection Low Threshold",
                )
                high_threshold = gr.Slider(
                    minimum=1,
                    maximum=255,
                    step=1,
                    value=200,
                    label="Edge Detection High Threshold",
                )
                with gr.Accordion("Edge Detection Thresholds Explanation", open=False):
                    gr.Markdown(
                        """
                        **Edge Detection Thresholds** affect how the QR code edges are processed:
                        
                        - **Low Threshold**: Lower values detect more edges, higher values fewer.
                        - **High Threshold**: Determines which edges are strong. Higher values result in fewer strong edges.
                        
                        Default values (100, 200) work well for most QR codes. Adjust if you need more or less edge definition.
                        """
                    )

            with gr.Row():
                guess_mode = gr.Checkbox(
                    label="Guess Mode",
                    value=False,
                )
                with gr.Accordion("Guess Mode Explanation", open=False):
                    gr.Markdown(
                        """
                        **Guess Mode**, when enabled, allows the AI to interpret the input image more freely:
                        
                        - **Unchecked**: AI follows the QR code structure more strictly.
                        - **Checked**: AI has more freedom to interpret the input, potentially leading to more creative results.
                        
                        Use this if you want more artistic interpretations of your QR code.
                        """
                    )

            with gr.Row():
                disable_safety_check = gr.Checkbox(
                    label="Disable Safety Check",
                    value=False,
                )
                with gr.Accordion("Safety Check Explanation", open=False):
                    gr.Markdown(
                        """
                        **Disable Safety Check** removes content filtering from the generation process:
                        
                        - **Unchecked**: Normal content filtering applied.
                        - **Checked**: No content filtering, may produce unexpected or inappropriate results.
                        
                        Use with caution and only if necessary for your specific use case.
                        """
                    )
    with gr.Tab("Image Editing"):
        with gr.Column():
            image_selector = gr.Dropdown(label="Select Image to Edit", choices=[], interactive=True, visible=False)
            image_to_edit = gr.Image(label="Your Artistic QR Code", show_download_button=True, show_fullscreen_button=True, container=True)

            with gr.Row():
                qr_overlay = gr.Checkbox(label="Overlay Original QR Code", value=False, visible=False)
                qr_opacity = gr.Slider(minimum=0.1, maximum=1.0, step=0.1, value=0.5, label="QR Overlay Opacity", visible=False)
                edge_enhance = gr.Slider(minimum=0.0, maximum=5.0, step=0.1, value=0.0, label="Edge Enhancement", visible=False)

            with gr.Row():
                red_balance = gr.Slider(minimum=-1.0, maximum=1.0, step=0.1, value=0.0, label="Red Balance")
                green_balance = gr.Slider(minimum=-1.0, maximum=1.0, step=0.1, value=0.0, label="Green Balance")
                blue_balance = gr.Slider(minimum=-1.0, maximum=1.0, step=0.1, value=0.0, label="Blue Balance")


            with gr.Row():
                brightness = gr.Slider(minimum=0.1, maximum=2.0, step=0.1, value=1.0, label="Brightness")
                contrast = gr.Slider(minimum=0.1, maximum=2.0, step=0.1, value=1.0, label="Contrast")
                saturation = gr.Slider(minimum=0.1, maximum=2.0, step=0.1, value=1.0, label="Saturation")
            with gr.Row():
                invert_button = gr.Button("Invert Image", size="sm")

            with gr.Row():
                edited_image = gr.Image(label="Edited QR Code", show_download_button=True, show_fullscreen_button=True, visible=False)
                scan_button = gr.Button("Verify QR Code Works", size="sm", visible=False)
                scan_result = gr.Textbox(label="Validation Result of QR Code", interactive=False, visible=False)
                
            used_seed = gr.Number(label="Seed Used", interactive=False)
            
            gr.Markdown(
                """
                ### 🔍 Analyzing Your Creation
                - Is the QR code scannable? Check with your phone camera to see if it can scan it.
                - If not scannable, use the Brightness, Contrast, and Saturation sliders to optimize the QR code for scanning.
                - Does the art style match your prompt? If not, try adjusting the 'Prompt Adherence'.
                - Want more artistic flair? Increase the 'Artistic Freedom'.
                - Need a clearer QR code? Raise the 'QR Code Visibility'.
                """
            )

    def scan_and_display(image):
        if image is None:
            return "No image to scan"
        
        scanned_text = scan_qr_code(image)
        if scanned_text:
            return f"Scanned successfully: {scanned_text}"
        else:
            return "Failed to scan QR code. Try adjusting the settings for better visibility."

    def invert_displayed_image(image):
        if image is None:
            return None
        return invert_image(image)

    scan_button.click(
        scan_and_display,
        inputs=[result_image],
        outputs=[scan_result]
    )

    invert_button.click(
        invert_displayed_image,
        inputs=[result_image],
        outputs=[result_image]
    )

    invert_init_image_button.click(
        invert_init_image_display,
        inputs=[init_image],
        outputs=[init_image]
    )

    brightness.change(
        adjust_image,
        inputs=[result_image, brightness, contrast, saturation],
        outputs=[result_image]
    )
    contrast.change(
        adjust_image,
        inputs=[result_image, brightness, contrast, saturation],
        outputs=[result_image]
    )
    saturation.change(
        adjust_image,
        inputs=[result_image, brightness, contrast, saturation],
        outputs=[result_image]
    )

    # Add logic to show/hide the reference_image_strength slider
    def update_reference_image_strength_visibility(init_image, use_qr_code_as_init_image):
        return gr.update(visible=init_image is not None and not use_qr_code_as_init_image)

    init_image.change(
        update_reference_image_strength_visibility,
        inputs=[init_image, use_qr_code_as_init_image],
        outputs=[reference_image_strength]
    )

    use_qr_code_as_init_image.change(
        update_reference_image_strength_visibility,
        inputs=[init_image, use_qr_code_as_init_image],
        outputs=[reference_image_strength]
    )

    run_btn.click(
        fn=inference,
        inputs=[
            qr_code_content,
            prompt,
            negative_prompt,
            guidance_scale,
            qr_conditioning_scale,
            num_inference_steps,
            seed,
            image_resolution,
            scheduler,
            eta,
            low_threshold,
            high_threshold,
            guess_mode,
            disable_safety_check,
        ],
        outputs=[result_image, used_seed],
        concurrency_limit=20
    )

    # Define login button click behavior
    login_button.click(
        login,
        inputs=[username, password],
        outputs=[app_container, login_message, login_button, login_message]
    )

    # Define password textbox submit behavior
    password.submit(
        login,
        inputs=[username, password],
        outputs=[app_container, login_message, login_button, login_message]
    )

# Load models on launch
#load_models_on_launch()

blocks.queue(max_size=20)
blocks.launch(share=False, show_api=False)