import os
import math
import gradio as gr
import numpy as np
import requests
import json
import base64
from PIL import Image
from io import BytesIO
import runpod
from enum import Enum


api_key = os.getenv("FAI_API_KEY")
api = os.getenv("FAI_API")
rmbgkey = os.getenv("RMBGKEY")

def rmbg(pil_image):
    
    # Convert PIL image to bytes
    image_bytes = BytesIO()
    pil_image.save(image_bytes, format='PNG')
    image_bytes.seek(0)
    
    # Send the image to the remove.bg API
    response = requests.post(
        'https://api.remove.bg/v1.0/removebg',
        files={'image_file': ('filename.png', image_bytes, 'image/png')},
        data={'size': 'auto'},
        headers={'X-Api-Key': rmbgkey}
    )
    
    if response.status_code == 200:        
        # Convert the bytes response to a PIL image
        result_image = Image.open(BytesIO(response.content))
        return result_image
    else:
        return None

def image_to_base64(image):
    # Open the image file
    with image:
        # Create a buffer to hold the binary data
        buffered = BytesIO()
        # Save the image in its original format to the buffer
        #print(image.format)
        image.save(buffered, format="PNG")
        # Get the byte data from the buffer
        binary_image_data = buffered.getvalue()
        # Encode the binary data to a base64 string
        base64_image = base64.b64encode(binary_image_data).decode("utf-8")
        return base64_image

def create_square_image(image):
    """
    Create a new square image with the side length equal to the largest dimension
    of the original image and paste the original image at the center on a transparent canvas.

    :param image: A PIL image.
    :return: A new square PIL image.
    """
    original_width, original_height = image.size
    new_side_length = max(original_width, original_height)

    # Create a new square image with a transparent background
    new_image = Image.new("RGBA", (new_side_length, new_side_length), (255, 255, 255, 0))

    # Calculate the position to paste the original image on the new square canvas
    paste_x = (new_side_length - original_width) // 2
    paste_y = (new_side_length - original_height) // 2

    # Paste the original image onto the new square canvas using the alpha channel as a mask
    new_image.paste(image, (paste_x, paste_y), image)

    return new_image
     
def process(data, api, api_key):
    
    runpod.api_key = api_key
    input_payload = {"input": data }

    try:
        endpoint = runpod.Endpoint(api)
        run_request = endpoint.run(input_payload)

        # Initial check without blocking, useful for quick tasks
        status = run_request.status()
        print(f"Initial job status: {status}")
        if status=="IN_QUEUE":
            gr.Info("Queued 🚶🚶🚶🚶!", duration=15)

        if status != "COMPLETED":
            # Polling with timeout for long-running tasks
            output = run_request.output(timeout=120)
        else:
            output = run_request.output()
        print(f"Job output: {output}")
    except Exception as e:
        print(f"An error occurred: {e}")
        status = run_request.status()
        if status=="FAILED":
            raise gr.Error(f"An error occured 💥! {e}", duration=5)
        if status=="TIMED_OUT":
            raise gr.Error("Sorry we could not secure a worker for you ⏳! Try again", duration=5)
        

    image_data = output['image']
    # Decode the Base64 string
    image_bytes = base64.b64decode(image_data)
    # Convert binary data to image
    image = Image.open(BytesIO(image_bytes))
    
    return image

def resize_to_fit(max_size, original_size):
    """
    Calculate the new size for an image to fit within max_size while maintaining the aspect ratio.

    :param max_size: Maximum allowed size as a tuple (width, height).
    :param original_size: Original size of the image as a tuple (width, height).
    :return: New size as a tuple (new_width, new_height) that fits within max_size while maintaining the aspect ratio.
    """
    original_width, original_height = original_size
    max_width, max_height = max_size

    # Calculate the scaling factor to maintain aspect ratio
    width_ratio = max_width / original_width
    height_ratio = max_height / original_height
    scaling_factor = min(width_ratio, height_ratio)

    # Calculate the new size while maintaining the aspect ratio
    new_width = int(original_width * scaling_factor)
    new_height = int(original_height * scaling_factor)

    return new_width, new_height

    
def process_generate(fore, prompt, intensity, mode, refprompt, isrmbg): 
    
    if isrmbg:
        try:
            rmbgfore = rmbg(fore)
            if rmbgfore is not None:
                fore = rmbgfore.convert("RGBA")
                print(f"Background removed!")
        except:
            pass
         
    fore = create_square_image(fore)
    size = fore.size
    image_width = size[0]
    image_height = size[1]
    
    if size[0]*size[1]<=(768*768):
        gr.Warning("ℹ️ The input image resolution is low, it might lead to some deformation!")
        
    if size[0]*size[1]>(1500*1500):
        gr.Warning("ℹ️ The input image size is too big, I will lower it!")
        image_width, image_height = resize_to_fit((1500,1500), (image_width, image_height))
        fore.resize((1500,1500))

    
        
    
    forestr = image_to_base64(fore.convert("RGBA"))    
    data = {
        "foreground_image64": forestr,
        "prompt" : prompt,
        "mode" : mode,
        "intensity" : float(intensity),
        "width" : 1500,
        "height" : 1500,
        "refprompt" : refprompt
    }
    print(f"DATA: {data}")
    
    '''
    data = {
        "foreground_image64": forestr,
        "prompt" : "There is Perfume, nestled on a crystalline cliff of glistening snow, under a celestial night sky adorned with constellations and swirling galaxies, framed by ethereal, blue flames that dance gracefully in the icy air",
        "mode" : "full", #refiner, full
        "intensity" : 3.0,
        "width" : 1000,
        "height" : 1000,
        "refprompt" : " transparent glass "    
    }
    '''    
    image = process(data, api, api_key)

    return image



def update_value(val):
  return val

class Stage(Enum):
    FIRST_STAGE = "first-stage"
    SECOND_STAGE = "refiner"
    FULL = "full"

css="""#disp_image {
    text-align: center; /* Horizontally center the content */
}
#share-btn-container {padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; max-width: 13rem; margin-left: auto;}
div#share-btn-container > div {flex-direction: row;background: black;align-items: center}
#share-btn-container:hover {background-color: #060606}
#share-btn {all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.5rem !important; padding-bottom: 0.5rem !important;right:0;}
#share-btn * {all: unset}
#share-btn-container div:nth-child(-n+2){width: auto !important;min-height: 0px !important;}
#share-btn-container .wrap {display: none !important}
#share-btn-container.hidden {display: none!important}
#duplicate-button {
    margin-left: auto;
    color: #fff;
    background: #1565c0;
  }
  body {
            font-family: Arial, sans-serif;
            background-color: #f4f4f9;
            margin: 0;
            padding: 0;
            display: flex;
            justify-content: center;
            align-items: center;
            height: 100vh;
            color: #333;
        }
        .container {
            background-color: #fff;
            padding: 20px 40px;
            border-radius: 10px;
            box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
            text-align: center;
        }
        h1 {
            color: #4a90e2;
        }
        a {
            color: #4a90e2;
            text-decoration: none;
            font-weight: bold;
        }
        a:hover {
            text-decoration: underline;
        }
        .emoji {
            font-size: 1.5em;
        }
        """
block = gr.Blocks(css=css, title="## F.ai Fuzer").queue()
with block:
    
    gr.HTML('''
        
        <div class="container">
        <h1>🔧 F.ai Fuzer v0.1: Transcending image Generation Control!</h1>
        <h2>Control Your Creativity with Unmatched Precision: </h2>
        <p>F.ai Fuzer v0.1 empowers you to seamlessly blend foreground elements with any background, while maintaining the shape and style consistency of the foreground. This tool transcends traditional image generation methods by giving you unprecedented control over the final output.</p>
        <h2>Features:</h2>
        <ul>
            <li>🖼️ <strong>Consistent Foreground Style:</strong> Keep the foreground's shape and style intact across various backgrounds.</li>
            <li>🌄 <strong>Seamless Blending:</strong> Effortlessly blend foreground elements with any background for a natural look.</li>
            <li>🎨 <strong>Custom Background Control:</strong> Choose or generate backgrounds that perfectly match your creative vision.</li>
            <li>⚙️ <strong>Easy Integration:</strong> Integrates smoothly with your existing workflow and tools.</li>
        </ul>

        <h2>Step-by-Step Instructions</h2>
        <p>Follow these instructions to control the generation of backgrounds while keeping the foreground's shape and style consistent:</p>
        <ul>
            <li>
                <span class="emoji">📝</span>
                <strong>Step 1: Describe the Background</strong>
                <p>Start by providing a detailed description of the background you want to create.</p>
                <div class="example">
                    <p><strong>Example:</strong> "A Perfume Bottle nestled on a crystalline cliff of glistening snow, overlooking a serene, moonlit valley."</p>
                </div>
            </li>
            <li>
                <span class="emoji">💡</span>
                <strong>Step 2: Describe the Foreground</strong>
                <p>Next, describe the texture, lighting, and style of the foreground element.</p>
                <div class="example">
                    <p><strong>Example:</strong> "A transparent glass perfume bottle, vibrant, sunset lighting reflecting off its surface."</p>
                </div>
            </li>
            <li>
                <span class="emoji">🎚️</span>
                <strong>Step 3: Adjust the Intensity</strong>
                <p>Decide how much change you want to apply to the image. Adjust the intensity to balance between keeping consistency and introducing new elements.</p>
            </li>
        </ul>
    </div>
        ''')
    gr.HTML("""
            <center><h2><a href="https://test-apidash-dot-lightr-fotographer-app-dot-fotographer-ai.an.r.appspot.com/login.html">🔗 Full Release Here:</a></h2></center>""")

    with gr.Row():
        gr.Markdown("### F.ai Fuzer: Real Composite Photography in 2 minutes!")
    with gr.Row():
        fore = gr.Image(image_mode='RGBA', type="pil", label="Foreground Image", height=400)
        with gr.Column():
            
            result_gallery = gr.Image(label='Output')  #gr.Gallery(height=400, object_fit='contain', label='Outputs')
    with gr.Row():
        prompt = gr.Textbox(label="Prompt")
        with gr.Column():
            refprompt = gr.Textbox(label="Refiner Prompt")
    with gr.Row():
        mode = gr.Radio(choices=[e.value for e in Stage],
                            value=Stage.FULL.value,
                            label="Generation Mode", type='value')
        mode.change(fn=update_value, inputs=mode, outputs=mode)
        
        with gr.Column():
            gr.HTML('''
                <div class="container">
                <h1>🚀 For more freedom of usage, please use our SDK module</h1>
                <p>👤 by logging in or signing up to our API dashboard and buying some credits:</p>
                <p><a href="https://test-apidash-dot-lightr-fotographer-app-dot-fotographer-ai.an.r.appspot.com/login.html">🔗 API Dashboard</a></p>
                </div>
                ''')
            
    with gr.Row():
        intensity = gr.Slider(label="Refiner Strength", minimum=1.0, maximum=7.0, value=3.0, step=0.5)
        intensity.change(fn=update_value, inputs=intensity, outputs=intensity)
        isrmbg = gr.Checkbox(label="Remove Background")
        isrmbg.change(fn=update_value, inputs=isrmbg, outputs=isrmbg)
        generate_button = gr.Button(value="Generate")
        
    gr.HTML("""
            <center><h2><a href="https://test-apidash-dot-lightr-fotographer-app-dot-fotographer-ai.an.r.appspot.com/login.html">🔗 Check Out our other Projects Here!:</a></h2></center>""")
    
    ips = [fore, prompt, intensity, mode, refprompt, isrmbg]
    generate_button.click(fn=process_generate, inputs=ips, outputs=[result_gallery])


block.launch()