app.py

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")

#fore, prompt, intensity, mode, refprompt, isrmbg
example_list = [
 [
 "examples/in1.png",
 "A Bottle, placed on a rustic wooden table, viewed from a slight above angle, overlooking a serene beach, with seashells and driftwood artfully scattered around, bathed in the warm glow of the setting sun",
 2.50,
 "full",
 "A transparent Bottle with a black cap and a semi transparent liquide, Sunset",
 False,
 "examples/out1.png",
 ],
 [
 "examples/in2.jpg",
 "A Perfume bottle, perched delicately on a rock by the ocean, with a breathtaking sunset casting a golden glow over the waves",
 3.50,
 "full",
 "A glass perfume Bottle, with a yellow lequide and a black cap, sunset, transparent",
 True,
 "examples/out3.png",
 ],
 [
 "examples/in3.jpg",
 "A car, on a high-tech city street at night, surrounded by neon lights and holographic billboards, with sleek skyscrapers and flying cars in the background, a glowing cyber-road beneath",
 3.0,
 "full",
 "A light grey Car, vibrant, reflections",
 True,
 "examples/out3.png",
 ],
]

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>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, check out our API</h1>
 <p>👤 You can test with free credits:</p>
 <h2><a href="https://test-apidash-dot-lightr-fotographer-app-dot-fotographer-ai.an.r.appspot.com/login.html">🔗 API Dashboard</a></h2>
 </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('''
 
 <div class="container">
 <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>
 </div>
 ''')
 
 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>""")
 
 with gr.Row():
 imgholder = gr.Image(visible=False, label='Outputs')
 gr.Examples(
 fn=lambda *args: [args[-1]],
 examples=example_list,
 inputs=[
 fore, prompt, intensity, mode, refprompt, isrmbg, imgholder
 ],
 
 )

 
 ins = [fore, prompt, intensity, mode, refprompt, isrmbg]
 generate_button.click(fn=process_generate, inputs=ins, outputs=[result_gallery])



block.launch()