Create app.py

app.py

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+fai-lanthos
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+app.py
+
+comdoleger's picture
+comdoleger
+Update app.py
+d677fb1
+VERIFIED
+about 1 hour ago
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+7.87 kB
+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")
+
+
+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 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 != "COMPLETED":
+ # Polling with timeout for long-running tasks
+ output = run_request.output(timeout=60)
+ else:
+ output = run_request.output()
+ print(f"Job output: {output}")
+ except Exception as e:
+ print(f"An error occurred: {e}")
+ 
+
+ 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 process_generate(fore, prompt, image_width, image_height, intensity, mode, refprompt): 
+ 
+ print(f"MODE: {mode}, INTENSITY: {intensity}, WIDTH: {image_width}, HEIGHT: {image_height}")
+ 
+
+ forestr = image_to_base64(fore.convert("RGBA"))
+ data = {
+ "foreground_image64": forestr,
+ "prompt" : prompt,
+ "mode" : mode,
+ "intensity" : float(intensity),
+ "width" : int(image_width),
+ "height" : int(image_height),
+ "refprompt" : refprompt
+ }
+ 
+ image = process(data, api, api_key)
+
+ return image
+
+
+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;
+ }
+ """
+block = gr.Blocks(css=css, title="## F.ai Lanthos").queue()
+with block:
+ gr.HTML("""
+ <center><h1 style="color:#000">Fotographer AI Lanthos</h1></center>""")
+ 
+ gr.HTML('''
+ <div>
+ <a style="display:inline-block; margin-left: .5em" href="https://app.fotographer.ai/home"><img src="https://img.shields.io/badge/2310.15110-f9f7f7?logo=data:image/png;base64,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"></a>
+ <a style="display:inline-block; margin-left: .5em" href='https://app.fotographer.ai/home'><img src='https://img.shields.io/github/stars/SUDO-AI-3D/zero123plus?style=social' /></a>
+ Check out our App<a href="https://app.fotographer.ai/home">Fotographer.ai</a>! 
+ </div>
+ ''')
+
+ with gr.Row():
+ gr.Markdown("### F.ai Lanthos: Real Composite Photography in 2 minutes!")
+ with gr.Row():
+ fore = gr.Image(source='upload', 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')
+ with gr.Column():
+ image_width = gr.Slider(label="Image Width", minimum=256, maximum=1500, value=1024, step=64)
+ image_height = gr.Slider(label="Image Height", minimum=256, maximum=1500, value=1024, step=64)
+ 
+ with gr.Row():
+ intensity = gr.Slider(label="Refiner Strength", minimum=1, maximum=7, value=3, step=0.5)
+ generate_button = gr.Button(value="Generate")
+ 
+
+
+
+ ips = [fore, prompt, image_width, image_height, intensity, mode, refprompt]
+ generate_button.click(fn=process_generate, inputs=ips, outputs=[result_gallery])
+
+
+block.launch()
+