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import gradio as gr
from prodiapy import Prodia
from PIL import Image
from io import BytesIO
import requests
import random
import os
import base64
client = Prodia()
def infer(source, target):
if source_image is None or target_image is None:
return
source_url = upload_image(source)
target_url = upload_image(target)
job = client.faceswap(source_url=source_url, target_url=target_url)
res = client.wait(job, raise_on_fail=False)
if res.failed:
return
return res.image_url
def upload_image(file):
files = {'file': open(file, 'rb')}
img_id = requests.post(os.getenv("IMAGE_API_1"), files=files).json()['id']
payload = {
"content": "",
"nonce": f"{random.randint(1, 10000000)}H9X42KSEJFNNH",
"replies": [],
"attachments": [img_id]
}
res = requests.post(os.getenv("IMAGE_API_2"), json=payload, headers={"x-session-token": os.getenv("SESSION_TOKEN")})
return f"{os.getenv('IMAGE_API_1')}/{img_id}/{res.json()['attachments'][0]['filename']}"
def image_to_base64(image: Image):
# Convert the image to bytes
buffered = BytesIO()
image.save(buffered, format="PNG") # You can change format to PNG if needed
# Encode the bytes to base64
img_str = base64.b64encode(buffered.getvalue())
return img_str.decode('utf-8') # Convert bytes to string
with gr.Blocks() as demo:
with gr.Column():
gr.HTML("<h1><center>Face Swap</center></h1>")
with gr.Row():
with gr.Row():
source_image = gr.Image(type="filepath", label="Source Image")
target_image = gr.Image(type="filepath", label="Target Image")
with gr.Column():
result = gr.Image()
run_button = gr.Button("Swap Faces", variant="primary")
gr.Examples(
examples=[
[
"/examples/example1.jpg",
"/examples/example2.jpg"
]
],
fn=infer,
inputs=[source_image, target_image],
outputs=[result]
)
run_button.click(fn=infer, inputs=[source_image, target_image], outputs=[result])
demo.queue(max_size=20, api_open=False).launch(show_api=False, max_threads=400)
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