import os
import gradio as gr
import requests
import base64
from io import BytesIO
from PIL import Image
count = 0
def image_to_base64(image):
buffered = BytesIO()
image.save(buffered, format="PNG")
return base64.b64encode(buffered.getvalue()).decode('utf-8')
def base64_to_image(base64_str):
return Image.open(BytesIO(base64.b64decode(base64_str + '=' * (-len(base64_str) % 4))))
def search_face(file):
global count
url = os.environ.get("SERVER_URL")
try:
image = Image.open(file)
image_base64 = image_to_base64(image)
r = requests.post(url=url, json={"token": os.environ.get("ACCESS_TOKEN"), "type": "novip", "image": image_base64})
except:
raise gr.Error("Please select image file!")
if r.text == "No matches":
gr.Info("No images found.")
return [], count
try:
res = r.json().get('img_array')
out_array = []
for item in res:
out_array.append((base64_to_image(item["image"]), item["url"]))
count += 1
return out_array, count
except:
raise gr.Error("Try again.")
with gr.Blocks() as demo:
gr.Markdown(
"""
# Search Your Face Online For Free
## For more detailed information, please check on our website.
## [FaceOnLive: On-premises ID Verification, Biometric Authentication Solution Provider](https://faceonlive.com)
## For premium support or partnership inquiries, contact us.
"""
)
with gr.Row():
with gr.Column(scale=1):
image = gr.Image(type='filepath', height=480)
search_face_button = gr.Button("Search Face")
with gr.Column(scale=2):
output = gr.Gallery(label="Found Images", columns=[4], object_fit="contain", height="auto")
countwg = gr.Number(label="Count")
gr.Examples(['examples/1.jpg', 'examples/2.jpg'], inputs=image, cache_examples=True, cache_mode='lazy', fn=search_face, outputs=[output, countwg])
search_face_button.click(search_face, inputs=image, outputs=[output, countwg], api_name=False)
gr.HTML('')
demo.queue(api_open=False).launch(server_name="0.0.0.0", server_port=7860, show_api=False)