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import gradio as gr
import requests
import json
from PIL import Image
def compare_face(frame1, frame2):
url = "http://127.0.0.1:8000/api/compare_face"
files = {'image1': open(frame1, 'rb'), 'image2': open(frame2, 'rb')}
r = requests.post(url=url, files=files)
faces = None
try:
image1 = Image.open(frame1)
image2 = Image.open(frame2)
face1 = None
face2 = None
data = r.json().get('data')
if data.get('face1') is not None:
face = data.get('face1')
x1 = face.get('x1')
y1 = face.get('y1')
x2 = face.get('x2')
y2 = face.get('y2')
if x1 < 0:
x1 = 0
if y1 < 0:
y1 = 0
if x2 >= image1.width:
x2 = image1.width - 1
if y2 >= image1.height:
y2 = image1.height - 1
face1 = image1.crop((x1, y1, x2, y2))
face_image_ratio = face1.width / float(face1.height)
resized_w = int(face_image_ratio * 150)
resized_h = 150
face1 = face1.resize((int(resized_w), int(resized_h)))
if data.get('face2') is not None:
face = data.get('face2')
x1 = face.get('x1')
y1 = face.get('y1')
x2 = face.get('x2')
y2 = face.get('y2')
if x1 < 0:
x1 = 0
if y1 < 0:
y1 = 0
if x2 >= image2.width:
x2 = image2.width - 1
if y2 >= image2.height:
y2 = image2.height - 1
face2 = image2.crop((x1, y1, x2, y2))
face_image_ratio = face2.width / float(face2.height)
resized_w = int(face_image_ratio * 150)
resized_h = 150
face2 = face2.resize((int(resized_w), int(resized_h)))
if face1 is not None and face2 is not None:
new_image = Image.new('RGB',(face1.width + face2.width + 10, 150), (80,80,80))
new_image.paste(face1,(0,0))
new_image.paste(face2,(face1.width + 10, 0))
faces = new_image.copy()
elif face1 is not None and face2 is None:
new_image = Image.new('RGB',(face1.width + face1.width + 10, 150), (80,80,80))
new_image.paste(face1,(0,0))
faces = new_image.copy()
elif face1 is None and face2 is not None:
new_image = Image.new('RGB',(face2.width + face2.width + 10, 150), (80,80,80))
new_image.paste(face2,(face2.width + 10, 0))
faces = new_image.copy()
except:
pass
return [r.json(), faces]
with gr.Blocks() as demo:
gr.Markdown(
"""
# Face Recognition
Get your own Face Recognition Server by duplicating this space.<br/>
Or run on your own machine using docker.<br/>
```docker run -it -p 7860:7860 --platform=linux/amd64 \
-e LICENSE_KEY="YOUR_VALUE_HERE" \
registry.hf.space/faceonlive-face-recognition-sdk:latest ```<br/><br/>
Contact us at https://faceonlive.com for issues and support.<br/>
"""
)
with gr.Row():
with gr.Column():
compare_face_input1 = gr.Image(type='filepath', height=480)
gr.Examples(['gradio/examples/1.jpg', 'gradio/examples/2.jpg'],
inputs=compare_face_input1)
compare_face_button = gr.Button("Compare Face")
with gr.Column():
compare_face_input2 = gr.Image(type='filepath', height=480)
gr.Examples(['gradio/examples/3.jpg', 'gradio/examples/4.jpg'],
inputs=compare_face_input2)
with gr.Column():
compare_face_output = gr.Image(type="pil", height=150)
compare_result_output = gr.JSON(label='Result')
compare_face_button.click(compare_face, inputs=[compare_face_input1, compare_face_input2], outputs=[compare_result_output, compare_face_output])
demo.launch(server_name="0.0.0.0", server_port=7860) |