File size: 5,616 Bytes
c88be80 ad55b16 28dcf2b c88be80 28dcf2b c88be80 fecade2 c88be80 387d1ef |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 |
import gradio as gr
import requests
import datadog_api_client
from PIL import Image
def compare_face(frame1, frame2):
url = "http://127.0.0.1:8080/compare_face"
files = {'file1': open(frame1, 'rb'), 'file2': open(frame2, 'rb')}
r = requests.post(url=url, files=files)
html = None
faces = None
compare_result = r.json().get('compare_result')
compare_similarity = r.json().get('compare_similarity')
html = ("<table>"
"<tr>"
"<th>Compare Result</th>"
"<th>Value</th>"
"</tr>"
"<tr>"
"<td>Result</td>"
"<td>{compare_result}</td>"
"</tr>"
"<tr>"
"<td>Similarity</td>"
"<td>{compare_similarity}</td>"
"</tr>"
"</table>".format(compare_result=compare_result, compare_similarity=compare_similarity))
try:
image1 = Image.open(frame1)
image2 = Image.open(frame2)
face1 = None
face2 = None
if r.json().get('face1') is not None:
face = r.json().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 r.json().get('face2') is not None:
face = r.json().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 [faces, html]
with gr.Blocks() as demo:
gr.Markdown(
"""
# KBY-AI - Face Recognition
We offer SDKs for face recognition, liveness detection(anti-spoofing) and ID card recognition.
We also specialize in providing outsourcing services with a variety of technical stacks like AI(Computer Vision/Machine Learning), Mobile apps, and web apps.
##### KYC Verification Demo - https://github.com/kby-ai/KYC-Verification-Demo-Android
##### ID Capture Web Demo - https://id-document-recognition-react-alpha.vercel.app
##### Documentation - Help Center - https://docs.kby-ai.com
"""
)
with gr.TabItem("Face Recognition"):
gr.Markdown(
"""
##### Docker Hub - https://hub.docker.com/r/kbyai/face-recognition
```bash
sudo docker pull kbyai/face-recognition:latest
sudo docker run -e LICENSE="xxxxx" -p 8081:8080 -p 9001:9000 kbyai/face-recognition:latest
```
"""
)
with gr.Row():
with gr.Column():
compare_face_input1 = gr.Image(type='filepath')
gr.Examples(['face_examples/1.jpg', 'face_examples/3.jpg', 'face_examples/5.jpg', 'face_examples/7.jpg', 'face_examples/9.jpg'],
inputs=compare_face_input1)
compare_face_button = gr.Button("Compare Face")
with gr.Column():
compare_face_input2 = gr.Image(type='filepath')
gr.Examples(['face_examples/2.jpg', 'face_examples/4.jpg', 'face_examples/6.jpg', 'face_examples/8.jpg', 'face_examples/10.jpg'],
inputs=compare_face_input2)
with gr.Column():
compare_face_output = gr.Image(type="pil").style(height=150)
compare_result_output = gr.HTML(label='Result')
compare_face_button.click(compare_face, inputs=[compare_face_input1, compare_face_input2], outputs=[compare_face_output, compare_result_output])
gr.HTML('<a href="https://visitorbadge.io/status?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2Fkby-ai%2FFaceRecognition"><img src="https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2Fkby-ai%2FFaceRecognition&countColor=%23263759" /></a>')
demo.launch(server_name="0.0.0.0", server_port=7860) |