File size: 4,999 Bytes
c88be80
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
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
    We offer SDKs for Face Recognition, Face Liveness Detection(Face Anti-Spoofing), and ID Card Recognition.<br/>
    Besides that, we can provide several AI models and development services in machine learning.

    ## Simple Installation & Simple API
    ```
    sudo docker pull kbyai/face-recognition:latest
    sudo docker run -e LICENSE="xxxxx" -p 8081:8080 -p 9001:9000 kbyai/face-recognition:latest
    ```      
    ## KYC Verification Demo
    https://github.com/kby-ai/KYC-Verification    
    """
    )
    with gr.TabItem("Face Recognition"):
        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])

demo.launch(server_name="0.0.0.0", server_port=9000)