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import sys |
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sys.path.append('.') |
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sys.path.append('./face_recognition1') |
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import os |
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import io |
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import cv2 |
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import base64 |
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import json |
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import gradio as gr |
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import requests |
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import numpy as np |
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from io import BytesIO |
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import configparser |
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import numpy as np |
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from PIL import Image |
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from face_recognition1.run import match_image |
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def face_recognition_on_file(file1, file2): |
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img1 = cv2.imread(file1) |
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img2 = cv2.imread(file2) |
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response = match_image(img1, img2) |
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return response |
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with gr.Blocks() as demo: |
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gr.Markdown( |
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""" |
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# FacePlugin Online Demo |
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""" |
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) |
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with gr.TabItem("Face Recognition"): |
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with gr.Row(): |
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with gr.Column(): |
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first_input = gr.Image(type='filepath') |
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gr.Examples(['images/rec_5.jpg', 'images/rec_1.jpg', 'images/9.png', 'images/rec_3.jpg'], |
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inputs=first_input) |
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start_button = gr.Button("Run") |
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with gr.Column(): |
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second_input = gr.Image(type='filepath') |
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gr.Examples(['images/rec_6.jpg', 'images/rec_2.jpg', 'images/10.jpg', 'images/rec_4.jpg'], |
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inputs=second_input) |
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with gr.Column(): |
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app_output = [gr.JSON()] |
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start_button.click(face_recognition_on_file, inputs=[first_input, second_input], outputs=app_output) |
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demo.queue().launch(share=True) |
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