PortraitExplorer/app.py at main · hza2002/PortraitExplorer · GitHub

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import gradio as gr
from dotenv import dotenv_values
from modules import *

cfg = dotenv_values(".env")

with gr.Blocks(theme="nuttea/Softblue", title="智能人像分析器") as demo:
    gr.Markdown(
        """
        # 智能人像分析器
        > 基于讯飞开放平台开发
        """
    )
    with gr.Tab("人脸比对"):
        with gr.Row():
            pic1 = gr.Image(label="图片1", type="filepath")
            pic2 = gr.Image(label="图片2", type="filepath")
        with gr.Row():
            examples = gr.Examples(
                examples=[["examples/pic1.jpeg", "examples/pic2.jpeg"]],
                inputs=[pic1, pic2],
            )
            compare = gr.Button(value="开始比对")
            result = gr.Textbox(label="比对结果")

            def display_compare(data):
                res = f"可信度: {data['score']}\n结果: {data['desc']}"
                return res

            @compare.click(inputs=[pic1, pic2], outputs=result)
            def face_compare(img1_path, img2_path):
                appid, api_secret, api_key = (
                    cfg["FACE_COMPARE_APPID"],
                    cfg["FACE_COMPARE_APISECRET"],
                    cfg["FACE_COMPARE_APIKEY"],
                )
                res = FaceCompare(
                    appid, api_secret, api_key, img1_path, img2_path
                ).run()
                res = display_compare(res)
                return res

    with gr.Tab("人脸特征分析"):
        with gr.Row():
            img = gr.Image(label="分析图片", type="filepath")
            with gr.Column():
                examples = gr.Examples(
                    examples=[["examples/pic1.jpeg"], ["examples/pic2.jpeg"]],
                    inputs=[img],
                )
                result = gr.TextArea(label="分析结果")
                analyze = gr.Button(value="开始分析")

        def display_analyze(data):
            result = ""
            for item in data:
                result += f"{item['type']}: {item['desc']}\n"
            return result

        @analyze.click(inputs=img, outputs=result)
        def face_analyze(img_path):
            appid, api_key = (
                cfg["FACE_ANALYZE_APPID"],
                cfg["FACE_ANALYZE_APIKEY"],
            )
            res = FaceFeature(appid, api_key, img_path).face_local_analysis()
            res = display_analyze(res)
            return res


demo.launch()