Create app.py

app.py

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+from huggingface_hub import snapshot_download
+from insightface.app import FaceAnalysis
+import numpy as np
+import cv2
+import gradio as gr
+
+# 下载模型
+snapshot_download(
+    "fal/AuraFace-v1",
+    local_dir="models/auraface",
+)
+
+# 初始化FaceAnalysis
+face_app = FaceAnalysis(
+    name="auraface",
+    providers=["CUDAExecutionProvider", "CPUExecutionProvider"],
+    root=".",
+)
+
+def get_embedding(image):
+    # 将图片转换为OpenCV格式
+    cv2_image = np.array(image.convert("RGB"))
+    cv2_image = cv2_image[:, :, ::-1]
+    
+    # 获取人脸嵌入
+    faces = face_app.get(cv2_image)
+    if len(faces) > 0:
+        return faces[0].normed_embedding
+    else:
+        return None
+
+def calculate_similarity(image1, image2):
+    # 获取两张图片的嵌入
+    embedding1 = get_embedding(image1)
+    embedding2 = get_embedding(image2)
+    
+    if embedding1 is not None and embedding2 is not None:
+        # 计算余弦相似度
+        similarity = np.dot(embedding1, embedding2) / (np.linalg.norm(embedding1) * np.linalg.norm(embedding2))
+        return f"图片相似度: {similarity:.4f}"
+    else:
+        return "无法检测到人脸或计算相似度"
+
+# 创建Gradio界面
+iface = gr.Interface(
+    fn=calculate_similarity,
+    inputs=[gr.Image(type="pil"), gr.Image(type="pil")],
+    outputs="text",
+    title="图片相似度计算",
+    description="上传两张图片，计算它们的相似度。"
+)
+
+# 启动Gradio应用
+iface.launch(share = True)