Create app.py

app.py

@@ -0,0 +1,22 @@
+import gradio as gr
+import cv2
+from insightface.app import FaceAnalysis
+import torch
+
+app = FaceAnalysis(name="buffalo_l", providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])
+app.prepare(ctx_id=0, det_size=(640, 640))
+
+def calculate(photo):
+    image = cv2.imread(photo)
+    faces = app.get(image)
+    faceid_embeds = torch.from_numpy(faces[0].normed_embedding).unsqueeze(0)
+    return faceid_embeds
+    
+with gr.Blocks() as demo:
+    face_photo = gr.Image(label="Photo", type="filepath")
+    output = gr.JSON()
+    greet_btn = gr.Button("Calculate")
+    greet_btn.click(fn=calculate, inputs=face_photo, outputs=output, api_name="calculate_face_embedding")
+
+if __name__ == "__main__":
+    demo.launch()