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hermes/MCP_face_recognition/face_recognition_mcp.py

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+import os, cv2, face_recognition
+from pathlib import Path
+from dotenv import load_dotenv
+from mcp.server.fastmcp import FastMCP
+load_dotenv();mcp=FastMCP("Alfred Face Recognition");DB=Path(os.getenv('FACE_DB','/home/hermes/faces'));T=float(os.getenv('FACE_TOLERANCE','0.48'))
+def encodings():
+    known=[]
+    for person in DB.iterdir() if DB.exists() else []:
+        if not person.is_dir():continue
+        for f in person.glob('*'):
+            try:
+                im=face_recognition.load_image_file(str(f)); es=face_recognition.face_encodings(im)
+                if es:known.append((person.name,es[0]))
+            except Exception:pass
+    return known
+@mcp.tool()
+def identify_people(camera_index:int=0):
+    cap=cv2.VideoCapture(camera_index);ok,frame=cap.read();cap.release()
+    if not ok:raise RuntimeError('Caméra indisponible')
+    rgb=cv2.cvtColor(frame,cv2.COLOR_BGR2RGB); locs=face_recognition.face_locations(rgb); es=face_recognition.face_encodings(rgb,locs); known=encodings();out=[]
+    for e in es:
+        name='inconnu';best=T
+        for n,k in known:
+            d=face_recognition.face_distance([k],e)[0]
+            if d<best:name,best=n,d
+        out.append({'name':name,'distance':float(best)})
+    return {'count':len(out),'people':out,'unknown_count':sum(x['name']=='inconnu' for x in out)}
+if __name__=='__main__':mcp.run()