remove old refimg.encodings generation, we now do this when we make a person/refimg, so its always done before an AI job needs to use it

pa_job_manager.py

@@ -216,13 +216,15 @@ class Refimg(Base):
     __tablename__ = "refimg"
     id = Column(Integer, Sequence('refimg_id_seq'), primary_key=True )
     fname = Column(String(256), unique=True, nullable=False)
-    face = Column(LargeBinary)
+    face = Column(LargeBinary, unique=True, nullable=False)
     thumbnail = Column(String, unique=False, nullable=True)
-    encodings = Column(LargeBinary)
     created_on = Column(Float)
+    orig_w = Column(Integer)
+    orig_h = Column(Integer)
+    face_locn = Column(String)
 
     def __repr__(self):
-        return f"<id: {self.id}, fname: {self.fname}, created_on: {self.created_on}, encodings: {self.encodings}>"
+        return f"<id: {self.id}, fname: {self.fname}, created_on: {self.created_on}>"
 
 class Face(Base):
     __tablename__ = "face"
@@ -949,10 +951,6 @@ def JobProcessAI(job):
     p = session.query(Path).filter(Path.path_prefix==path).first()
     job.num_files=p.num_files
 
-    people = session.query(Person).all()
-    for person in people:
-        generateKnownEncodings(person)
-    
     RunFuncOnFilesInPath( job, path, ProcessAI, True )
 
     FinishJob(job, "Finished Processesing AI")
@@ -1099,22 +1097,6 @@ def generateUnknownEncodings(im):
     return unknown_encodings
 
 
-def generateKnownEncodings(person):
-    for refimg in person.refimg:
-        file = 'reference_images/'+refimg.fname
-        stat = os.stat(file)
-        if refimg.created_on and stat.st_ctime < refimg.created_on:
-            print("OPTIM: skipping re-creating encoding for refimg because file has not changed")
-            continue
-        img = face_recognition.load_image_file(file)
-        location = face_recognition.face_locations(img)
-        encodings = face_recognition.face_encodings(img, known_face_locations=location)
-        print(f"INFO: created encoding for refimg of {file}")
-        refimg.encodings = encodings[0].tobytes()
-        refimg.created_on = time.time()
-        session.add(refimg)
-    session.commit()
-
 def compareAI(known_encoding, unknown_encoding):
     results = face_recognition.compare_faces([known_encoding], unknown_encoding, tolerance=0.55)
     return results