now using new face linking code, and working, removed many debugs, needs work (around log commits). Also put a quick hack to create Bin path on init, but need to rethink this bit

pa_job_manager.py

@@ -954,10 +954,8 @@ def WrapperForScanFileForPerson(job, entry):
         ppl=session.query(Person).filter(Person.tag==which_person).all()
     
     if entry.type.name == 'Image':
-        print( f"JobRunAIOn: file to process had id: {entry.id}" )
         for person in ppl:
-            print( f"call ==  ScanFileForPerson( {entry.id}, {person.id}, force=False )" )
+            ScanFileForPerson( job, entry, person.id, force=False)
-            ScanFileForPerson( entry, person.id, force=False)
     return
 
 def JobRunAIOn(job):
@@ -967,26 +965,22 @@ def JobRunAIOn(job):
         ppl=session.query(Person).all()
     else:
         ppl=session.query(Person).filter(Person.tag==which_person).all()
-    print( "JobRunAIOn() called" )
+
+    # FIXME: probably shouldbe elsewhere, but this is optmised so if refimgs exist for ppl, then it wont regen them
     for person in ppl:
-        print( f"person={person.tag}" )
+        generateKnownEncodings(person)
 
     for jex in job.extra:
         if 'eid-' in jex.name:
             entry=session.query(Entry).get(jex.value)
-            print( f'en={entry.name}, {entry.type.name}' )
             if entry.type.name == 'Directory':
                 ProcessFilesInDir( job, entry, WrapperForScanFileForPerson )
             elif entry.type.name == 'Image':
                 which_file=session.query(Entry).join(File).filter(Entry.id==jex.value).first()
-                print( f"JobRunAIOn: file to process had id: {which_file.id}" )
                 for person in ppl:
-                    print( f"call ==  ScanFileForPerson( {which_file.id}, {person.id}, force=False )" )
+                    ScanFileForPerson( job, which_file, person.id, force=False)
-                    ScanFileForPerson( which_file, person.id, force=False)
             else:
                 AddLogForJob( job, f'Not processing Entry: {entry.name} - not an image' )
-    #print(" HARD EXITING to keep testing " )
-    #exit( -1 )
     FinishJob(job, "Finished Processesing AI")
     return
  
@@ -1093,6 +1087,7 @@ def generateKnownEncodings(person):
         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)
@@ -1105,8 +1100,7 @@ def compareAI(known_encoding, unknown_encoding):
 
 def ProcessFilesInDir(job, e, file_func):
     if DEBUG==1:
-        print( f"???? e={e}" )
+        print( f"DEBUG: ProcessFilesInDir: {e.FullPathOnFS()}")
-        # print( f"DEBUG: ProcessFilesInDir: {e.FullPathOnFS()}")
     if e.type.name != 'Directory':
         file_func(job, e)
     else:
@@ -1324,7 +1318,7 @@ def JobDeleteFiles(job):
         if 'eid-' in jex.name:
             del_me=session.query(Entry).join(File).filter(Entry.id==jex.value).first()
             MoveFileToRecycleBin(job,del_me)
-    now=datetime.now(pytz.utc)
+    ynw=datetime.now(pytz.utc)
     next_job=Job(start_time=now, last_update=now, name="checkdups", state="New", wait_for=None, pa_job_state="New", current_file_num=0 )
     session.add(next_job)
     MessageToFE( job.id, "success", "Completed (delete of selected files)" )
@@ -1365,6 +1359,10 @@ def InitialValidationChecks():
             break
     if not rbp_exists:
         AddLogForJob(job, "ERROR: The bin path in settings does not exist - Please fix now");
+    else:
+        bin_path=session.query(Path).join(PathType).filter(PathType.name=='Bin').first()
+        if not bin_path:
+            ProcessRecycleBinDir(job)
     sp_exists=0
     paths = settings.storage_path.split("#")
     for path in paths:
@@ -1389,10 +1387,8 @@ def InitialValidationChecks():
     FinishJob(job,"Finished Initial Validation Checks")
     return
 
-#### CAM: New FACES/AI code
-
 def AddFaceToFile( face_data, file_eid ):
-    face = Face( face=face_data )
+    face = Face( face=face_data.tobytes() )
     session.add(face)
     session.commit()
     ffl = FaceFileLink( face_id=face.id, file_eid=file_eid )
@@ -1412,46 +1408,50 @@ def MatchRefimgToFace( refimg_id, face_id ):
     return
 
 def UnmatchedFacesForFile( eid ):
-    rows = session.execute( f"select f.id, ffl.file_eid, frl.refimg_id from face f left join face_refimg_link frl on f.id = frl.face_id join face_file_link ffl on f.id = ffl.face_id where ffl.file_eid = {eid} and frl.refimg_id is null" )
+    rows = session.execute( f"select f.* from face f left join face_refimg_link frl on f.id = frl.face_id join face_file_link ffl on f.id = ffl.face_id where ffl.file_eid = {eid} and frl.refimg_id is null" )
     return rows
 
-### CAM: something like this -- HAVE NOT TRIED THIS IT WILL FAIL###
+def ScanFileForPerson( job, e, person_id, force=False ):
-def ScanFileForPerson( e, person_id, force=False ):
+    AddLogForJob( job, f'INFO: Looking for person: {person_id} in file: {e.name}' )
     file_h = session.query(File).get( e.id )
     # if we are forcing this, delete any old faces (this will also delete linked tables), and reset faces_created_on to None
     if force:
+        AddLogForJob( job, f'INFO: force is true, so deleting old face information for {e.name}' )
         DelFacesForFile( e.id )
-        file_h.faces_create_on = None
+        file_h.faces_created_on = 0
 
     # optimise: dont rescan if we already have faces (we are just going to try
     # to match (maybe?) a refimg
-    if not file_h.faces_created_on:
+    if file_h.faces_created_on == 0:
-        print("------------- CAM -----------:\n")
+        if DEBUG:
+            AddLogForJob( job, f"DEBUG: {e.name} is missing unknown faces, generating them" )
         im = face_recognition.load_image_file(e.FullPathOnFS())
-        print(im)
         face_locations = face_recognition.face_locations(im)
-        print(f"FACE LOCATIONS: {face_locations}")
         unknown_encodings = face_recognition.face_encodings(im, known_face_locations=face_locations)
-        print("AAAAAAAAAAAAAAAA " + str(len(unknown_encodings)))
         for face in unknown_encodings:
-            new_face = Face( face_data = face )
+            AddFaceToFile( face, e.id )
-            session.add(new_face)
+        file_h.faces_created_on = time.time()
-            session.commit()
+    session.commit()
-            AddFaceToFile( new_face.id, e.id )
-        now=datetime.now(pytz.utc)
-        file_h.face_created_on = now
 
     ## now look for person
     refimgs = session.query(Refimg).join(PersonRefimgLink).filter(PersonRefimgLink.person_id==person_id).all()
     uf = UnmatchedFacesForFile( e.id )
+    if DEBUG and not uf:
+        AddLogForJob( job, "DEBUG: {e.name} all faces already matched - finished" )
+        
     for face in uf:
         for r in refimgs:
-            match = compareAI(r, uf)
+            unknown_face_data = numpy.frombuffer(face.face, dtype=numpy.float64)
-            if match:
+            refimg_face_data = numpy.frombuffer(r.encodings, dtype=numpy.float64)
-                print(f'AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA WE MATCHED: {r}, {uf}')
+            match = compareAI(refimg_face_data, unknown_face_data)
+            if match[0]:
+                AddLogForJob(job, f'WE MATCHED: {r.fname} with file: {e.name} ')
                 MatchRefimgToFace( r.id, face.id )
+                # no need to keep looking for this face, we found it, go to next unknown face
+                break
     return
 
+
 if __name__ == "__main__":
     print("INFO: PA job manager starting - listening on {}:{}".format( PA_JOB_MANAGER_HOST, PA_JOB_MANAGER_PORT) )