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