diff --git a/BUGs b/BUGs
index d10e71a..52e4a62 100644
--- a/BUGs
+++ b/BUGs
@@ -1,4 +1,3 @@
 ### Next: 19
 BUG-16: now we dont do dir level optimising for genfiledetails, need to stat the file / check dates that way to optimise
 BUG-17: I think it won't handle me deleting files after scan
-BUG-18: ProcessAI not counting files properly
diff --git a/pa_job_manager.py b/pa_job_manager.py
index fc6d66c..93fc4bf 100644
--- a/pa_job_manager.py
+++ b/pa_job_manager.py
@@ -486,6 +486,11 @@ def JobProcessAI(job):
     path = SymlinkName(path, '/')
     d=session.query(Dir).filter(Dir.path_prefix==path).first()
     job.num_files=d.num_files
+
+    people = session.query(Person).all()
+    for person in people:
+        generateKnownEncodings(person)
+    
     for e in FilesInDir( path ):
         ProcessFilesInDir(job, e, ProcessAI)
     FinishJob(job, "Finished Processesing AI")
@@ -508,13 +513,9 @@ def GenHashAndThumb(job, e):
 def ProcessAI(job, e):
     if e.type.name != 'Image':
         job.current_file_num+=1
+        print("DDP: ProcessAI: adding 1 to current_file_num as we have a non-image file")
         return
 
-    people = session.query(Person).all()
-    for person in people:
-        generateKnownEncodings(person)
-    
-
     file = e.in_dir[0].path_prefix + '/' + e.name
     stat = os.stat(file)
     # only find faces if we have not already OR file is newer than when we found faces before
@@ -530,10 +531,12 @@ def ProcessAI(job, e):
             e.file_details[0].faces = flat_faces.tobytes()
         else:
             e.file_details[0].faces = None
+            job.current_file_num+=1
             return
     else:
         if not e.file_details[0].faces:
             print("OPTIM: This image has no faces, skip it")
+            job.current_file_num+=1
             return
         recover=numpy.frombuffer(e.file_details[0].faces,dtype=numpy.float64)      
         real_recover=numpy.reshape(recover,(-1,128))      
@@ -541,6 +544,7 @@ def ProcessAI(job, e):
         for el in real_recover:
             l.append(numpy.array(el))
         faces = l
+    people = session.query(Person).all()
     for unknown_encoding in faces:
         for person in people:
             lookForPersonInImage(job, person, unknown_encoding, e)