model_used is now per file, not per face, implemented split of default_model to default_refimg_model and default_scan_model in settings, and default_refimg_model actualy works when creating refimgs in person.py. The model_used in face_file_link is based on default settings model and will scan with cnn if chosen and store that in DB as needed. Need viewer to allow changing per file / not just default for future scans

TODO

@@ -1,9 +1,5 @@
 ## GENERAL
 
-    * allow for and implement: default_refimg_model and default_scan_model
-        - cnn for refimgs should be defaul, for scan use hog
-        - research upsample val...
-
     * viewer needs to allow toggle to scan_model (and prob. right-click on file... AI (with CNN) AI (with hog)
         - I think go to html5 toggles for: face, distance (only shows if you toggle face on), drop-down for model (allow change to cnn and reprocess)
         - show matching face distance in viewer

pa_job_manager.py

@@ -190,11 +190,12 @@ class Settings(Base):
     import_path = Column(String)
     storage_path = Column(String)
     recycle_bin_path = Column(String)
-    default_model = Column(Integer,ForeignKey('ai_model.id'), unique=True, nullable=False)
+    default_refimg_model = Column(Integer,ForeignKey('ai_model.id'), unique=True, nullable=False)
+    default_scan_model = Column(Integer,ForeignKey('ai_model.id'), unique=True, nullable=False)
     default_threshold = Column(Integer)
 
     def __repr__(self):
-        return f"<id: {self.id}, import_path: {self.import_path}, recycle_bin_path: {self.recycle_bin_path}, default_model: {self.default_model}, default_threshold: {self.default_threshold}>"
+        return f"<id: {self.id}, import_path: {self.import_path}, recycle_bin_path: {self.recycle_bin_path}, default_refimg_model: {self.default_refimg_model}, default_scan_model: {self.default_scan_model}, default_threshold: {self.default_threshold}>"
         
 class PersonRefimgLink(Base):
     __tablename__ = "person_refimg_link"
@@ -225,6 +226,7 @@ class Refimg(Base):
     orig_w = Column(Integer)
     orig_h = Column(Integer)
     face_locn = Column(String)
+    model_used = Column(Integer, ForeignKey("ai_model.id") )
 
     def __repr__(self):
         return f"<id: {self.id}, fname: {self.fname}, created_on: {self.created_on}>"
@@ -259,7 +261,6 @@ class FaceRefimgLink(Base):
     __tablename__ = "face_refimg_link"
     face_id = Column(Integer, ForeignKey("face.id"), primary_key=True )
     refimg_id = Column(Integer, ForeignKey("refimg.id"), primary_key=True )
-    model_used = Column(Integer, ForeignKey("ai_model.id") )
     face_distance = Column(Integer)
 
     def __repr__(self):
@@ -981,6 +982,10 @@ def JobRunAIOn(job):
     else:
         job.refimgs=session.query(Refimg).join(PersonRefimgLink).join(Person).filter(Person.tag==which_person).all()
 
+    if not job.refimgs:
+        FinishJob(job, "Failed Processesing AI - the person(s) you chose has no reference images!", "Failed" )
+        return
+
     # start by working out how many images in this selection we will need face match on 
     job.num_files = 0
     for jex in job.extra:
@@ -1060,25 +1065,6 @@ def GenHashAndThumb(job, e):
     e.file_details.last_hash_date = time.time()
     return
 
-def lookForPersonInImage(job, person, unknown_encoding, e):
-    FinishJob( job, "THIS CODE HAS BEEN REMOVED, need to use new Face* tables, and rethink", "Failed" )
-    return
-
-
-def generateUnknownEncodings(im):
-    unknown_image = numpy.array(im)
-    face_locations = face_recognition.face_locations(unknown_image)
-    if not face_locations:
-        return None
-    unknown_encodings = face_recognition.face_encodings(unknown_image, known_face_locations=face_locations)
-    return unknown_encodings
-
-
-def compareAI(known_encoding, unknown_encoding):
-    results = face_recognition.compare_faces([known_encoding], unknown_encoding, tolerance=0.55)
-    return results
-
-
 def ProcessFilesInDir(job, e, file_func, count_dirs):
     if DEBUG==1:
         print( f"DEBUG: ProcessFilesInDir: {e.FullPathOnFS()}")
@@ -1353,11 +1339,11 @@ def InitialValidationChecks():
     FinishJob(job,"Finished Initial Validation Checks")
     return
 
-def AddFaceToFile( locn_data, face_data, file_eid ):
+def AddFaceToFile( locn_data, face_data, file_eid, model ):
     face = Face( face=face_data.tobytes(), locn=json.dumps(locn_data) )
     session.add(face)
     session.commit()
-    ffl = FaceFileLink( face_id=face.id, file_eid=file_eid )
+    ffl = FaceFileLink( face_id=face.id, file_eid=file_eid, model_used=model )
     session.add(ffl)
     session.commit()
     return face
@@ -1367,10 +1353,10 @@ def DelFacesForFile( eid ):
     session.commit()
     return
 
-def MatchRefimgToFace( refimg_id, face_id, model, face_dist ):
+def MatchRefimgToFace( refimg_id, face_id, face_dist ):
     # remove any match to this face from previous attempts, and 'replace' with new one
     session.query(FaceRefimgLink).filter(FaceRefimgLink.face_id==face_id).delete()
-    rfl = FaceRefimgLink( refimg_id = refimg_id, face_id = face_id, model_used=model, face_distance=face_dist )
+    rfl = FaceRefimgLink( refimg_id = refimg_id, face_id = face_id, face_distance=face_dist )
     session.add(rfl)
     session.commit()
     return
@@ -1398,24 +1384,24 @@ def ScanFileForPerson( job, e, force=False ):
         DelFacesForFile( e.id )
         file_h.faces_created_on = 0
 
+    # get default_scan_model from settings (test this)
+    settings = session.query(Settings).first()
+    model=settings.default_scan_model
+    threshold = settings.default_threshold
+
     # optimise: dont rescan if we already have faces 
     if file_h.faces_created_on == 0:
         if DEBUG:
             AddLogForJob( job, f"DEBUG: {e.name} is missing unknown faces, generating them" )
         im = face_recognition.load_image_file(e.FullPathOnFS())
-        # TODO: use setting to use model
+        model=AIModel.query.get(model)
-        face_locations = face_recognition.face_locations(im)
+        face_locations = face_recognition.face_locations(im, model=model.name)
         unknown_encodings = face_recognition.face_encodings(im, known_face_locations=face_locations)
         for locn, face in zip( face_locations, unknown_encodings ):
-            AddFaceToFile( locn, face, e.id )
+            AddFaceToFile( locn, face, e.id, model )
         file_h.faces_created_on = time.time()
     session.commit()
 
-    # get default_model from settings (test this)
-    settings = session.query(Settings).first()
-    model=settings.default_model
-    threshold = settings.default_threshold
-
     faces = session.query(Face).join(FaceFileLink).filter(FaceFileLink.file_eid==e.id).all()
     # if there are no faces for this file, then dont go any futher
     if not faces:
@@ -1437,7 +1423,7 @@ def ScanFileForPerson( job, e, force=False ):
     for face in faces:
         who, fd = BestFaceMatch(dist, face.id, threshold )
         if who != None:
-            MatchRefimgToFace( who, face.id, model, fd )
+            MatchRefimgToFace( who, face.id, fd )
             AddLogForJob(job, f'WE MATCHED: {name[who]} with file: {e.name} - face distance of {fd}')
             del( dist[who] )
     return

person.py

@@ -2,6 +2,7 @@ from wtforms import SubmitField, StringField, HiddenField, validators, Form
 from flask_wtf import FlaskForm
 from flask import request, render_template, redirect, url_for
 from main import db, app, ma
+from settings import Settings, AIModel
 from sqlalchemy import Sequence
 from sqlalchemy.exc import SQLAlchemyError
 from status import st, Status
@@ -27,6 +28,7 @@ class Refimg(db.Model):
     face_locn = db.Column(db.String)
     thumbnail = db.Column(db.String, unique=True, nullable=False)
     created_on = db.Column(db.Float)
+    model_used = db.Column(db.Integer, db.ForeignKey("ai_model.id") )
     person = db.relationship( 'Person', secondary="person_refimg_link", uselist=False, viewonly=True )
 
     def __repr__(self):
@@ -123,7 +125,7 @@ def person(id):
                 # do the linkage tables by hand
                 db.session.execute( f"delete from face_refimg_link frl where refimg_id in ( select refimg_id from person_refimg_link where person_id = {id} )" )
                 db.session.execute( f"delete from person_refimg_link where person_id = {id}" )
-                person = Person.query.filter(Person.id==id).delete()
+                Person.query.filter(Person.id==id).delete()
                 db.session.commit()
                 return redirect( f'/persons' )
             elif request.form and form.validate():
@@ -132,9 +134,11 @@ def person(id):
                     if "ref-img-id-{}".format(ref_img.id) in request.form:
                         new_refs.append(ref_img)
                 if new_refs != person.refimg:
-                    deld = list(set(person.refimg) - set(new_refs))
+                    deld = list(set(person.refimg) - set(new_refs));
-                    st.SetMessage( f"Successfully Updated Person: removed reference image {deld[0].fname}" )
+                    print(deld)
                     person.refimg = new_refs
+                    Refimg.query.filter(Refimg.id==deld[0].id).delete()
+                    st.SetMessage( f"Successfully Updated Person: removed reference image {deld[0].fname}" )
                 else:
                     st.SetMessage("Successfully Updated Person: (From: {}, {}, {})".format(person.tag, person.firstname, person.surname) )
                     person.tag = request.form['tag']
@@ -176,8 +180,11 @@ def add_refimg():
         fname = f"/tmp/{fname}"
         f.save( fname )
         refimg.thumbnail, refimg.orig_w, refimg.orig_h = GenThumb( fname )
-        refimg.face, face_locn = GenFace( fname )
+        settings = Settings.query.first()
+        model=AIModel.query.get(settings.default_refimg_model)
+        refimg.face, face_locn = GenFace( fname, model=model.name )
         refimg.face_locn = json.dumps(face_locn)
+        refimg.model_used = settings.default_refimg_model
         os.remove(fname)
         person.refimg.append(refimg)
         db.session.add(person)

settings.py

@@ -29,11 +29,12 @@ class Settings(db.Model):
     import_path = db.Column(db.String)
     storage_path = db.Column(db.String)
     recycle_bin_path = db.Column(db.String)
-    default_model = db.Column(db.Integer,db.ForeignKey('ai_model.id'), unique=True, nullable=False)
+    default_refimg_model = db.Column(db.Integer,db.ForeignKey('ai_model.id'), unique=True, nullable=False)
+    default_scan_model = db.Column(db.Integer,db.ForeignKey('ai_model.id'), unique=True, nullable=False)
     default_threshold = db.Column(db.Integer)
 
     def __repr__(self):
-        return f"<id: {self.id}, import_path: {self.import_path}, storage_path: {self.storage_path}, recycle_bin_path: {self.recycle_bin_path}, default_model: {self.default_model}, default_threshold: {self.default_threshold}>"
+        return f"<id: {self.id}, import_path: {self.import_path}, storage_path: {self.storage_path}, recycle_bin_path: {self.recycle_bin_path}, default_refimg_model: {self.default_refimg_model}, default_scan_model: {self.default_scan_model}, default_threshold: {self.default_threshold}>"
 
 ################################################################################
 # Helper class that inherits a .dump() method to turn class Settings into json / useful in jinja2
@@ -54,7 +55,8 @@ class SettingsForm(FlaskForm):
     import_path = StringField('Path(s) to import from:', [validators.DataRequired()])
     storage_path = StringField('Path to store sorted images to:', [validators.DataRequired()])
     recycle_bin_path = StringField('Path to temporarily store deleted images in:', [validators.DataRequired()])
-    default_model = SelectField( 'default_model',  choices=[(c.id, c.name) for c in AIModel.query.order_by('id')] )
+    default_refimg_model = SelectField( 'default_refimg_model',  choices=[(c.id, c.name) for c in AIModel.query.order_by('id')] )
+    default_scan_model = SelectField( 'default_scan_model',  choices=[(c.id, c.name) for c in AIModel.query.order_by('id')] )
     default_threshold = StringField('Face Distance threshold (below is a match):', [validators.DataRequired()])
     submit = SubmitField('Save' )
 
@@ -78,7 +80,8 @@ def settings():
                 s.import_path = request.form['import_path']
                 s.storage_path = request.form['storage_path']
                 s.recycle_bin_path = request.form['recycle_bin_path']
-                s.default_model = request.form['default_model']
+                s.default_refimg_model = request.form['default_refimg_model']
+                s.default_scan_model = request.form['default_scan_model']
                 s.default_threshold = request.form['default_threshold']
             db.session.commit()
             return redirect( '/settings' )

shared.py

@@ -96,9 +96,10 @@ def GenThumb(fname):
         print( f"GenThumb failed: {e}")
         return None, None, None
 
-def GenFace(fname):
+def GenFace(fname, model):
     img = face_recognition.load_image_file(fname)
-    location = face_recognition.face_locations(img)
+    # TODO: change face_locations call basedon model
+    location = face_recognition.face_locations(img, model=model)
     encodings = face_recognition.face_encodings(img, known_face_locations=location)
     if len(encodings):
         return encodings[0].tobytes(), location

tables.sql

@@ -1,15 +1,16 @@
 alter database PA set timezone to 'Australia/Victoria'; 
 
 -- these are hard-coded at present, not sure I can reflexively find models from API?
-create table AI_MODEL ( ID integer, NAME varchar(24), constraint PK_AI_MODEL primary key(ID) );
+create table AI_MODEL ( ID integer, NAME varchar(24), DESCRIPTION varchar(80), constraint PK_AI_MODEL primary key(ID) );
-insert into AI_MODEL values ( 1, 'hog' );
+insert into AI_MODEL values ( 1, 'hog', 'normal' );
-insert into AI_MODEL values ( 2, 'cnn' );
+insert into AI_MODEL values ( 2, 'cnn', 'slower but more accurate' );
 
 create table SETTINGS( 
     ID integer, IMPORT_PATH varchar, STORAGE_PATH varchar, RECYCLE_BIN_PATH varchar, 
-    DEFAULT_MODEL integer, DEFAULT_THRESHOLD float,
+    DEFAULT_REFIMG_MODEL integer, DEFAULT_SCAN_MODEL integer, DEFAULT_THRESHOLD float,
     constraint PK_SETTINGS_ID primary key(ID),
-    constraint FK_DEFAULT_MODEL foreign key (DEFAULT_MODEL) references AI_MODEL(ID) );
+    constraint FK_DEFAULT_REFIMG_MODEL foreign key (DEFAULT_REFIMG_MODEL) references AI_MODEL(ID),
+    constraint FK_DEFAULT_SCAN_MODEL foreign key (DEFAULT_SCAN_MODEL) references AI_MODEL(ID) );
 
 create table PA_USER( ID integer, dn varchar, constraint PK_PA_USER_ID primary key(ID) );
 
@@ -49,8 +50,9 @@ create table ENTRY_DIR_LINK ( entry_id integer, dir_eid integer,
 create table PERSON ( ID integer, TAG varchar(48), FIRSTNAME varchar(48), SURNAME varchar(48),
     constraint PK_PERSON_ID primary key(ID) );
 
-create table REFIMG ( ID integer, FNAME varchar(128), FACE bytea, ORIG_W integer, ORIG_H integer, FACE_LOCN varchar(32), CREATED_ON float, THUMBNAIL varchar, 
+create table REFIMG ( ID integer, FNAME varchar(128), FACE bytea, ORIG_W integer, ORIG_H integer, FACE_LOCN varchar(32), CREATED_ON float, THUMBNAIL varchar, MODEL_USED integer, 
-    constraint PK_REFIMG_ID primary key(ID) );
+    constraint PK_REFIMG_ID primary key(ID),
+    constraint FK_REFIMG_MODEL_USED foreign key (MODEL_USED) references AI_MODEL(ID) );
 
 create table FACE( ID integer, FACE bytea, LOCN varchar(32), constraint PK_FACE_ID primary key(ID) );
 
@@ -60,11 +62,10 @@ create table FACE_FILE_LINK( FACE_ID integer, FILE_EID integer, MODEL_USED integ
     constraint FK_FFL_FILE_EID foreign key (FILE_EID) references FILE(EID),
     constraint FK_FFL_MODEL_USED foreign key (MODEL_USED) references AI_MODEL(ID) );
 
-create table FACE_REFIMG_LINK( FACE_ID integer, REFIMG_ID integer, MODEL_USED integer, FACE_DISTANCE integer,
+create table FACE_REFIMG_LINK( FACE_ID integer, REFIMG_ID integer, FACE_DISTANCE integer,
     constraint PK_FRL_FACE_ID_REFIMG_ID primary key(FACE_ID, REFIMG_ID), 
     constraint FK_FRL_FACE_ID foreign key (FACE_ID) references FACE(ID) on delete cascade,
-    constraint FK_FRL_REFIMG_ID foreign key (REFIMG_ID) references REFIMG(ID),
+    constraint FK_FRL_REFIMG_ID foreign key (REFIMG_ID) references REFIMG(ID) );
-    constraint FK_FRL_MODEL_USED foreign key (MODEL_USED) references AI_MODEL(ID) );
 
 create table PERSON_REFIMG_LINK ( PERSON_ID integer, REFIMG_ID integer,
     constraint PK_PRL primary key(PERSON_ID, REFIMG_ID), 
@@ -120,6 +121,6 @@ insert into PERSON values ( (select nextval('PERSON_ID_SEQ')), 'mum', 'Mandy', '
 insert into PERSON values ( (select nextval('PERSON_ID_SEQ')), 'cam', 'Cameron', 'De Paoli' );
 insert into PERSON values ( (select nextval('PERSON_ID_SEQ')), 'mich', 'Michelle', 'De Paoli' );
 -- DEV:
-insert into SETTINGS ( id, import_path, storage_path, recycle_bin_path, default_model, default_threshold ) values ( (select nextval('SETTINGS_ID_SEQ')), '/home/ddp/src/photoassistant/images_to_process/#c:/Users/cam/Desktop/code/python/photoassistant/photos/#/home/ddp/src/photoassistant/new_img_dir/', '/home/ddp/src/photoassistant/storage/#c:/Users/cam/Desktop/code/python/photoassistant/storage/', '/home/ddp/src/photoassistant/.pa_bin/#c:/Users/cam/Desktop/code/python/photoassistant/.pa_bin/', 1, '0.55' );
+insert into SETTINGS ( id, import_path, storage_path, recycle_bin_path, default_refimg_model, default_scan_model, default_threshold ) values ( (select nextval('SETTINGS_ID_SEQ')), '/home/ddp/src/photoassistant/images_to_process/#c:/Users/cam/Desktop/code/python/photoassistant/photos/#/home/ddp/src/photoassistant/new_img_dir/', '/home/ddp/src/photoassistant/storage/#c:/Users/cam/Desktop/code/python/photoassistant/storage/', '/home/ddp/src/photoassistant/.pa_bin/#c:/Users/cam/Desktop/code/python/photoassistant/.pa_bin/', 2, 1, '0.55' );
 -- PROD:
---insert into SETTINGS ( id, import_path, storage_path, recycle_bin_path, default_model, default_threshold ) values ( (select nextval('SETTINGS_ID_SEQ')), '/export/docker/storage/Camera_uploads/', '/export/docker/storage/photos/', '/export/docker/storage/.pa_bin/', 1, '0.55' );
+--insert into SETTINGS ( id, import_path, storage_path, recycle_bin_path, default_refimg_model, default_scan_model, default_threshold ) values ( (select nextval('SETTINGS_ID_SEQ')), '/export/docker/storage/Camera_uploads/', '/export/docker/storage/photos/', '/export/docker/storage/.pa_bin/', 2, 1, '0.55' );

templates/person.html

@@ -83,6 +83,9 @@
                     </figure>
                 </div id="/RI*">
             {% endfor %}
+            <div id="throb" style="display:none" class="col-1 px-0 {{offset}}">
+                <img height="64px" src="{{url_for('static', filename='throbber.gif')}}"></img>
+            </div>
         </div class="row col-12">
         <div class="row col-12">
         <br>
@@ -100,7 +103,7 @@
             <div class="row col-12">
                 <label class="btn btn-success offset-3 col-2">
                     Add reference image
-                    <input name="refimg_file" type="file" onChange="$('#new_ri').submit()" style="display:none;" id="new_file_chooser">
+                    <input name="refimg_file" type="file" onChange="$('#throb').attr('style','show'); $('#new_ri').submit()" style="display:none;" id="new_file_chooser">
                 </label>
             </div class="row col-12">
         </form>