def async_detect(self, path):
"""Async detection."""
self.log.log('Request: Detecting {}'.format(path))
self.result.SetLabelText('Detecting ...')
self.btn.Disable()
self.face_list.Clear()
self.face_list.Refresh()
self.rsizer.Layout()
self.vhsizer.Layout()
try:
attributes = (
'age,gender,headPose,smile,facialHair,glasses,emotion,hair,'
'makeup,occlusion,accessories,blur,exposure,noise')
res = util.CF.face.detect(path, False, False, attributes)
faces = [model.Face(face, path) for face in res]
self.face_list.SetItems(faces)
util.draw_bitmap_rectangle(self.bitmap, faces)
log_text = 'Response: Success. Detected {} face(s) in {}'.format(
len(res), path)
self.log.log(log_text)
text = '{} face(s) has been detected.'.format(len(res))
self.result.SetLabelText(text)
except util.CF.CognitiveFaceException as exp:
self.log.log('Response: {}. {}'.format(exp.code, exp.msg))
self.btn.Enable()
self.rsizer.Layout()
self.vhsizer.Layout()
def async_detect(self, path):
"""Async detection."""
self.log.log('Request: Detecting {}'.format(path))
self.result.SetLabelText('Detecting ...')
self.btn.Disable()
self.face_list.Clear()
self.face_list.Refresh()
self.rsizer.Layout()
self.vhsizer.Layout()
try:
attributes = (
'age,gender,headPose,smile,facialHair,glasses,emotion,hair,'
'makeup,occlusion,accessories,blur,exposure,noise')
res = util.CF.face.detect(path, False, False, attributes)
faces = [model.Face(face, path) for face in res]
self.face_list.SetItems(faces)
util.draw_bitmap_rectangle(self.bitmap, faces)
log_text = 'Response: Success. Detected {} face(s) in {}'.format(
len(res), path)
self.log.log(log_text)
text = '{} face(s) has been detected.'.format(len(res))
self.result.SetLabelText(text)
except util.CF.CognitiveFaceException as exp:
self.log.log('Response: {}. {}'.format(exp.code, exp.msg))
self.btn.Enable()
self.rsizer.Layout()
self.vhsizer.Layout()
def OnChooseImage(self, evt, bitmap, face_id):
"""Choose Image"""
dlg = wx.FileDialog(self, wildcard=util.IMAGE_WILDCARD)
if dlg.ShowModal() != wx.ID_OK:
return
path = dlg.GetPath()
self.log.log('Request: Detecting {}'.format(path))
res = util.CF.face.detect(path)
faces = [model.Face(face, path) for face in res]
self.log.log('Response: Success. Detected {} face(s) in {}'.format(
len(res), path))
if len(faces) > 1:
text = (
'Verification accepts two faces as input, please pick images'
'with only one detectable face in it.'
)
title = 'Warning'
style = wx.OK | wx.ICON_WARNING
wx.MessageBox(text, title, style)
return
bitmap.set_path(path)
util.draw_bitmap_rectangle(bitmap, faces)
self.face_ids[face_id] = faces[0].id
self.check_btn_verify()
def OnChooseImage(self, evt, bitmap, face_id):
"""Choose Image"""
dlg = wx.FileDialog(self, wildcard=util.IMAGE_WILDCARD)
if dlg.ShowModal() != wx.ID_OK:
return
path = dlg.GetPath()
self.log.log('Request: Detecting {}'.format(path))
res = util.CF.face.detect(path)
faces = [model.Face(face, path) for face in res]
self.log.log('Response: Success. Detected {} face(s) in {}'.format(
len(res), path))
if len(faces) > 1:
text = (
'Verification accepts two faces as input, please pick images '
'with only one detectable face in it.')
title = 'Warning'
style = wx.OK | wx.ICON_WARNING
wx.MessageBox(text, title, style)
return
bitmap.set_path(path)
util.draw_bitmap_rectangle(bitmap, faces)
self.face_ids[face_id] = faces[0].id
self.check_btn_verify()
def async_detect(self, path):
"""Async detection."""
self.log.log('Request: Detecting {}'.format(path))
self.result.SetLabelText('Detecting ...')
self.btn.Disable()
self.rsizer.Layout()
self.vhsizer.Layout()
try:
# Use the ML algo on input image, give background (BG) as a class
res = util.DD.detect.detect(path,
self.detection_init.model,
class_names=['BG', 'object_interest'])
# Read in image
self.bitmap.set_path(res['image_file'])
# Set the image on the StaticBitmap object for display
util.draw_bitmap_rectangle(self.bitmap)
log_text = 'Response: Success. Detected {} object location(s)'.format(
res['num_objects'], path)
self.log.log(log_text)
text = '{} object location(s) detected.'.format(res['num_objects'])
self.result.SetLabelText(text)
except Exception as exp:
self.log.log('Response: {}'.format(exp))
self.btn.Enable()
self.rsizer.Layout()
self.vhsizer.Layout()
def OnChooseImage(self, evt):
"""Choose Image."""
util.CF.util.wait_for_large_face_list_training(self.large_face_list_id)
self.log.log(
'Response: Success. List "{0}" training process is Succeeded'.
format(self.large_face_list_id))
dlg = wx.FileDialog(self, wildcard=util.IMAGE_WILDCARD)
if dlg.ShowModal() != wx.ID_OK:
return
path = dlg.GetPath()
self.bitmap.set_path(path)
self.log.log('Detecting faces in {}'.format(path))
self.faces.clear()
res = util.CF.face.detect(path)
for entry in res:
face = model.Face(entry, path)
self.faces[face.id] = face
util.draw_bitmap_rectangle(self.bitmap, self.faces.values())
self.log.log('Success. Detected {} face(s) in {}'.format(
len(self.faces), path))
res_tot = {
'matchPerson': {},
'matchFace': {},
}
for face_id in self.faces:
self.log.log(
('Request: Finding similar faces in Person Match Mode for '
'face {}').format(face_id))
for mode in ('matchPerson', 'matchFace'):
res_tot[mode][face_id] = []
res = util.CF.face.find_similars(
face_id,
large_face_list_id=self.large_face_list_id,
mode=mode)
self.log.log(
'Response: Found {} similar faces for face {} in {} mode'.
format(len(res), face_id, mode))
for entry in res:
persisted_id = entry['persistedFaceId']
confidence = entry['confidence']
res_tot[mode][face_id].append(
(self.persisted_faces[persisted_id], confidence))
self.result.set_data(self.faces, res_tot)
self.panel.SetupScrolling(scroll_x=False)
def OnChooseImage(self, evt):
"""Choose Image."""
util.CF.util.wait_for_large_face_list_training(self.large_face_list_id)
self.log.log(
'Response: Success. List "{0}" training process is Succeeded'.
format(self.large_face_list_id))
dlg = wx.FileDialog(self, wildcard=util.IMAGE_WILDCARD)
if dlg.ShowModal() != wx.ID_OK:
return
path = dlg.GetPath()
self.bitmap.set_path(path)
self.log.log('Detecting faces in {}'.format(path))
self.faces.clear()
res = util.CF.face.detect(path)
for entry in res:
face = model.Face(entry, path)
self.faces[face.id] = face
util.draw_bitmap_rectangle(self.bitmap, self.faces.values())
self.log.log(
'Success. Detected {} face(s) in {}'.format(len(self.faces), path))
res_tot = {
'matchPerson': {},
'matchFace': {},
}
for face_id in self.faces:
self.log.log((
'Request: Finding similar faces in Person Match Mode for '
'face {}').format(face_id))
for mode in ('matchPerson', 'matchFace'):
res_tot[mode][face_id] = []
res = util.CF.face.find_similars(
face_id,
large_face_list_id=self.large_face_list_id,
mode=mode)
self.log.log(
'Response: Found {} similar faces for face {} in {} mode'.
format(len(res), face_id, mode))
for entry in res:
persisted_id = entry['persistedFaceId']
confidence = entry['confidence']
res_tot[mode][face_id].append(
(self.persisted_faces[persisted_id], confidence))
self.result.set_data(self.faces, res_tot)
self.panel.SetupScrolling(scroll_x=False)
def OnChooseImage(self, evt):
"""Choose Image."""
util.CF.util.wait_for_large_person_group_training(
self.large_person_group_id)
self.log.log(
'Response: Success. Group "{0}" training process is Succeeded'.
format(self.large_person_group_id))
dlg = wx.FileDialog(self, wildcard=util.IMAGE_WILDCARD)
if dlg.ShowModal() != wx.ID_OK:
return
path = dlg.GetPath()
self.bitmap.set_path(path)
self.log.log('Detecting faces in {}'.format(path))
self.faces.clear()
del self.face_ids[:]
res = util.CF.face.detect(path)
for entry in res:
face = model.Face(entry, path)
self.faces[face.id] = face
self.face_ids.append(face.id)
self.log.log('Request: Identifying {0} face(s) in group "{1}"'.format(
len(self.faces), self.large_person_group_id))
res = util.CF.face.identify(
self.face_ids,
large_person_group_id=self.large_person_group_id)
for entry in res:
face_id = entry['faceId']
if entry['candidates']:
person_id = entry['candidates'][0]['personId']
self.faces[face_id].set_name(self.person_id_names[person_id])
else:
self.faces[face_id].set_name('Unknown')
util.draw_bitmap_rectangle(self.bitmap, self.faces.values())
log_text = 'Response: Success.'
for face_id in self.faces:
log_text += ' Face {0} is identified as {1}.'.format(
face_id, self.faces[face_id].name)
self.log.log(log_text)
def OnChooseImage(self, evt):
"""Choose Image."""
util.CF.util.wait_for_large_person_group_training(
self.large_person_group_id)
self.log.log(
'Response: Success. Group "{0}" training process is Succeeded'.
format(self.large_person_group_id))
dlg = wx.FileDialog(self, wildcard=util.IMAGE_WILDCARD)
if dlg.ShowModal() != wx.ID_OK:
return
path = dlg.GetPath()
self.bitmap.set_path(path)
self.log.log('Detecting faces in {}'.format(path))
self.faces.clear()
del self.face_ids[:]
res = util.CF.face.detect(path)
for entry in res:
face = model.Face(entry, path)
self.faces[face.id] = face
self.face_ids.append(face.id)
self.log.log('Request: Identifying {0} face(s) in group "{1}"'.format(
len(self.faces), self.large_person_group_id))
res = util.CF.face.identify(
self.face_ids,
large_person_group_id=self.large_person_group_id)
for entry in res:
face_id = entry['faceId']
if entry['candidates']:
person_id = entry['candidates'][0]['personId']
self.faces[face_id].set_name(self.person_id_names[person_id])
else:
self.faces[face_id].set_name('Unknown')
util.draw_bitmap_rectangle(self.bitmap, self.faces.values())
log_text = 'Response: Success.'
for face_id in self.faces:
log_text += ' Face {0} is identified as {1}.'.format(
face_id, self.faces[face_id].name)
self.log.log(log_text)
def async_detect(self, path):
"""Async detection."""
self.log.log('Request: Detecting {}'.format(path))
self.result.SetLabelText('Detecting ...')
self.btn.Disable()
self.face_list.Clear()
self.face_list.Refresh()
self.rsizer.Layout()
self.vhsizer.Layout()
attributes = 'age,gender,headPose,smile,facialHair,glasses,emotion'
res = util.CF.face.detect(path, False, False, attributes)
faces = [model.Face(face, path) for face in res]
self.face_list.SetItems(faces)
util.draw_bitmap_rectangle(self.bitmap, faces)
log_text = 'Response: Success. Detected {} face(s) in {}'.format(
len(res), path)
self.log.log(log_text)
text = '{} face(s) has been detected.'.format(len(res))
self.result.SetLabelText(text)
self.btn.Enable()
self.rsizer.Layout()
self.vhsizer.Layout()
