def create_categorical_slice_session(dataset_name: str):
dataset = backend.get_dataset(dataset_name)
if dataset is None:
abort(400)
current_sessions = sessions.get_sessions(db.session, dataset)
label_session_count = len(current_sessions)
form = CreateCategoricalSliceSessionForm(meta={'csrf': False})
comparison_sessions = sessions.get_sessions(db.session, dataset, LabelSessionType.COMPARISON_SLICE)
for sess in comparison_sessions:
form.comparisons.choices.append((str(sess.id), sess.session_name))
if form.validate_on_submit():
if form.session_name.data in [se.session_name for se in current_sessions]:
form.session_name.errors.append('Session name already in use.')
else:
label_values = [v.strip() for v in form.label_values.data.split(',')]
from_session = sessions.get_session_by_id(db.session, int(form.comparisons.data))
slices = sampling.get_slices_from_session(from_session)
sessions.create_categorical_slice_session(db.session, form.session_name.data, form.prompt.data,
dataset, label_values, slices)
return redirect(url_for('dataset_overview', dataset_name=dataset.name))
return render_template('create_categorical_slice_session.html',
dataset=dataset,
label_session_count=label_session_count,
form=form)
def test_get_sessions_length(self):
dataset1 = backend.get_dataset('dataset1')
dataset2 = backend.get_dataset('dataset2')
sessions.create_categorical_image_session(db.session, 'session1',
'prompt', dataset1,
['l1', 'l2', 'l3'])
sessions.create_categorical_image_session(db.session, 'session2',
'prompt', dataset1,
['l1', 'l2', 'l3'])
sessions.create_categorical_image_session(db.session, 'session3',
'prompt', dataset1,
['l1', 'l2', 'l3'])
sessions.create_categorical_image_session(db.session, 'session4',
'prompt', dataset2,
['l1', 'l2', 'l3'])
dataset1_sessions = sessions.get_sessions(db.session, dataset1)
dataset1_sessions_count = len(dataset1_sessions)
dataset2_sessions = sessions.get_sessions(db.session, dataset2)
dataset2_sessions_count = len(dataset2_sessions)
self.assertEqual(dataset1_sessions_count, 3)
self.assertEqual(dataset2_sessions_count, 1)
def create_comparison_session(dataset_name: str):
dataset = backend.get_dataset(dataset_name)
if dataset is None:
abort(400)
current_sessions = sessions.get_sessions(db.session, dataset)
label_session_count = len(current_sessions)
images = backend.get_images(dataset)
total_image_count = len(images)
form = CreateComparisonSessionForm(meta={'csrf': False})
comparison_sessions = sessions.get_sessions(db.session, dataset, LabelSessionType.COMPARISON_SLICE)
for sess in comparison_sessions:
form.comparisons.choices.append((str(sess.id), sess.session_name))
form.image_count.validators = [
ComparisonNumberRange(min=1, max=total_image_count,
message='Must be between %(min)s and %(max)s (the dataset size).')
]
if form.validate_on_submit():
if form.session_name.data in [se.session_name for se in current_sessions]:
form.session_name.errors.append('Session name already in use.')
elif form.comparisons.data == 'create' and form.min_slice_percent.data >= form.max_slice_percent.data:
form.max_slice_percent.errors.append('Max must be greater than min.')
else:
slice_type = backend.SliceType[form.slice_type.data]
if form.comparisons.data == 'create':
slices = sampling.sample_slices(dataset, slice_type, form.image_count.data, form.slice_count.data,
form.min_slice_percent.data, form.max_slice_percent.data)
if form.comparison_count.data is None:
comparisons = sampling.all_comparisons(slices)
else:
comparisons = sampling.sample_comparisons(slices, form.comparison_count.data,
form.max_comparisons_per_slice.data)
else:
from_session = sessions.get_session_by_id(db.session, int(form.comparisons.data))
comparisons = sampling.get_comparisons_from_session(from_session)
label_values = [v.strip() for v in form.label_values.data.split(',')]
sessions.create_comparison_slice_session(db.session, form.session_name.data, form.prompt.data,
dataset, label_values, comparisons)
return redirect(url_for('dataset_overview', dataset_name=dataset.name))
return render_template('create_comparison_session.html',
dataset=dataset,
label_session_count=label_session_count,
total_image_count=total_image_count,
form=form)
def test_get_sessions_by_type_length(self):
dataset = backend.get_dataset('dataset1')
sessions.create_categorical_image_session(db.session, 'session1',
'prompt', dataset,
['l1', 'l2', 'l3'])
sessions.create_categorical_image_session(db.session, 'session2',
'prompt', dataset,
['l1', 'l2', 'l3'])
sessions.create_categorical_slice_session(db.session, 'session3',
'prompt', dataset,
['l1', 'l2', 'l3'], [])
sessions.create_categorical_slice_session(db.session, 'session4',
'prompt', dataset,
['l1', 'l2', 'l3'], [])
sessions.create_comparison_slice_session(db.session, 'session5',
'prompt', dataset,
['l1', 'l2'], [])
sessions.create_categorical_image_session(db.session, 'session6',
'prompt', dataset,
['l1', 'l2', 'l3'])
sessions.create_categorical_image_session(db.session, 'session7',
'prompt', dataset,
['l1', 'l2', 'l3'])
categorical_image_sessions = sessions.get_sessions(
db.session, dataset, LabelSessionType.CATEGORICAL_IMAGE)
categorical_image_session_count = len(categorical_image_sessions)
categorical_slice_sessions = sessions.get_sessions(
db.session, dataset, LabelSessionType.CATEGORICAL_SLICE)
categorical_slice_session_count = len(categorical_slice_sessions)
comparison_slice_sessions = sessions.get_sessions(
db.session, dataset, LabelSessionType.COMPARISON_SLICE)
comparison_slice_session_count = len(comparison_slice_sessions)
self.assertEqual(categorical_image_session_count, 4)
self.assertEqual(categorical_slice_session_count, 2)
self.assertEqual(comparison_slice_session_count, 1)
def create_sort_session(dataset_name: str):
dataset = backend.get_dataset(dataset_name)
if dataset is None:
abort(400)
current_sessions = sessions.get_sessions(db.session, dataset)
label_session_count = len(current_sessions)
images = backend.get_images(dataset)
total_image_count = len(images)
form = CreateSortSessionForm(meta={'csrf': False})
form.image_count.validators = [
NumberRange(min=1, max=total_image_count, message='Must be between %(min)s and %(max)s (the dataset size).')
]
for sess in sessions.get_sessions(db.session, dataset):
t = sess.session_type
if t in SLICE_SESSION_NAMES:
form.slices_from.choices.append((str(sess.id), sess.session_name))
if form.validate_on_submit():
if form.session_name.data in [se.session_name for se in current_sessions]:
form.session_name.errors.append('Session name already in use.')
elif form.min_slice_percent.data >= form.max_slice_percent.data:
form.max_slice_percent.errors.append('Max must be greater than min.')
else:
if form.slices_from.data == 'create':
slice_type = backend.SliceType[form.slice_type.data]
slices = sampling.sample_slices(dataset, slice_type, form.image_count.data, form.slice_count.data,
form.min_slice_percent.data, form.max_slice_percent.data)
else:
from_session = sessions.get_session_by_id(db.session, int(form.slices_from.data))
slices = sampling.get_slices_from_session(from_session)
sessions.create_sort_slice_session(db.session, form.session_name.data, form.prompt.data, dataset, slices)
return redirect(url_for('dataset_overview', dataset_name=dataset.name))
return render_template('create_sort_session.html',
dataset=dataset,
label_session_count=label_session_count,
total_image_count=total_image_count,
form=form)
def dataset_overview(dataset_name: str):
dataset = backend.get_dataset(dataset_name)
if dataset is None:
abort(404)
images = backend.get_images(dataset)
label_sessions = sessions.get_sessions(db.session, dataset)
sessions_by_type: Dict[LabelSessionType, List[LabelSession]] = {st: [] for st in LabelSessionType}
for sess in label_sessions:
sessions_by_type[LabelSessionType[sess.session_type]].append(sess)
return render_template('dataset_overview.html',
dataset=dataset,
images=images,
label_sessions=sessions_by_type)
def import_session(dataset_name: str):
dataset = backend.get_dataset(dataset_name)
if dataset is None:
abort(400)
form = ImportSessionForm(meta={'csrf': False})
if form.validate_on_submit():
sessions.import_session(db.session, dataset, form.session_name.data, form.session_file.data)
return redirect(url_for('dataset_overview', dataset_name=dataset.name))
label_session_count = len(sessions.get_sessions(db.session, dataset))
return render_template('import_session.html',
dataset=dataset,
form=form,
label_session_count=label_session_count)
def create_categorical_session(dataset_name: str):
dataset = backend.get_dataset(dataset_name)
if dataset is None:
abort(400)
current_sessions = sessions.get_sessions(db.session, dataset)
label_session_count = len(current_sessions)
form = CreateCategoricalSessionForm(meta={'csrf': False})
if form.validate_on_submit():
if form.session_name.data in [se.session_name for se in current_sessions]:
form.session_name.errors.append('Session name already in use.')
else:
label_values = [v.strip() for v in form.label_values.data.split(',')]
sessions.create_categorical_image_session(db.session, form.session_name.data, form.prompt.data,
dataset, label_values)
return redirect(url_for('dataset_overview', dataset_name=dataset.name))
return render_template('create_categorical_session.html',
dataset=dataset,
label_session_count=label_session_count,
form=form)
def test_get_sessions_empty(self):
dataset = backend.get_dataset('dataset1')
label_sessions = sessions.get_sessions(db.session, dataset)
label_session_count = len(label_sessions)
self.assertEqual(label_session_count, 0)
def dataset_list():
datasets = [(d, backend.get_images(d), sessions.get_sessions(db.session, d))
for d in backend.get_datasets()]
return render_template('dataset_list.html',
datasets=datasets)