# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from args import image_net_arg, brats_arg, image_retrieval_arg
DATA_SEQUENCES = {
'action-recognition': [
image_net_arg('00000001'),
image_net_arg('00000002'),
image_net_arg('00000003'),
image_net_arg('00000004'),
image_net_arg('00000005'),
image_net_arg('00000006'),
image_net_arg('00000007'),
image_net_arg('00000008'),
image_net_arg('00000009'),
image_net_arg('00000010'),
image_net_arg('00000011'),
image_net_arg('00000012'),
image_net_arg('00000013'),
image_net_arg('00000014'),
image_net_arg('00000015'),
image_net_arg('00000016'),
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from args import image_net_arg
IMAGE_SEQUENCES = {
'face-detection-adas': [
image_net_arg('00000002'),
image_net_arg('00000032'),
image_net_arg('00000184'),
image_net_arg('00000442'),
image_net_arg('00008165'),
image_net_arg('00008170'),
image_net_arg('00008172'),
image_net_arg('00040548'),
image_net_arg('00040557'),
image_net_arg('00045630'),
],
'gaze-estimation-adas': [
image_net_arg('00008165'),
image_net_arg('00008170'),
image_net_arg('00012803'),
image_net_arg('00018801'),
'-v': ModelFileArg('bert-base-ner', 'bert-base-ner/vocab.txt')
}),
)),
PythonDemo(name='colorization_demo', device_keys=['-d'], test_cases=combine_cases(
TestCase(options={
'--no_show': None,
**MONITORS,
'-i': DataPatternArg('classification'),
'-m': ModelArg('colorization-v2'),
})
)),
PythonDemo(name='face_detection_mtcnn_demo', device_keys=['-d'], test_cases=combine_cases(
TestCase(options={'--no_show': None,
'-i': image_net_arg('00000002'),
'-m_p': ModelArg('mtcnn-p'),
'-m_r': ModelArg('mtcnn-r'),
'-m_o': ModelArg('mtcnn-o')}),
)),
PythonDemo(name='face_recognition_demo', device_keys=['-d_fd', '-d_lm', '-d_reid'],
test_cases=combine_cases(
TestCase(options={'--no_show': None,
**MONITORS,
'-i': DataPatternArg('face-detection-adas'),
'-fg': DataDirectoryArg('face-recognition-gallery')
}),
single_option_cases('-m_fd',
ModelArg('face-detection-adas-0001'),
ModelArg('face-detection-retail-0004'),
device_keys=['-d'],
test_cases=combine_cases(
TestCase(
options={
'--no_show': None,
**MONITORS,
'-i': DataPatternArg('classification'),
'-m': ModelArg('colorization-v2'),
}))),
PythonDemo(name='face_detection_mtcnn_demo',
device_keys=['-d'],
test_cases=combine_cases(
TestCase(
options={
'--no_show': None,
'-i': image_net_arg('00000002'),
'-m_p': ModelArg('mtcnn-p'),
'-m_r': ModelArg('mtcnn-r'),
'-m_o': ModelArg('mtcnn-o')
}), )),
PythonDemo(
name='gesture_recognition_demo',
device_keys=['-d'],
test_cases=combine_cases(
TestCase(
options={
'--no_show':
None,
'-i':
TestDataArg(
'msasl/global_crops/_nz_sivss20/clip_0017/img_%05d.jpg'