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[to #42322933] move input face_deteciton pipeline into face_recognition init

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Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9652773

    * move input face_deteciton pipeline into face_recognition init
This commit is contained in:
yuxiang.tyx
2022-08-05 12:32:52 +08:00
committed by yingda.chen
parent cb1aa66a49
commit d38f9f442b
2 changed files with 6 additions and 10 deletions
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7
modelscope/pipelines/cv/face_recognition_pipeline.py
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@@ -24,12 +24,11 @@ logger = get_logger()
Tasks.face_recognition, module_name=Pipelines.face_recognition)
class FaceRecognitionPipeline(Pipeline):
def __init__(self, model: str, face_detection: Pipeline, **kwargs):
def __init__(self, model: str, **kwargs):
"""
use `model` to create a face recognition pipeline for prediction
Args:
model: model id on modelscope hub.
face_detecion: pipeline for face detection and face alignment before recognition
"""
# face recong model
@@ -47,7 +46,9 @@ class FaceRecognitionPipeline(Pipeline):
self.face_model = face_model
logger.info('face recognition model loaded!')
# face detect pipeline
self.face_detection = face_detection
det_model_id = 'damo/cv_resnet_facedetection_scrfd10gkps'
self.face_detection = pipeline(
Tasks.face_detection, model=det_model_id)
def _choose_face(self,
det_result,

9
tests/pipelines/test_face_recognition.py
View File

@@ -17,20 +17,15 @@ from modelscope.utils.test_utils import test_level
class FaceRecognitionTest(unittest.TestCase):
def setUp(self) -> None:
self.recog_model_id = 'damo/cv_ir101_facerecognition_cfglint'
self.det_model_id = 'damo/cv_resnet_facedetection_scrfd10gkps'
self.model_id = 'damo/cv_ir101_facerecognition_cfglint'
@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
def test_face_compare(self):
img1 = 'data/test/images/face_recognition_1.png'
img2 = 'data/test/images/face_recognition_2.png'
face_detection = pipeline(
Tasks.face_detection, model=self.det_model_id)
face_recognition = pipeline(
Tasks.face_recognition,
face_detection=face_detection,
model=self.recog_model_id)
Tasks.face_recognition, model=self.model_id)
# note that for dataset output, the inference-output is a Generator that can be iterated.
emb1 = face_recognition(img1)[OutputKeys.IMG_EMBEDDING]
emb2 = face_recognition(img2)[OutputKeys.IMG_EMBEDDING]