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tried to make it faster

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Ox 2023-10-12 13:43:19 -03:00
parent 1df77fa652
commit 084d470005
1 changed files with 15 additions and 30 deletions
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45
src/para_facematch.py
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@ -15,8 +15,6 @@ import paravision.recognition.utils as pru
class Facematch(object):
errstr = ""
def init(self):
print("@@@ initialising paravision")
try:
@ -64,36 +62,31 @@ class Facematch(object):
print("## loading images", dev1, dev2)
self.dev1 = dev1
self.dev2 = dev2
errstr = ""
try:
# Load images
errstr = "id image load"
self.id_image = pru.load_image(id_image_filepath)
errstr = "client photo load"
self.photo_image = pru.load_image(photo_image_filepath)
#print("++++++++++++++++ ",self.id_image)
return True
except Exception as e:
print("uk oh loading failed ", e)
return False
return "id image loading failed ", e
try:
self.photo_image = pru.load_image(photo_image_filepath)
except Exception as e:
return "client image loading failed ", e
return None
def get_faces(self):
print("# get faces...")
errstr = ""
try:
# Get all faces from images with qualities, landmarks, and embeddings
errstr = "getting faces"
print("Finding faces...")
self.inference_result = self.sdk.get_faces([self.id_image, self.photo_image], qualities=True, landmarks=True, embeddings=True)
print("Inferences...")
self.image_inference_result = self.inference_result.image_inferences
if len(self.image_inference_result)==0:
return "no inferences found"
# Get most prominent face
print("most prominent...")
errstr = "getting most prominent id face"
print("Most prominent...")
self.id_face = self.image_inference_result[0].most_prominent_face_index()
errstr = "getting most prominent id face"
self.photo_face = self.image_inference_result[1].most_prominent_face_index()
if self.id_face<0:
return "no id face found"
@ -101,27 +94,24 @@ class Facematch(object):
return "no live face found"
# Get numerical representation of faces (required for face match)
print("digesting...")
errstr = "getting numericals"
print("stats...")
if (len(self.image_inference_result)<2):
return "ID or human face could not be recognised"
self.id_emb = self.image_inference_result[0].faces[self.id_face].embedding
self.photo_emb = self.image_inference_result[1].faces[self.photo_face].embedding
except Exception as ex:
errstr = "image processing exception "+str(ex)
return False
return True
return "image processing exception "+str(ex)
return None
# return " id=%d photo=%d result=%d " % (self.id_face, self.photo_face, len(self.image_inference_result))
def compute_scores(self):
print("## compute scores...")
try:
# Get image quality scores (how 'good' a face is)
errstr = "getting image quality"
self.id_qual = self.image_inference_result[0].faces[self.id_face].quality
self.photo_qual = self.image_inference_result[1].faces[self.photo_face].quality
@ -129,7 +119,6 @@ class Facematch(object):
self.photo_qual = round(self.photo_qual, 3)
# Get face match score
errstr = "scoring"
self.match_score = self.sdk.get_match_score(self.id_emb, self.photo_emb)
# Create .json
@ -153,11 +142,7 @@ class Facematch(object):
#print(response.read())
except Exception as ex:
errstr = str(ex)
return False
return True
return str(ex)
def get_scores(self):