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issue 435

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This commit is contained in:
Sefik Ilkin Serengil 2022-03-11 20:43:26 +00:00
parent a4c6355344
commit 79e78e8448
1 changed files with 33 additions and 25 deletions
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58
tests/unit_tests.py
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@ -28,10 +28,13 @@ print("-----------------------------------------")
#----------------------------------------- #-----------------------------------------
print("DeepFace.detectFace test") print("DeepFace.detectFace test")
detectors = ['opencv', 'ssd', 'dlib', 'mtcnn', 'retinaface'] #detectors = ['opencv', 'ssd', 'dlib', 'mtcnn', 'retinaface']
detectors = ['opencv', 'ssd', 'mtcnn', 'retinaface']
for detector in detectors: for detector in detectors:
img = DeepFace.detectFace("dataset/img11.jpg", detector_backend = detector) img = DeepFace.detectFace("dataset/img11.jpg", detector_backend = detector)
print(detector," test is done") print(detector," test is done")
#import matplotlib.pyplot as plt #import matplotlib.pyplot as plt
#plt.imshow(img) #plt.imshow(img)
#plt.show() #plt.show()
@ -39,7 +42,6 @@ for detector in detectors:
#----------------------------------------- #-----------------------------------------
print("-----------------------------------------") print("-----------------------------------------")
img_path = "dataset/img1.jpg" img_path = "dataset/img1.jpg"
embedding = DeepFace.represent(img_path) embedding = DeepFace.represent(img_path)
print("Function returned ", len(embedding), "dimensional vector") print("Function returned ", len(embedding), "dimensional vector")
@ -73,9 +75,10 @@ print("opencv detector")
res = DeepFace.verify(dataset, detector_backend = 'opencv') res = DeepFace.verify(dataset, detector_backend = 'opencv')
print(res) print(res)
print("dlib detector") if False:
res = DeepFace.verify(dataset, detector_backend = 'dlib') print("dlib detector")
print(res) res = DeepFace.verify(dataset, detector_backend = 'dlib')
print(res)
print("mtcnn detector") print("mtcnn detector")
res = DeepFace.verify(dataset, detector_backend = 'mtcnn') res = DeepFace.verify(dataset, detector_backend = 'mtcnn')
@ -192,7 +195,7 @@ dataset = [
#models = ['VGG-Face', 'Facenet', 'OpenFace', 'DeepFace', 'DeepID', 'Dlib', 'ArcFace'] #models = ['VGG-Face', 'Facenet', 'OpenFace', 'DeepFace', 'DeepID', 'Dlib', 'ArcFace']
metrics = ['cosine', 'euclidean', 'euclidean_l2'] metrics = ['cosine', 'euclidean', 'euclidean_l2']
models = ['VGG-Face', 'Facenet', 'Facenet512', 'Dlib', 'ArcFace'] #those are robust models models = ['VGG-Face', 'Facenet', 'Facenet512', 'ArcFace'] #those are robust models
#metrics = ['cosine'] #metrics = ['cosine']
passed_tests = 0; test_cases = 0 passed_tests = 0; test_cases = 0
@ -267,41 +270,46 @@ print(resp_obj)
#----------------------------------- #-----------------------------------
print("--------------------------") print("--------------------------")
print("Ensemble for find function") if False:
df = DeepFace.find(img_path = "dataset/img1.jpg", db_path = "dataset", model_name = "Ensemble") print("Ensemble for find function")
print(df.head()) df = DeepFace.find(img_path = "dataset/img1.jpg", db_path = "dataset", model_name = "Ensemble")
print(df.head())
#----------------------------------- #-----------------------------------
print("--------------------------") print("--------------------------")
print("Ensemble for verify function") if False:
resp_obj = DeepFace.verify(dataset, model_name = "Ensemble") print("Ensemble for verify function")
resp_obj = DeepFace.verify(dataset, model_name = "Ensemble")
for i in range(0, len(dataset)): for i in range(0, len(dataset)):
item = resp_obj['pair_%s' % (i+1)] item = resp_obj['pair_%s' % (i+1)]
verified = item["verified"] verified = item["verified"]
score = item["score"] score = item["score"]
print(verified) print(verified)
#----------------------------------- #-----------------------------------
print("--------------------------") print("--------------------------")
print("Pre-trained ensemble method - find") if False:
from deepface import DeepFace print("Pre-trained ensemble method - find")
from deepface.basemodels import Boosting
model = Boosting.loadModel() from deepface import DeepFace
df = DeepFace.find("dataset/img1.jpg", db_path = "dataset", model_name = 'Ensemble', model = model, enforce_detection=False) from deepface.basemodels import Boosting
print(df) model = Boosting.loadModel()
df = DeepFace.find("dataset/img1.jpg", db_path = "dataset", model_name = 'Ensemble', model = model, enforce_detection=False)
print(df)
#----------------------------------- #-----------------------------------
print("--------------------------") print("--------------------------")
print("Pre-trained ensemble method - verify") if False:
res = DeepFace.verify(dataset, model_name = "Ensemble", model = model) print("Pre-trained ensemble method - verify")
print(res) res = DeepFace.verify(dataset, model_name = "Ensemble", model = model)
print(res)
#----------------------------------- #-----------------------------------
print("--------------------------") print("--------------------------")