def test_database(img_path, db_path):
if not os.path.isfile(img_path) or not os.path.isdir(db_path):
print("indicated path doesn't exist!")
return
# load test image
img_A = cv2.imread(img_path)
seeta_A = seetaface.SeetaImage(img_A)
faces_A = fd.detect(seeta_A)
featA = extract_features(seeta_A, faces_A[0].pos)
# load database
for fn in os.listdir(db_path):
fp = os.path.join(db_path, fn)
if not os.path.isfile(fp): continue
img_B = cv2.imread(fp)
seeta_B = seetaface.SeetaImage(img_B)
# detect face in image
faces_B = fd.detect(seeta_B)
if len(faces_A) and len(faces_B):
sim_list = []
for face in faces_B:
featB = extract_features(seeta_A, face.pos)
sim = fr.calcsim(featA, featB)
sim_list.append(sim)
colr = (0, 0, 255) if sim < 0.65 else (255, 0, 0)
mark(img_B, face.pos, colr)
print('sim: {}'.format(sim_list))
show(img_B)
def test_simple():
img = cv2.imread(single)
seetaImg = seetaface.SeetaImage(img)
faces = fd.detect(seetaImg)
features = extract_features(seetaImg, faces[0].pos)
img_B = cv2.imread(double)
seeta_B = seetaface.SeetaImage(img_B)
faces_B = fd.detect(seeta_B)
for face in faces_B:
rect = face.pos
feats = extract_features(seeta_B, rect)
sim = fr.calcsim(features, feats)
print(sim)
colr = (0, 0, 255) if sim < 0.65 else (255, 0, 0)
mark(img_B, rect, colr)
show(img_B)
import seetaface
import cv2
root = 'example2.jpg'
image = seetaface.SeetaImage(root)
pd = seetaface.PointDetector(
'/home/tumh/python-seetaface2/SeetaPointDetector2.0.pts5.ats')
# given a boudning box
rect = seetaface.SeetaRect()
rect.x = 221
rect.y = 130
rect.width = 232
rect.height = 278
im = cv2.imread(root)
cv2.rectangle(im, (rect.x, rect.y),
(rect.x + rect.width, rect.y + rect.height), (0, 0, 255), 2)
points = pd.detect(image, rect)
for p in points:
cv2.circle(im, (int(p.x), int(p.y)), 2, (0, 0, 255), -1)
cv2.imwrite('example2_result.jpg', im)
import seetaface
import cv2
root = 'examples/example1.jpg'
fd = seetaface.FaceDetector('models/fd_2_00.dat')
fl = seetaface.FaceLandmarker('models/pd_2_00_pts81.dat')
print("model loaded")
im = cv2.imread(root)
image = seetaface.SeetaImage(im)
print("image loaded")
# or you can pass image path to SeetaImage
# image = seetaface.SeetaImage(root)
faces = fd.detect(image)
for face in faces:
rect = face.pos
cv2.rectangle(im, (rect.x, rect.y),
(rect.x + rect.width, rect.y + rect.height), (0, 0, 255), 2)
points = fl.detect(image, rect)
for p in points:
cv2.circle(im, (int(p.x), int(p.y)), 2, (0, 0, 255), -1)
cv2.imwrite('examples/example1_result.jpg', im)
cv2.imshow('win', im)
cv2.waitKey(0)