def test_image(image_to_check,
known_names,
known_face_encodings,
tolerance=0.6,
show_distance=False):
unknown_image = face_recognition.load_image_file(image_to_check)
if max(unknown_image.shape) > 1600:
pil_img = PIL.Image.fromarray(unknown_image)
pil_img.thumbnail((1600, 1600), PIL.Image.LANCZOS)
unknown_image = np.array(pil_img)
unknown_encodings = face_recognition.face_encodings(unknown_image)
for unknown_encoding in unknown_encodings:
distances = face_recognition.face_distance(known_face_encodings,
unknown_encoding)
result = list(distances <= tolerance)
if True in result:
[
print_result(image_to_check, name, distance, show_distance) for
is_match, name, distance in zip(result, known_names, distances)
if is_match
]
else:
print_result(image_to_check, "unknown_person", None, show_distance)
if not unknown_encodings:
print_result(image_to_check, "no_persons_found", None, show_distance)
def test_image(image_to_check, model):
unknown_image = face_recognition.load_image_file(image_to_check)
face_locations = face_recognition.face_locations(
unknown_image, number_of_times_to_upsample=0, model=model)
for face_location in face_locations:
print_result(image_to_check, face_location)
def scan_known_people(known_people_folder):
known_names = []
known_face_encodings = []
for file in image_files_in_folder(known_people_folder):
basename = os.path.splitext(os.path.basename(file))[0]
img = face_recognition.load_image_file(file)
encodings = face_recognition.face_encodings(img)
if len(encodings) > 1:
click.echo(
"WARNING: More than one face found in {}. Only considering the first face."
.format(file))
if len(encodings) == 0:
click.echo(
"WARNING: No faces found in {}. Ignoring file.".format(file))
else:
known_names.append(basename)
known_face_encodings.append(encodings[0])
return known_names, known_face_encodings
def sortByFace(p, imageInput, des, reverse, threadID):
filesOwn = filesOwnA
nowS = datetime.datetime.now()
start = nowS.strftime("%H:%M:%S")
imageEncoding = loadFaceAndReturn(p, imageInput, des)
print(imageEncoding)
# print(str(len(filesOwnA)))
if reverse == "1":
print("reversing")
filesOwn = filesOwnA[::-1]
for file in filesOwn:
if os.path.exists(file):
d = os.path.join(file)
print(
"---------------------------------------------------------------------------"
)
print(d)
uk = ""
unknownEncoding = ""
uk = fr.load_image_file(d)
print("Load completed")
try:
unknownEncoding = fr.face_encodings(uk)[0]
print("File image encoded")
result = fr.compare_faces([imageEncoding], unknownEncoding)
print(result[0])
if result[0] == True:
newDir = p + "/" + des
if os.path.exists(newDir) == False:
os.mkdir(newDir)
print("Creating the directory: " + newDir)
source = d
print(os.path.basename(d))
destination = newDir + "/" + os.path.basename(d)
print(destination)
now = datetime.datetime.now()
a = now.strftime("%Y%m%d%H%M%S") + "[dx]"
destinationDX = newDir + "/" + a + os.path.basename(d)
if os.path.exists(destination):
print(
"Transfer: " + os.path.basename(source) +
" (This is a duplicated, this file will have a [dx] sign to be easily recognized."
)
try:
if os.path.exists(source):
shutil.move(source, destinationDX)
except:
print("Error during move")
else:
try:
if os.path.exists(source):
print("Transfer: " + os.path.basename(source))
shutil.move(source, destination)
except:
print("Error during move")
except Exception as e:
print("No faces detected")
nowE = datetime.datetime.now()
end = nowE.strftime("%H:%M:%S")
d = datetime.datetime.strptime(
end, "%H:%M:%S") - datetime.datetime.strptime(start, "%H:%M:%S")
print(str(d.seconds) + " seconds elapsed.")
def loadFaceAndReturn(p, imageInput, des):
ki = fr.load_image_file(imageInput)
print("Base image loaded.")
imageEncodingg = fr.face_encodings(ki)[0]
print("Base image encoded.")
return imageEncodingg