|
import os |
|
import urllib.request |
|
|
|
if not os.path.exists("data"): |
|
os.mkdir("data") |
|
urllib.request.urlretrieve("https://upload.wikimedia.org/wikipedia/commons/b/bb/Andy_Lau_%E5%88%98%E5%BE%B7%E5%8D%8E%2C_Beijing_International_Film_Festival_%E5%8C%97%E4%BA%AC%E7%94%B5%E5%BD%B1%E8%8A%82%2C_2013_%28cropped%29.jpg", "data/劉德華.jpg") |
|
urllib.request.urlretrieve("https://upload.wikimedia.org/wikipedia/commons/d/dc/Chaplin_The_Champion.jpg", "data/卓別林.jpg") |
|
urllib.request.urlretrieve("https://upload.wikimedia.org/wikipedia/commons/thumb/8/86/Dayo_Wong_at_Olympian_City.jpg/800px-Dayo_Wong_at_Olympian_City.jpg", "data/黃子華.jpg") |
|
urllib.request.urlretrieve("https://upload.wikimedia.org/wikipedia/commons/2/2c/Woody_Allen_Cannes_2015.jpg", "data/伍迪·艾伦.jpg") |
|
urllib.request.urlretrieve("https://upload.wikimedia.org/wikipedia/commons/0/09/RussellPeters08TIFF.jpg", "data/罗素·彼得斯.jpg") |
|
opener = urllib.request.URLopener() |
|
opener.addheader('User-Agent', 'whatever') |
|
opener.retrieve("https://cfcdn.she.com/media/she.com/2023/03/411903-411903-Screenshot-2023-03-10-at-11.19.32-940x1024.png", "data/林青霞.png") |
|
opener.retrieve("https://cfcdn.she.com/media/she.com/2023/03/122403-122403-IMG_4831-481x600-1.jpeg", "data/張曼玉.jpeg") |
|
opener.retrieve("https://cfcdn.she.com/media/she.com/2023/03/092803-092803-Screenshot-2023-03-10-at-11.28.01-687x1024.png", "data/關之琳.png") |
|
opener.retrieve("https://cfcdn.she.com/media/she.com/2023/03/233103-233103-Screenshot-2023-03-10-at-11.31.08-783x1024.png", "data/王祖賢.png") |
|
opener.retrieve("https://cfcdn.she.com/media/she.com/2023/03/433403-433403-w644-4.jpeg", "data/邱淑貞.jpeg") |
|
opener.retrieve("https://cfcdn.she.com/media/she.com/2023/03/333503-333503-20210621104344-80d11f2a.jpeg", "data/李嘉欣.jpeg") |
|
|
|
|
|
import face_recognition |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
known_encodings = [] |
|
known_persons = [] |
|
valid_images = [".jpg",".jpeg",".png"] |
|
for f in os.listdir("data"): |
|
ext = os.path.splitext(f)[1] |
|
if ext.lower() not in valid_images: |
|
continue |
|
|
|
|
|
known_image = face_recognition.load_image_file(os.path.join("data",f)) |
|
face_encoding = face_recognition.face_encodings(known_image)[0] |
|
known_encodings.append(face_encoding) |
|
|
|
known_persons.append(os.path.basename(f)) |
|
|
|
import tempfile |
|
import faceSym |
|
from PIL import Image |
|
import numpy as np |
|
|
|
def left_right_sim(img): |
|
tmpf = tempfile.NamedTemporaryFile(delete=False) |
|
im = Image.fromarray(img) |
|
im.save(tmpf.name, format='png') |
|
f = faceSym.FaceSym(tmpf.name) |
|
_, left, _, _, right, _ = f.get_symmetrized_images(idx=0) |
|
tmpf.close() |
|
os.unlink(tmpf.name) |
|
left_encoding = face_recognition.face_encodings(np.asarray(left))[0] |
|
right_encoding = face_recognition.face_encodings(np.asarray(right))[0] |
|
diff = face_recognition.face_distance([left_encoding], right_encoding) |
|
return 100 * (1 - diff) |
|
|
|
import gradio as gr |
|
|
|
def greet(image_to_test): |
|
|
|
|
|
image_to_test_encoding = face_recognition.face_encodings(image_to_test)[0] |
|
|
|
|
|
face_distances = face_recognition.face_distance(known_encodings, image_to_test_encoding) |
|
idx = face_distances.argmin() |
|
filepath = known_persons[idx] |
|
face_distance = face_distances[idx] |
|
ret = "The most similar person is of {} with score {:.3}".format( |
|
os.path.splitext(filepath)[0], |
|
100 * (1 - face_distance)) |
|
img = face_recognition.load_image_file(os.path.join("data", filepath)) |
|
ret += "\n\n \ |
|
The similarity (symmetry score) of \ |
|
left and right face = {:.3}%".format( |
|
left_right_sim(image_to_test).item()) |
|
return img, ret |
|
|
|
iface = gr.Interface(fn=greet, inputs=gr.Image(source="webcam", streaming=True, type="numpy"), outputs=["image", "text"]) |
|
iface.launch() |
|
|