我有一个机器学习的面部识别脚本,该脚本读取您放置在同一目录中的图像,并显示带有标签的面部。但是,如果我给它提供一个大到适合在屏幕上显示的图像,那么它就不合适了。我将如何在Python脚本中调整此图像的大小以适合我的屏幕。 谢谢
CODE
import face_recognition as fr
import os
import cv2
import face_recognition
import numpy as np
from time import sleep
def get_encoded_faces():
"""
looks through the faces folder and encodes all
the faces
:return: dict of (name, image encoded)
"""
encoded = {}
for dirpath, dnames, fnames in os.walk("./faces"):
for f in fnames:
if f.endswith(".jpg") or f.endswith(".png"):
face = fr.load_image_file("faces/" + f)
encoding = fr.face_encodings(face)[0]
encoded[f.split(".")[0]] = encoding
return encoded
def unknown_image_encoded(img):
"""
encode a face given the file name
"""
face = fr.load_image_file("faces/" + img)
encoding = fr.face_encodings(face)[0]
return encoding
def classify_face(im):
faces = get_encoded_faces()
faces_encoded = list(faces.values())
known_face_names = list(faces.keys())
face_locations = face_recognition.face_locations(img)
unknown_face_encodings = face_recognition.face_encodings(img, face_locations)
face_names = []
for face_encoding in unknown_face_encodings:
# See if the face is a match for the known face(s)
matches = face_recognition.compare_faces(faces_encoded, face_encoding)
name = "Unknown"
# use the known face with the smallest distance to the new face
face_distances = face_recognition.face_distance(faces_encoded, face_encoding)
best_match_index = np.argmin(face_distances)
if matches[best_match_index]:
name = known_face_names[best_match_index]
face_names.append(name)
for (top, right, bottom, left), name in zip(face_locations, face_names):
# Draw a box around the face
cv2.rectangle(img, (left-20, top-20), (right+20, bottom+20), (255, 0, 0), 2)
# Draw a label with a name below the face
cv2.rectangle(img, (left-20, bottom -15), (right+20, bottom+20), (255, 0, 0), cv2.FILLED)
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(img, name, (left -20, bottom + 15), font, 1.0, (255, 255, 255), 2)
# Display the resulting image
while True:
cv2.imshow('Image', img)
if cv2.waitKey(1) & 0xFF == ord('q'):
return face_names
print(classify_face("test.jpg"))
如您所见,我添加了一些注释以帮助完成此过程。 任何帮助将不胜感激!
答案 0 :(得分:0)
使用matplotlib.pyplot.imshow
,那么您就不会遇到这个问题。在大多数情况下,OpenCV都会这样做,所以我更喜欢matplotlib
。
import matplotlib.pyplot as plt
plt.imshow(img)
plt.show()
答案 1 :(得分:0)
您可以安装以下模块:
pip install screeninfo
然后使用以下代码获取屏幕尺寸:
import screeninfo
for monitor in screeninfo.get_monitors():
print(str(monitor))
从字符串中提取尺寸,然后使用cv.resize()函数使图像适合屏幕。
如果您已经知道屏幕的分辨率,另一种解决方案是添加一个简单的if语句,如果图像的尺寸超过显示器的尺寸,则可以将其调整为当前尺寸。