Question

这是我的代码（基于购买者的代码）：

import face_recognition
import cv2

# This is a super simple (but slow) example of running face recognition 
on live video from your webcam.
# There's a second example that's a little more complicated but runs 
faster.

# PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be 
installed only to read from your webcam.
# OpenCV is *not* required to use the face_recognition library. It's 
only required if you want to run this
# specific demo. If you have trouble installing it, try any of the other 
demos that don't require it instead.

# Get a reference to webcam #0 (the default one)
video_capture = cv2.VideoCapture('video2.mp4')

# Load a sample picture and learn how to recognize it.
obama_image =face_recognition.load_image_file("/Users/user/Desktop/CODE/FACE_RECO/obama.jpg")

obama_face_encoding = face_recognition.face_encodings（obama_image）[0]

# Create arrays of known face encodings and their names
known_face_encodings = [
    obama_face_encoding,

]
known_face_names = [
    "Barack Obama",

]

while True:
    # Grab a single frame of video
    ret, frame = video_capture.read()

    # Convert the image from BGR color (which OpenCV uses) to RGB color 
(which face_recognition uses)
    rgb_frame = frame[:, :, ::-1]

# Find all the faces and face enqcodings in the frame of video
face_locations = face_recognition.face_locations(rgb_frame)
face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)

# Loop through each face in this frame of video
for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
    # See if the face is a match for the known face(s)
    matches = face_recognition.compare_faces(known_face_encodings, face_encoding)

    name = "Unknown"

    # If a match was found in known_face_encodings, just use the first one.
    if True in matches:
        first_match_index = matches.index(True)
        name = known_face_names[first_match_index]

    # Draw a box around the face
    cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
    cv2.imwrite("essai.png",cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2))

    # Draw a label with a name below the face
    cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
    font = cv2.FONT_HERSHEY_DUPLEX
    cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)

# Display the resulting image
cv2.imshow('Video', frame)

# Hit 'q' on the keyboard to quit!
if cv2.waitKey(1) & 0xFF == ord('q'):
    break


video_capture.release()
cv2.destroyAllWindows()

我唯一修改的是imwrite，但是我在这里遇到了问题。我只想导出红色框中的头像，但是当我使用imwrite功能时，它将导出所有图片。您如何解决？

Answer 1

您需要将imageRoi选择到新的垫子中，然后将新的垫子而不是框架覆盖。一些有用的功能：

# Crop image
imCrop = frame[top:bottom, left:right]

# Display cropped image
cv2.imshow("Video", imCrop)

Answer 2

如果要保存检测到/识别出的脸，则必须在for-loop内执行以下操作：

cv2.imwrite("your_filename_.jpg", frame[top:bottom, left:right])

导出ROI OpenCV

2 个答案: