拥有face_recognition代码并尝试更改某些图片的BGR。使用以下行运行代码:python3 encode_faces.py --dataset dataset --encodings encodings.pickle
。有一种方法可以绕过下面的错误:
OpenCV(3.4.1) Error: Assertion failed (scn == 3 || scn == 4) in cvtColor, file /tmp/opencv-20180529-55469-97fkx6/opencv-3.4.1/modules/imgproc/src/color.cpp, line 11115
Traceback (most recent call last):
File "encode_faces.py", line 38, in <module>
rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
cv2.error: OpenCV(3.4.1) /tmp/opencv-20180529-55469-97fkx6/opencv-3.4.1/modules/imgproc/src/color.cpp:11115: error: (-215) scn == 3 || scn == 4 in function cvtColor
这是我的源代码:
# import the necessary packages
#asa s ruleaza
# python3 encode_faces.py --dataset dataset --encodings encodings.pickle
from imutils import paths
import face_recognition
import argparse
import pickle
import cv2
import os
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--dataset", required=True,
help="path to input directory of faces + images")
ap.add_argument("-e", "--encodings", required=True,
help="path to serialized db of facial encodings")
ap.add_argument("-d", "--detection-method", type=str, default="cnn",
help="face detection model to use: either `hog` or `cnn`")
args = vars(ap.parse_args())
# grab the paths to the input images in our dataset
print("[INFO] quantifying faces...")
imagePaths = list(paths.list_images(args["dataset"]))
# initialize the list of known encodings and known names
knownEncodings = []
knownNames = []
# loop over the image paths
for (i, imagePath) in enumerate(imagePaths):
# extract the person name from the image path
print("[INFO] processing image {}/{}".format(i + 1,
len(imagePaths)))
name = imagePath.split(os.path.sep)[-2]
# load the input image and convert it from RGB (OpenCV ordering)
# to dlib ordering (RGB)
image = cv2.imread(imagePath)
rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# detect the (x, y)-coordinates of the bounding boxes
# corresponding to each face in the input image
boxes = face_recognition.face_locations(rgb,
model=args["detection_method"])
# compute the facial embedding for the face
encodings = face_recognition.face_encodings(rgb, boxes)
# loop over the encodings
for encoding in encodings:
# add each encoding + name to our set of known names and
# encodings
knownEncodings.append(encoding)
knownNames.append(name)
# dump the facial encodings + names to disk
print("[INFO] serializing encodings...")
data = {"encodings": knownEncodings, "names": knownNames}
f = open(args["encodings"], "wb")
f.write(pickle.dumps(data))
f.close()
打印(image.shape)错误=
[INFO] quantifying faces...
[INFO] processing image 1/1401
libpng warning: iCCP: known incorrect sRGB profile
(1080, 1920, 3)
[INFO] processing image 2/1401
Traceback (most recent call last):
File "encode_faces.py", line 38, in <module>
print(image.shape)
AttributeError: 'NoneType' object has no attribute 'shape'
答案 0 :(得分:1)
似乎照片有误。他们必须重新校准。 DId运行另一个脚本来保存照片,以便创建新的数据集。它第二次起作用了。