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OpenCV Homography gives error: The input arrays should have at least

Following this https://www.youtube.com/watch?v=I8tHLZDDHr4&list=WL&index=1&ab_channel=Pysource tutorial on YouTube for my own project, answers I found basically had the exact same code, but my code gives me this error:
Traceback (most recent call last): File "c:\Users\NoName69\Desktop\ProJects\PyJects\Homography\test.py", line 31, in <module> matrix, mask = cv2.findHomography(query_p, train_p, cv2.RANSAC, 5.0) cv2.error: OpenCV(4.5.1) C:\Users\appveyor\AppData\Local\Temp\1\pip-req-build 5rb_9df3\opencv\modules\calib3d\src\fundam.cpp:385: error: (-28:Unknown error code -28) The input arrays should have at least 4 corresponding point sets to calculate Homography in function "cv::findHomography"
Code:
from cv2 import cv2
import numpy as np
img1 = cv2.cvtColor(cv2.imread("Aim Circle.png"), cv2.COLOR_RGB2GRAY)
img2 = cv2.cvtColor(cv2.imread("Map.png"), cv2.COLOR_RGB2GRAY)
sift = cv2.xfeatures2d.SIFT_create()
kp_img1, desc_img1 = sift.detectAndCompute(img1, None)
kp_img2, desc_img2 = sift.detectAndCompute(img2, None)
img1 = cv2.drawKeypoints(img1, kp_img1, img1)
img2 = cv2.drawKeypoints(img2, kp_img2, img2)
index_params = dict(algorithm = 0, trees = 5)
search_params = dict()
flann = cv2.FlannBasedMatcher(index_params, search_params)
while True:
matches = flann.knnMatch(desc_img1, desc_img2, k = 2)
good_kp = []
for m, n in matches:
if m.distance < 0.75 * n.distance:
good_kp.append(m)
if len(good_kp) > 2:
query_p = np.float32([kp_img1[m.queryIdx].pt for m in good_kp]).reshape(-1, 1 ,2)
train_p = np.float32([kp_img2[m.trainIdx].pt for m in good_kp]).reshape(-1, 1, 2)
matrix, mask = cv2.findHomography(query_p, train_p, cv2.RANSAC, 5.0)
if cv2.waitKey(25) & 0xFF == ord(" "):
cv2.destroyAllWindows()
break
OpenCv also gives this warning:
[ WARN:0] global c:\users\appveyor\appdata\local\temp\1\pip-req-build-5rb_9df3\opencv_contrib\modules\xfeatures2d\misc\python\shadow_sift.hpp (15) cv::xfeatures2d::SIFT_create DEPRECATED: cv.xfeatures2d.SIFT_create() is deprecated due SIFT tranfer to the main repository. https://github.com/opencv/opencv/issues/16736

I have found out the problem. OpenCV cannot find enough features in the file "Aim Circle.png", and so gives this error. If anyone knows another way to find a picture that is similar embedded in another picture it would be greatly appreciated.

i think in
if len(good_kp) > 2:
you have to substiture the value of 2 with a value greater than 4:
example: if len(good_kp) > 10:

_queryDescriptors.type() == trainDescType error training SVM using BoW of ORB features

I am training an SVM using the ORB descriptor next to BOW, however when I execute it I receive the following error
"return bowDiction.compute (gray, orb.detect (gray))
cv2.error: OpenCV (3.4.5) D: \ Build \ OpenCV \ opencv-3.4.5 \ modules \ features2d \ src \ matchers.cpp: 753: error: (-215: Assertion failed) _queryDescriptors.type () = = trainDescType in function 'cv :: BFMatcher :: knnMatchImpl' "
What I understand is that the error occurs because the query descriptor and train descriptor does not have the same type, however I can not find a way to correct it.
for p in training_paths:
image = cv2.imread(p)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Initiate STAR detector
orb = cv2.ORB_create()
# find the keypoints with ORB
kp = orb.detect(gray,None)
# compute the descriptors with ORB
kp, des = orb.compute(gray, kp)
des = np.float32(des)
BOW.add(des)
#dictionary created
dictionary = BOW.cluster()
FLANN_INDEX_KDTREE = 0
index_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5)
search_params = dict(checks=50) # or pass empty dictionary
flann = cv2.FlannBasedMatcher(index_params,search_params)
orb2 = cv2.ORB_create()
bowDiction = cv2.BOWImgDescriptorExtractor(orb2, cv2.BFMatcher(cv2.NORM_L2))
bowDiction.setVocabulary(dictionary)
print("bow dictionary", np.shape(dictionary))
#returns descriptor of image at pth
def feature_extract(pth):
im = cv2.imread(pth, 1)
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
return bowDiction.compute(gray, orb.detect(gray))
train_desc = []
train_labels = []
i = 0
for p in training_paths:
##Error Here
train_desc.extend(feature_extract(p))
if names_path[i]=='Accordian':
train_labels.append(1)
if names_path[i]=='Dollar Bill':
train_labels.append(2)
if names_path[i]=='Motor Bike':
train_labels.append(3)
if names_path[i]=='Soccer Ball':
train_labels.append(4)
i = i+1
After this, I hope to perform some techniques to evaluate the performance of the SVM classifier, I found the percentage of division and cross validation, however I do not know if they work in this case.
Finally, I would like to know what considerations i should have when training an SVM using BOW.

OpenCV error while feature matching with FLANN

I have a piece of code for matching features between a movie clip and a reference image. It generally works well, but sometimes it throws an error in the middle of a clip. Since it's always in the same clips, and at the same time, I guess there is something wrong with the frame it tries to analyze.
My code:
cap = cv2.VideoCapture(clip_file)
img1 = cv2.imread(ref_image,0)
while(cap.isOpened()):
# read the frame and convert to gray-scale
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Initiate ORB detector
orb = cv2.ORB_create()
# find the keypoints and descriptors with ORB
kp1, des1 = orb.detectAndCompute(img1,None)
kp2, des2 = orb.detectAndCompute(gray,None)
# FLANN parameters
FLANN_INDEX_LSH = 6
index_params= dict(algorithm = FLANN_INDEX_LSH,
table_number = 6, # 12
key_size = 12, # 20
multi_probe_level = 1) #2
search_params = dict(checks=50) # or pass empty dictionary
flann = cv2.FlannBasedMatcher(index_params,search_params)
matches = flann.knnMatch(des1,des2,k=2)
cv2.imshow('img3',frame)
The error it throws sometimes during the clip playing:
Traceback (most recent call last):
File "movie_test.py", line 81, in <module>
flann_movie('data/movie.avi','data/ref.jpg')
File "movie_test.py", line 35, in flann_movie
matches = flann.knnMatch(des1,des2,k=1)
cv2.error: OpenCV(3.4.2) C:\projects\opencv-
python\opencv\modules\flann\src\miniflann.cpp:317: error: (-5:Bad
argument) Only continuous arrays are supported in function
'cv::flann::buildIndex_'
Any suggestions on what causes the error would be appreciated. Thanks.

I think error is caused by frames of your video where no trace of original feature template was detected. Check what mid-results of matching are for each frame and then if that is the cause change the parameters of FLANN or simply skip those frames before the error occurs.

You have the following:
matches = flann.knnMatch(des1,des2,k=2)
With k=2 it means each element needs to have 2-nearest neighbors. As a result, each list of descriptors needs to have more than 2 elements each:
if(des1 is not None and len(des1)>2 and des2 is not None and len(des2)>2):
matches = flann.knnMatch(des1,des2,k=2)
(k-nearest neighbors algorithm)

opencv 3 python feature detection error on function cv2.detectAndCompute and also on cv2.compute

i use opencv 3.0.0 and python 2.7.5_x32
This is my code (ORB_feature_detection):
import numpy as np
import cv2
from matplotlib import pyplot as plt
img1 = cv2.imread('C:\\Python27\\madar1.jpg',0) # queryImage
img2 = cv2.imread('C:\\Python27\\madar2.jpg',0) # trainImage
# Initiate SIFT detector
orb = cv2.ORB_create()
# line 12
# find the keypoints and descriptors with SIFT
kp1, des1 = orb.detectAndCompute(img1,None)
kp2, des2 = orb.detectAndCompute(img2,None)
# create BFMatcher object
bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
# Match descriptors.
matches = bf.match(des1,des2)
# Sort them in the order of their distance.
matches = sorted(matches, key = lambda x:x.distance)
# Draw first 10 matches.
img3 = cv2.drawMatches(img1,kp1,img2,kp2,matches[:10], flags=2)
plt.imshow(img3),plt.show()
cv2.waitKey()
cv2.destroyAllWindows()
and this is the error message, the error message is on the
kp1, des1 = orb.detectAndCompute(img1,None) part,
i did work on opencv 2.4.11 and it doesn't work on opencv 3.0.0 !
Traceback (most recent call last):
File "C:\Python27\orb_matcher.py", line 12, in <module>
kp1, des1 = orb.detectAndCompute(img1,None)
error: ..\..\..\modules\python\src2\cv2.cpp:163: error: (-215) The data should normally be NULL! in function NumpyAllocator::allocate
please help me, what should i do to make this work?

You can try add this script after import cv2 and others cv2.ocl.setUseOpenCL(False) this solved my issue.

This is a known bug. You can find more information here https://github.com/opencv/opencv/issues/6081.
Today someone is fixing this issue: T-API python support implemented #6847.

OpenCV doesn't come with "external" libraries

I tried this example from the OpenCV website:
import numpy as np
import cv2
from matplotlib import pyplot as plt
# changed the image names from box* since the sample images were not given on the site
img1 = cv2.imread('burger.jpg',0) # queryImage
img2 = cv2.imread('burger.jpg',0) # trainImage
# Initiate SIFT detector
sift = cv2.SIFT()
# find the keypoints and descriptors with SIFT
kp1, des1 = sift.detectAndCompute(img1,None)
kp2, des2 = sift.detectAndCompute(img2,None)
# FLANN parameters
FLANN_INDEX_KDTREE = 0
index_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5)
search_params = dict(checks=50) # or pass empty dictionary
flann = cv2.FlannBasedMatcher(index_params,search_params)
matches = flann.knnMatch(des1,des2,k=2)
# Need to draw only good matches, so create a mask
matchesMask = [[0,0] for i in xrange(len(matches))]
# ratio test as per Lowe's paper
for i,(m,n) in enumerate(matches):
if m.distance < 0.7*n.distance:
matchesMask[i]=[1,0]
draw_params = dict(matchColor = (0,255,0),
singlePointColor = (255,0,0),
matchesMask = matchesMask,
flags = 0)
img3 = cv2.drawMatchesKnn(img1,kp1,img2,kp2,matches,None,**draw_params)
plt.imshow(img3,),plt.show()
Executing the example, viz. python test.py, gives the following error:
Traceback (most recent call last):
File "test.py", line 10, in <module>
sift = cv2.SIFT()
AttributeError: 'module' object has no attribute 'SIFT'
I had installed OpenCV from source, building manually. All modules were built by make, if I recall correctly.
This question suggested that I install opencv-contrib from its GitHub repository. I did, and I still get this error.
My system is Ubuntu 15.04 64-bit.

I'm not entirely sure if this is applicable, but at some point they stopped supporting SIFT in the later versions of opencv I believe due to the fact that it is patented or something related (source?), however an alternate is to use ORB which will have a similar effect.
You could try something like this:
from cv2 import ORB as SIFT
However in the event that you get an import error this also might work for you:
SIFT = cv2.ORB_create
If you insert those near the top of your file, then likely you can leave "SIFT" as it is throughout the file (well more or less, you get the idea, basically replace the cv2.Sift() with sift = SIFT() and you should be in better shape.)