Rakanid Rakanid - 1 month ago 18
Python Question

ValueError: total size of new array must be unchanged

I am trying to execute the code from this URL. However, I started getting this error:

des = np.array(des,np.float32).reshape((1,128))
ValueError: total size of new array must be unchanged


I have not made any major changes though. But I will paste what I did:

import scipy as sp
import numpy as np
import cv2

# Load the images
img =cv2.imread("image1.png")

# Convert them to grayscale
imgg =cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

# SURF extraction
surf = cv2.FeatureDetector_create("SURF")
surfDescriptorExtractor = cv2.DescriptorExtractor_create("SURF")
kp = surf.detect(imgg)
kp, descritors = surfDescriptorExtractor.compute(imgg,kp)

# Setting up samples and responses for kNN
samples = np.array(descritors)
responses = np.arange(len(kp),dtype = np.float32)

# kNN training
knn = cv2.KNearest()
knn.train(samples,responses)

modelImages = ["image2.png"]

for modelImage in modelImages:

# Now loading a template image and searching for similar keypoints
template = cv2.imread(modelImage)
templateg= cv2.cvtColor(template,cv2.COLOR_BGR2GRAY)
keys = surf.detect(templateg)

keys,desc = surfDescriptorExtractor.compute(templateg, keys)

for h,des in enumerate(desc):
des = np.array(des,np.float32).reshape((1,128))

retval, results, neigh_resp, dists = knn.find_nearest(des,1)
res,dist = int(results[0][0]),dists[0][0]

if dist<0.1: # draw matched keypoints in red color
color = (0,0,255)

else: # draw unmatched in blue color
#print dist
color = (255,0,0)

#Draw matched key points on original image
x,y = kp[res].pt
center = (int(x),int(y))
cv2.circle(img,center,2,color,-1)

#Draw matched key points on template image
x,y = keys[h].pt
center = (int(x),int(y))
cv2.circle(template,center,2,color,-1)



cv2.imshow('img',img)
cv2.imshow('tm',template)
cv2.waitKey(0)
cv2.destroyAllWindows()


Any help on this is greatly appreciated.

Answer Source

I had the same issue. I found that I changed the data length. A product of reshape arguments should be equal to a length of an array which you are changing. In your case:

des = np.array(des,np.float32).reshape(1, len(des))