Example #1
0
import cv2, cv
import numpy as np

#./pca_gen.py ./image_dir pc_size xblks yblks

gist.init(320,50)
print "PCA size", int(sys.argv[2])
pcadata = None

xblks=int(sys.argv[3])
yblks=int(sys.argv[4])

print sys.argv[1], int(sys.argv[2]), int(sys.argv[3]), int(sys.argv[4])

for f in os.listdir(sys.argv[1]):
	desc = gist.alloc(xblks,yblks)
	im = cv2.imread(sys.argv[1] + "/" + f)

	gist.process(im)
	gist.get(desc,0,320)

	if pcadata == None:
		pcadata = desc[0]
	else:
		pcadata = np.hstack([pcadata, desc[0]])
		
pcadata = np.transpose(pcadata)
print pcadata.shape
mean, eigenvectors = cv2.PCACompute(pcadata, maxComponents=int(sys.argv[2]))

print "Primary Component count ", eigenvectors.shape
Example #2
0
#!/usr/bin/python

import libgist as gist
import cv2
import numpy as np




cv2.namedWindow("Training Images")

im = cv2.imread("./mec2.jpg")


print im.shape
gist.init(im.shape[1],im.shape[0])


gist.process(im)

desc = gist.alloc(4,4)
print desc
gist.get(desc, 0,0, 240, 180)

gist.create_corner_descriptor(im, 5, 10, 10, 2, 2)



Example #3
0
import cv2, cv
import numpy as np

#./pca_gen.py ./image_dir pc_size xblks yblks

gist.init(320, 50)
print "PCA size", int(sys.argv[2])
pcadata = None

xblks = int(sys.argv[3])
yblks = int(sys.argv[4])

print sys.argv[1], int(sys.argv[2]), int(sys.argv[3]), int(sys.argv[4])

for f in os.listdir(sys.argv[1]):
    desc = gist.alloc(xblks, yblks)
    im = cv2.imread(sys.argv[1] + "/" + f)

    gist.process(im)
    gist.get(desc, 0, 320)

    if pcadata == None:
        pcadata = desc[0]
    else:
        pcadata = np.hstack([pcadata, desc[0]])

pcadata = np.transpose(pcadata)
print pcadata.shape
mean, eigenvectors = cv2.PCACompute(pcadata, maxComponents=int(sys.argv[2]))

print "Primary Component count ", eigenvectors.shape