import glob
import cv2
import numpy as np
from PIL import Image
import init_auv as auv

imdir = '/Users/Mackeprang/Dropbox (Personlig)/Master Thesis/Pictures/20181005_084733.9640_Mission_1'
#imdir = auv.datasetPath_Mads()["Images"]
filenames = auv.imagesFilePath(imdir, '*.png')

prev_frame = None
orb = cv2.ORB_create()
bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
for i, frame in enumerate(filenames):
    if auv.image_broken(frame):
        continue
    img = cv2.imread(frame)
    gray = auv.preprocess_image(img, unsharp=False)
    if prev_frame is None:
        prev_frame = gray
        kp1, des1 = orb.detectAndCompute(prev_frame, None)
    print "Numbers of features: " + str(len(kp1))
    kp2, des2 = orb.detectAndCompute(gray, None)
    matches = bf.match(des1, des2)
    matches = sorted(matches, key=lambda x: x.distance)
    img_match = cv2.drawMatches(prev_frame,
                                kp1,
                                gray,
                                kp2,
                                matches[:10],
                                None,
Example #2
0
im_filename = '*.png'
imdir = '/Users/Mackeprang/Dropbox (Personlig)/Master Thesis/Pictures/20181005_084733.9640_Mission_1'
filenames = auv.imagesFilePath(imdir)
images = []

def nothing(x):
    pass

cv2.namedWindow('image')
# Creating trackbar:
cv2.createTrackbar('Threshold 1','image',0,1000,nothing)
cv2.createTrackbar('Threshold 2','image',0,1000,nothing)

num = 1
while(1):
    if auv.image_broken(filenames[num]):
        continue
    im = cv2.imread(filenames[num])
    thres1 = cv2.getTrackbarPos('Threshold 1','image')
    thres2 = cv2.getTrackbarPos('Threshold 2', 'image')
    gray = auv.preprocess_image(im)
    unsharp_im = cv2.Canny(gray,thres1,thres2)
    im_combined = np.hstack((gray,unsharp_im))
    cv2.imshow("image",im_combined)
    key = cv2.waitKey(10)
    if key & 0xFF == ord('q'):
        break
    if key & 0xFF == ord('n'):
        num +=1

cv2.destroyAllWindows()