def createGifs(imgDir, createGifsOf):
#Single usage: utils.createGif(cfg.imgDir+'\\ImgShow\\', img_names )
print 'Creating Gifs'
gifPath = imgDir + 'gifs\\'
if createGifsOf['original']:
originalPath = imgDir
if os.path.exists(originalPath):
img_names = utils.getListOfImages(originalPath, cfg.imgFormats)
utils.createGif(originalPath, img_names, 'original', gifPath)
if createGifsOf['translation']:
translationPath = imgDir + 'translation'
if os.path.exists(translationPath):
img_names = utils.getListOfImages(translationPath, cfg.imgFormats)
utils.createGif(translationPath, img_names, 'translation', gifPath)
if createGifsOf['width']:
widthPath = imgDir + 'width'
if os.path.exists(widthPath):
img_names = utils.getListOfImages(widthPath, cfg.imgFormats)
utils.createGif(widthPath, img_names, 'width', gifPath)
if createGifsOf['width_hq']:
width_hqPath = imgDir + 'width_hq'
if os.path.exists(width_hqPath):
img_names = utils.getListOfImages(width_hqPath, cfg.imgFormats)
utils.createGif(width_hqPath, img_names, 'width_hq', gifPath)
if createGifsOf['test']:
originalPath = imgDir + 'test'
if os.path.exists(originalPath):
img_names = utils.getListOfImages(originalPath, cfg.imgFormats)
utils.createGif(originalPath, img_names, 'test', gifPath)
def loadFiles():
Imgfolder = cfg.imgDir
ImgFileList = utils.getListOfImages(cfg.imgDir, cfg.imgFormats)
natsort(ImgFileList)
if ImgFileList.__contains__('Thumbs.db'):
ImgFileList.remove('Thumbs.db')
return ImgFileList, Imgfolder
def run(dir=cfg.imgDir, method='linear'):
curve = []
curve.append((0, 0))
time_start = time.time()
print 'Translating movement in ', dir
onlyImages = utils.getListOfImages(dir, cfg.imgFormats)
imgRef = cv2.imread(dir + onlyImages[0])
sift = cv2.SIFT()
referenceKp, referenceDes = sift.detectAndCompute(imgRef, None)
for i in range(1, len(onlyImages)):
curve.append(
getInitialCurve(sift, imgRef, referenceKp, referenceDes, dir,
onlyImages[i], i, curve))
correctX, correctY = getCurveFromMethod(curve, method)
for i in range(0, len(onlyImages)):
performCorrection(correctX[i], correctY[i], dir, onlyImages[i])
plt.figure()
x = [k[0] for k in curve]
y = [k[1] for k in curve]
for i in range(0, len(onlyImages)):
plt.plot(x, label='x', color='g')
plt.plot(y, label='y', color='b')
plt.plot(correctX, label='fitx', color='c')
plt.plot(correctY, label='fity', color='m')
plt.xticks([k for k in range(1, len(x))])
plt.axvline(x=float(i), color='r')
plt.grid()
plt.legend()
append0 = '0'
if i >= 10.0:
append0 = ''
plt.savefig(cfg.imgDir + '\\translation\\' + append0 + str(i) + '.jpg')
plt.clf()
total_time = time.time() - time_start
np.save(dir + '\\translation\\translationX.npy', correctX)
np.save(dir + '\\translation\\translationY.npy', correctY)
print 'Translating displacement finished, spending time:', total_time
print '##############################################################'
from Configuration import Config as cfg
from Tools import utils
import cv2
import pdb
import matplotlib.pyplot as plt
img_names = utils.getListOfImages(cfg.imgDir+'BW_resized\\', cfg.imgFormats)
imgs = utils.loadAllImages(cfg.imgDir+'BW_resized\\', cfg.imgFormats, False)
img = imgs[0]
#find first vessel
bw_layer = img[:][:][0]
k=0
for row in bw_layer:
if sum(row)>0:
print 'ZES'
newRow = row*255
bw_layer[k]=newRow
cv2.imshow('image', bw_layer)
cv2.waitKey(0)
pdb.set_trace()
k+=1
laplacian = cv2.Laplacian(img, cv2.CV_64F)
sobelx = cv2.Sobel(img, cv2.CV_64F, 1, 0, ksize=5)
sobely = cv2.Sobel(img, cv2.CV_64F, 0, 1, ksize=5)
def justCreateGif(imgDir):
if os.path.exists(imgDir):
img_names = utils.getListOfImages(imgDir, cfg.imgFormats)
print 'got image names'
utils.createGif(imgDir, img_names, 'thisGif', imgDir)
from Tools.BGR2RGB import BGR2RGB
from Tools.ZoneMarker import zoneMarker
from Tools.SortFolder import natsort
from Configuration import Config as cfg
from Tools import utils
"""
This program is trying to realize the vessel analysis for Infared Images!!
"""
ImgNumber = 0
SegMethod = 2 ##Gabor 1 / LineDetector 2
"""provide the image folder location"""
# Imgfolder = 'Image\\folder\\path\\'
Imgfolder = cfg.imgDir
ImgFileList = utils.getListOfImages(cfg.imgDir, cfg.imgFormats)
natsort(ImgFileList)
if ImgFileList.__contains__('Thumbs.db'):
ImgFileList.remove('Thumbs.db')
"Read a image first: "
ImgName = Imgfolder + ImgFileList[ImgNumber]
Img0 = cv2.imread(ImgName)
print 'Img Name:', ImgNumber, ImgFileList[ImgNumber]
"""Resize the image"""
downsizeRatio = 1
Img_Resized = cv2.resize(Img0, dsize=None, fx=downsizeRatio, fy=downsizeRatio)
Mask = np.zeros((Img_Resized.shape[:2]), dtype=np.uint8)
Mask[20:-20, 20:-20] = 1
Img = Img_Resized.copy()
##############################################################
bf = cv2.BFMatcher()
matches = bf.knnMatch(referenceDes, targetDes, k=2)
# Apply ratio test
good = []
for m, n in matches:
if m.distance < 0.75 * n.distance:
# Removed the brackets around m
good.append(m)
src_pts = np.float32([referenceKp[m.queryIdx].pt for m in good]).reshape(-1, 1, 2)
dst_pts = np.float32([targetKp[m.trainIdx].pt for m in good]).reshape(-1, 1, 2)
M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)
#matchesMask = mask.ravel().tolist()
dst = cv2.warpPerspective(imgTarget, inv(M), (1600, 1200))
# plt.subplot(121),plt.imshow(img2),plt.title('Input')
# plt.subplot(122),plt.imshow(dst),plt.title('Output')
# plt.show()
cv2.imwrite(imgDir+'\\warpPerspective\\'+targetImg,dst)
onlyImages = utils.getListOfImages(cfg.imgDir, cfg.imgFormats)
imgRef = cv2.imread(cfg.imgDir+onlyImages[0],0)
sift = cv2.SIFT()
referenceKp, referenceDes = sift.detectAndCompute(imgRef,None)
cv2.imwrite(cfg.imgDir+'warpPerspective\\'+onlyImages[0],imgRef)
for i in range(1,len(onlyImages)):
warpPerspective(referenceKp, referenceDes, cfg.imgDir, onlyImages[i])
#img=cv2.drawKeypoints(img1,kp1,flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
def copyImages(baseDir, formats, targetDir):
print 'Copying images from ', baseDir, ' to ', targetDir
img_names = utils.getListOfImages(baseDir, formats)
for img in img_names:
copyfile(baseDir + img, targetDir + img)
print '##############################################################'