def __init__(self, starterWindow):
super(phaseMonster, self).setupUi(starterWindow)
self.imageName = None # holds image path
self.imageFormat = None # holds image format
self.mixer = image.mixer2Image(
) # holds the mixer object from image.py
self.image1 = image.image() # holds the image object from image.py
self.image2 = image.image() # holds the image object from image.py
self.out1 = image.image() # holds the image object of the first output
self.out2 = image.image(
) # holds the image object of the second output
self.imagesShapes = [] # holds images shapes loaded to be checked
self.images = [self.image1,
self.image2] # not used may be deleted later
self.logger = logging.getLogger()
self.logger.setLevel(logging.DEBUG)
# UI components
self.imageWidgets = [
self.imageOneOrigin, self.imageTwoOrigin, self.imageOneMods,
self.imageTwoMods, self.output1, self.output2
]
self.sliders = [self.slider1, self.slider2]
self.showCmbxs = [self.image1Cmbx, self.image2Cmbx]
self.mixerCmbxs = [self.mixerCmbx1, self.mixerCmbx2]
self.componentCmbxs = [self.component1, self.component2]
self.loadbtns = [self.img1Load, self.img2Load]
# loop settings
# imageView settings
for img in self.imageWidgets:
img.ui.histogram.hide()
img.ui.roiBtn.hide()
img.ui.menuBtn.hide()
img.ui.roiPlot.hide()
img.view.setBackgroundColor([255.0, 255.0, 255.0])
# buttons settings
for btn in self.loadbtns:
btn.clicked.connect(partial(self.loadImage, btn.property('image')))
for bx in self.showCmbxs:
bx.activated.connect(
partial(self.selectComponents, bx.property('image')))
self.mixerOutput.currentTextChanged.connect(self.chosenOutput)
for index, mxrbx in enumerate(self.mixerCmbxs):
mxrbx.currentTextChanged.connect(self.chosenOutput)
mxrbx.currentTextChanged.connect(self.setComponents)
for index, component in enumerate(self.componentCmbxs):
component.currentTextChanged.connect(self.chosenOutput)
for index, slider in enumerate(self.sliders):
slider.valueChanged.connect(self.chosenOutput)
def main(arg):
hostname = arg['-s']
version = arg['-v']
password = arg['-p']
username = arg['-u']
vm = arg["--vm"]
logfile_name = 'Image_firstnet_provision_patch_%s.log' % hostname
fp, out, err, log = cf.logfile_name_gen_open(logfile_name)
image.cleanup(hostname, username, password)
sys.stdout.flush()
time.sleep(300)
print "Will image the host %s" % hostname
sys.stdout.flush()
image.image(hostname, version, vm)
ips = configure_firstnet.configure_firstnet(hostname, version, vm)
print "Finish configure firstnet, you can use the following ip to configure:"
print ips
sys.stdout.flush()
if not configure_firstnet.is_dcs(hostname, version):
print "This host is OAK stack, please continue to deploy to %s manually!" % (
hostname, version)
sys.stdout.flush()
else:
print "Will do the provision and patch to latest version!"
sys.stdout.flush()
host = oda_lib.Oda_ha(ips[0], "root", "welcome1")
d_p_p.provision_patch(host)
sys.stdout.flush()
cf.closefile(fp, out, err)
print "Done, please check the log %s for details!" % log
def __init__(self, parent=None):
super(MyWidget, self).__init__(parent)
self.setupUi(self)
self.beach_dir = ""
self.forest_dir = ""
self.d = weights.data("weights")
self.ow, self.oh, self.inpf, self.inpb, self.w, self.m = self.d.load()
if self.ow == -1:
QtGui.QMessageBox.about(self, "ERROR", "error in weights file")
exit(0)
self.s = som.som(self.ow * self.oh * 3, self.inpf + self.inpb, 0.01)
self.s.init()
print self.ow * self.oh * 3 * (self.inpf + self.inpb), " ", len(self.m)
self.s.put_weights(self.w, self.m)
self.img1 = image.image(self.ow, self.oh)
self.img2 = image.image(self.ow, self.oh)
self.text = ""
self.f_dir = ""
self.b_dir = ""
self.timer = QtCore.QTimer()
self.timer.setInterval(1000)
self.timer.timeout.connect(self.re_write)
self.timer.start()
self.start.clicked.connect(self.start_func)
self.open_b.clicked.connect(self.open_b_dir)
self.open_f.clicked.connect(self.open_f_dir)
self.run = False
def append_tags(imagepath, width, height, title, url, query, result):
tags = list()
# add query
tags.append(query)
# add attribute from face++
tags.append(get_zn_from_dict(std_format(result['age']['value'])))
if result['race']['confidence'] > 80:
tags.append(get_zn_from_dict(std_format(result['race']['value'])))
if result['gender']['confidence'] > 80:
tags.append(get_zn_from_dict(std_format(result['gender']['value'])))
if result['smiling']['value'] > 60:
tags.append(get_zn_from_dict(std_format('smile')))
# parser title and add to tags
title_tag_list = text2word_list(title)
for t in title_tag_list:
tags.append(t)
# remove repeated elements
tags = list(set(tags))
# save img to mongodb
if title_tag_list.__len__() > 20:
img = image(imagepath, query, url, width, height, tags)
else:
img = image(imagepath, title, url, width, height, tags)
img.save()
# save tags info
updateTags(tags, imagepath)
return
def initiate():
fixedNumber = ""
print request.form['number']
print "A"
print request.values.get('number')
for elem in request.values.get('number'):
if elem.isnumeric():
fixedNumber = fixedNumber + str(elem)
print "B"
if len(fixedNumber) == 10:
fixedNumber = "+1" + fixedNumber
elif len(fixedNumber) == 11:
fixedNumber = "+" + fixedNumber
print "C"
r = Record(fixedNumber, request.values.get("image"))
phones = Record.query.filter_by(phone=fixedNumber).all()
print "D"
if phones == None:
db.session.add(r)
db.session.commit()
else:
pass
print "E"
image(fixedNumber, request.values.get("image"))
client = TwilioRestClient(twilio_account_sid, twilio_auth_token)
message = client.messages.create(to=fixedNumber, from_=twilio_number, body="Hey! Want to HEAR what your PICTURE looks like? Send \"yes\" to this SMS!")
return "None"
def generateFresh(self):
after = self.request.args.get('after')
if after is None:
msg = None
if g.user:
msg = Database.query(
'''select image from uploads ul
where (select score from imagescores where image=ul.image) < ?
and ul.image not in (select image from likes where userid=?)
order by (select score from imagescores where image=ul.image)
limit ?''', [
config.get('freshCeil'), session['userid'],
config.get('perPage')
])
else:
msg = Database.query(
'''select image from uploads ul
where (select score from imagescores where image=ul.image) < ?
order by (select score from imagescores where image=ul.image)
limit ?''',
[config.get('freshCeil'),
config.get('perPage')])
l = [image(f['image']) for f in msg]
return l
score = Database.query('select score from imagescores where image=?',
[after],
one=True)['score']
if g.user:
msg = Database.query(
'''select caption, image, image_url from uploads ul
where (select score from imagescores where image=ul.image) < ?
and (select score from imagescores where image=ul.image) < ?
and ul.image not in (select image from likes where userid=?)
order by (select score from imagescores where image=ul.image)
limit ?''', [
config.get('freshCeil'), score, session['userid'],
config.get('perPage')
])
else:
msg = Database.query(
'''select caption, image, image_url from uploads ul
where (select score from imagescores where image=ul.image) < ?
and (select score from imagescores where image=ul.image) < ?
order by (select score from imagescores where image=ul.image)
limit ?''',
[config.get('freshCeil'), score,
config.get('perPage')])
l = [image(f['image']) for f in msg]
return msg
def setType(self, type):
#Delete old panels
for i in self.GetChildren():
if i.GetName() in ["imagePanel", "customPanel", "colorPanel", "rotationPanel", "textPanel", "vartextPanel"]:
i.Destroy()
if type == "color":
self.color = color(self)
self.customSizer.Add(self.color, 1, wx.EXPAND|wx.ALL, 4)
if type == "image":
self.image = image(self)
self.customSizer.Add(self.image, 1, wx.EXPAND|wx.ALL, 4)
if type == "text":
self.rotation = rotation(self)
self.customSizer.Add(self.rotation, 0, wx.EXPAND|wx.ALL, 4)
self.text = text(self)
self.customSizer.Add(self.text, 1, wx.EXPAND|wx.ALL, 4)
if type == "vartext":
self.rotation = rotation(self)
self.customSizer.Add(self.rotation, 0, wx.EXPAND|wx.ALL, 4)
self.vartext = vartext(self)
self.customSizer.Add(self.vartext, 1, wx.EXPAND|wx.ALL, 4)
self.SetSizerAndFit(self.sizer)
self.Layout()
self.parent.Layout()
self.parent.propertiesPanel.Layout()
def imread(imageFile, dimension=None, fileFormat='', crop=None, module=''):
newImage = image.image(imageFile,
dimension=dimension,
fileFormat=fileFormat,
crop=crop,
module=module)
return newImage
def setType(self, type):
#Delete old panels
for i in self.GetChildren():
if i.GetName() in [
"imagePanel", "customPanel", "colorPanel", "rotationPanel",
"textPanel", "vartextPanel"
]:
i.Destroy()
if type == "color":
self.color = color(self)
self.customSizer.Add(self.color, 1, wx.EXPAND | wx.ALL, 4)
if type == "image":
self.image = image(self)
self.customSizer.Add(self.image, 1, wx.EXPAND | wx.ALL, 4)
if type == "text":
self.rotation = rotation(self)
self.customSizer.Add(self.rotation, 0, wx.EXPAND | wx.ALL, 4)
self.text = text(self)
self.customSizer.Add(self.text, 1, wx.EXPAND | wx.ALL, 4)
if type == "vartext":
self.rotation = rotation(self)
self.customSizer.Add(self.rotation, 0, wx.EXPAND | wx.ALL, 4)
self.vartext = vartext(self)
self.customSizer.Add(self.vartext, 1, wx.EXPAND | wx.ALL, 4)
self.SetSizerAndFit(self.sizer)
self.Layout()
self.parent.Layout()
self.parent.propertiesPanel.Layout()
def __createFeed(self, hot, recs):
if hot == []:
l = [f for f in recs]
random.shuffle(l)
random.shuffle(l)
return [image(f) for f in l]
a = set()
lHot = hot[-1]
hot = hot[:-1]
[a.add(f.permID) for f in hot]
[a.add(f.permID) for f in recs]
l = [f for f in a]
random.shuffle(l)
random.shuffle(l)
l = [image(f) for f in l]
l.append(lHot)
return l
def __init__(self,rootdir="caltech",dirlist=None):
self.categories = list(set(dirlist))
self.imgs = {}
for i in self.categories:
tmplist = []
for j in glob.glob(rootdir + "/" + i + "/*.jpg"):
tmplist.append(im.image(j,i))
self.imgs[i] = c.copy(tmplist)
def openfn(self):
dir_path = filedialog.askdirectory()
self.img_index = 0
self.images = [
image(imgPath, self.master)
for imgPath in glob(os.path.join(dir_path, '*.png'))
]
self.drawImage()
def fileOpen(self):
self.openFile = tkFileDialog.askopenfilename(filetypes=(('TARGA Image',
'*.tga'), ))
if self.openFile:
TGA = image(self.openFile)
self.fnLabel.config(state=NORMAL)
self.fnLabel.delete('1.0', END)
self.fnLabel.insert('1.0', self.openFile)
self.fnLabel.config(state=DISABLED)
def parse_image(self, path):
pathes = [
path + global_vars.split + f
for f in os.listdir(path)
if os.path.isfile(path + global_vars.split + f)
and os.path.splitext(f)[1] in global_vars.image_valid_extension
]
images = [image(p) for p in pathes]
return images
def accum_mean(self, source, num_channel, out_size):
print 'Loading mean', source
frame_num = self._get_frame_num(source)
self.count += frame_num
for c in range(num_channel):
for i in range(frame_num):
image_name = os.path.join(source, 'ch%i_%i_image.jpg' % (c, i))
self.image_sums['ch%i_image' % (c,)] += \
image(image_name).load(out_size, out_size)
def setup(directory):
mslist = [ name for name in os.listdir(directory) if os.path.isdir(os.path.join(directory, name)) ] #gathers all the ms subdirectories in mlist
images = []
for d in mslist:
images.append(image.image(d, directory +"/" + d)) #formats mlist
return images
images = imagearray.imageArray(directory)
return images
def __init__(self,imagecsvs=None):
if imagecsvs is not None:
rawfile = pd.read_csv(imagecsvs)
self.categories = list(set(rawfile['category'].tolist()))
self.imgs = {}
for i in self.categories:
tmplist = []
for j in rawfile[rawfile['category'] == i]['paths'].tolist():
tmplist.append(im.image(j,i))
self.imgs[i] = c.copy(tmplist)
def openImages(imgRange, imgDir, imgParams, imgSet):
images = []
for i in imgRange:
images.append(
im.image(imgDir[imgSet]['dir'] + str(i) + imgDir[imgSet]['ext'],
imgParams))
return images
def predict_and_visualize2(self,img,newimg):
dummyimg = image.image("dummyimage.jpg","None")
dummyimg2 = image.image("dummyimage2.jpg","None")
dummyimg3 = image.image("dummyimage3.jpg","None")
dummyimg4 = image.image("dummyimage4.jpg","None")
if img.data.shape[0] > 600:
b = img.data.shape[1]*600/img.data.shape[0]
img.data = cv2.resize(img.data,(b,600))
self.getDescriptors([dummyimg, dummyimg2, img, dummyimg3, dummyimg4])
if self.pca_before_kmeans is True:
self.PCA_test()
self.KMeans_test()
else:
self.KMeans_test()
self.PCA_test()
prediction = self.predict()
ptext = prediction[2]
cv2.namedWindow("Result", cv2.WINDOW_NORMAL)
pt = (0,3*img.data.shape[0] // 4)
cv2.putText(img.data, ptext, pt, cv2.FONT_HERSHEY_SCRIPT_COMPLEX,2, [0, 255, 0], 2)
cv2.imwrite(newimg,img.data)
def load_image(filename, label):
pic_size = (28, 28)
img = image.image(filename)
img.resize(pic_size)
data = []
width, height = (pic_size)
for y in range(height):
for x in range(width):
p = img.img.getpixel((x, y))
data.append(p[0] * 0.2989 + p[1] * 0.5870 + p[2] * 0.1140)
return (np.array(data), label)
def load_image(filename, label):
pic_size = (28, 28)
img = image.image(filename)
img.resize(pic_size)
data = []
width, height = (pic_size)
for y in range(height):
for x in range(width):
p = img.img.getpixel((x, y))
data.append(p[0] * 0.2989 + p[1] * 0.5870 + p[2] * 0.1140)
return (np.array(data), label)
def load_tledata(dirs,nprims,masks,pps,yn,vn):
retval = {}
for nprim,dirr in zip(nprims,dirs):
fyn = mkpath(dirr,yn)
fvn = mkpath(dirr,vn)
# if not os.path.isfile(fyn) or not os.path.isfile(fvn):
# fyn = mkpath(dirr,yn[:-4]+'10.mhd')
# fvn = mkpath(dirr,vn[:-4]+'10.mhd')
imagey = image.image(fyn,pps=pps,nprim=nprim,type='yield')
imagev = image.image(fvn,pps=pps,nprim=nprim,type='var')
imagey.applymask(*masks)
imagev.applymask(*masks)
#imagev.divide(10) #divide variance by number of jobs in batch)
#print "assuming 10 jobs in batch..."
retval[nprim] = {}
retval[nprim]['yield'] = imagey
retval[nprim]['var'] = imagev
return retval
def load_tledata(dirs, nprims, masks, pps, yn, vn):
retval = {}
for nprim, dirr in zip(nprims, dirs):
fyn = mkpath(dirr, yn)
fvn = mkpath(dirr, vn)
# if not os.path.isfile(fyn) or not os.path.isfile(fvn):
# fyn = mkpath(dirr,yn[:-4]+'10.mhd')
# fvn = mkpath(dirr,vn[:-4]+'10.mhd')
imagey = image.image(fyn, pps=pps, nprim=nprim, type='yield')
imagev = image.image(fvn, pps=pps, nprim=nprim, type='var')
imagey.applymask(*masks)
imagev.applymask(*masks)
#imagev.divide(10) #divide variance by number of jobs in batch)
#print "assuming 10 jobs in batch..."
retval[nprim] = {}
retval[nprim]['yield'] = imagey
retval[nprim]['var'] = imagev
return retval
async def on_message(ctx):
# If the message starts with a command
# Add more if-statements when more commands are added
if ctx.content.startswith('.sanders'):
# Remomving prefix
msg = ctx.content.replace(".sanders", "").strip()
# If nothing else is after the prefix (just ".sokkafy")
if len(msg) == 0:
await ctx.channel.send("Make sure to enter a valid string after `.sokkafy`! For example, `.sokkafy please stop`")
return
# If the text goes out of the permitted space in the image
elif len(msg) > 27:
await ctx.channel.send("Make sure that your string is under 28 characters!")
return
# Getting the avatar url of the message sender
url = str(ctx.author.avatar_url).replace("1024", "256")
print(url)
# Using the name
filename = url.split('/')[-1].split("?")[0].replace("webp", "jpg")
# Downloading image
img_data = requests.get(url).content
with open(f'pfps/{filename}.jpg', 'wb') as handler:
handler.write(img_data)
handler.close()
# Resetting the sokka object by redefining it
sokka = image("pls.jpg")
# Settings the self.txt variable to the value of the message
sokka.set_txt(msg)
# Pasting profile picture
sokka.paste(filename)
# Writing to the image
sokka.write()
# Saving to /downloaded
name = sokka.save()
# Getting file to send from /downloaded directory
to_send = discord.File(f"downloaded/{name}.jpg")
# Sending image
await ctx.channel.send(file=to_send)
# Deleteing image from /downloaded
os.remove(f"downloaded/{name}.jpg")
# Deleting pfp image from /pfps
os.remove(f"pfps/{filename}.jpg")
def scrapeImages():
"""
Main entry point to scrape images off the given subreddit
"""
listings = redditConnection.get_subreddit(subreddit).get_hot(limit=count)
for idx, submission in enumerate(listings):
uprint('#'+ str(idx + 1) + ' getting: ' + submission.url[:35] + ' titled: ' + submission.title[:25])
data = image(submission.title, submission.url)
if data.imageType != FILE_TYPES[0] and data.imageType != FILE_TYPES[1]:
print('^ERROR! Could not download the file. No proper extension was given^')
continue
path = TOP_FOLDER + '\\' + data.folderName
os.makedirs(path, exist_ok=True)
if not os.path.isfile(path + '\\' + data.fileName):
urllib.request.urlretrieve(data.url, TOP_FOLDER + '\\' + data.folderName+'\\'+data.fileName)
def __getImagesFromUsers(self, userList):
unlikedImages = set()
userLikes = Database.query('select image from likes where userid=?', [ self.userID ])
userSet = set()
[userSet.add(f['image']) for f in userLikes]
for user in userList:
otherLikesQuery = Database.query('select image from likes where userid=?', [ user.userID ])
otherLikes = [f['image'] for f in otherLikesQuery]
difLikes = [x for x in otherLikes if x not in userSet]
[unlikedImages.add(f) for f in difLikes]
unlikedImages = [image(f) for f in unlikedImages]
imageWeights = [(f, self.__distance(f) ) for f in unlikedImages]
imageWeights = sorted(imageWeights, key=itemgetter(1))
return [ f[0] for f in imageWeights ]
def __init__(self, parent=None):
super(MyWidget, self).__init__(parent)
self.setupUi(self)
self.ow = 80
self.oh = 60
self.d = weights.data("weights")
self.img = image.image(self.ow, self.oh)
self.timer = QtCore.QTimer()
self.timer.setInterval(1500)
self.timer.timeout.connect(self.re_write)
self.timer.start()
self.start.clicked.connect(self.start_func)
self.b_open.clicked.connect(self.open_b)
self.f_open.clicked.connect(self.open_f)
self.run = False
def main():
paths = find_images()
height = 600
width = 600
window = pygame.display.set_mode((width, height))
running = True
while running:
for event in pygame.event.get():
if event.type == pygame.QUIT:
running = False
img = image.image(choice(paths))
img.scale(width, height)
img.random_filter()()
window.fill((255, 255, 255))
window.blit(img.get_surface(), (0, 0))
pygame.display.update()
pygame.time.wait(2000)
def loadASCII(filePath):
img = image.image()
img.data = np.loadtxt(filePath)
with open(filePath, 'r') as f:
line = f.readline()
if len(line) >= 8:
if line[2:7] != 'ASCII':
raise Exception('Not an ASCII image file from medImgProc.')
else:
raise Exception('Not an ASCII image file from medImgProc.')
while line[2:-1] != 'ENDOFPROPERTIES':
if len(line) >= 11:
if line[2:10] == 'dtype = ':
if line[10:-1] == 'None':
img.dtype = None
else:
img.dtype = line[10:-1]
elif line[2:8] == 'dim = ':
if line[8:-1] == 'None':
img.dim = None
else:
img.dim = line[9:-2].split(',')
elif line[2:11] == 'dimlen = ':
if line[11:-1] == 'None':
img.dimlen = None
else:
dimlenstr = line[12:-2].split(',')
img.dimlen = {}
for n in range(len(dimlenstr)):
dimlenstrsplit = dimlenstr[n].split(':')
img.dimlen[dimlenstrsplit[0]] = float(
dimlenstrsplit[1])
elif line[2:10] == 'shape = ':
if line[10:-1] != 'None':
shape = tuple(map(int, line[11:-2].split(',')))
img.data = img.data.reshape(shape, order='F')
line = f.readline()
if img.data is not None and img.dtype is not None:
datamin, datamax = image.datatypeMinMax(np.dtype(img.dtype))
img.data = np.maximum(datamin, np.minimum(datamax,
img.data)).astype(img.dtype)
return img
def process(options):
dbfile = options.dbfile
overwrite = options.overwrite
resfile = os.path.splitext(dbfile)[0] + '.txt'
if overwrite:
if os.path.exists(resfile):
logger.info('%s exists. overwrite', resfile)
else:
if os.path.exists(resfile):
logger.info('%s exists. skip', resfile)
return
img = image.image(dbfile)
conn = sqlite3.connect(dbfile)
conn.text_factory = str
cursor = conn.execute(
"SELECT user_id, image_id, submit_time, suggested_sentence, rank, submitted_sentence, submitted_label, real_image_id FROM STATE"
)
fw = open(resfile, 'w')
img_list = []
user_list = []
for row in cursor:
user_list.append(row[0])
#image_id = row[7] #img.getimagename(row[1])
image_id = img.getimagename(row[1])
submit_time = row[2]
suggested_sentence = row[3]
rank = row[4]
submitted_sentence = row[5]
submitted_label = row[6]
fw.write('%s\t%s\t%s\t%s\n' %
(image_id, row[0], submitted_sentence, submitted_label))
img_list.append(image_id)
fw.close()
logger.info('Number of annotations: %d', len(img_list))
logger.info('Number of images: %d', len(set(img_list)))
logger.info('Number of users: %d', len(set(user_list)))
def get_sentence(self, user_id, page):
data = []
img = image.image(self.db_file)
conn = sqlite3.connect(self.db_file)
conn.text_factory = str
cursor = conn.execute("SELECT count(image_id) FROM STATE WHERE user_id=%d" % user_id)
for row in cursor:
count = row[0]
if (page - 1) * PAGE_LIMIT > count:
return False, None, None
cursor = conn.execute("SELECT user_id, image_id, submit_time, suggested_sentence, rank, submitted_sentence, submitted_label FROM STATE \
WHERE user_id = %d ORDER BY submit_time DESC LIMIT %d OFFSET %d" % (
user_id, PAGE_LIMIT, (page - 1) * PAGE_LIMIT))
import userControl as u
user_control = u.user(self.db_file)
for row in cursor:
image_id = row[1]
#import userControl as u
#user_control = u.user(self.db_file)
j, iid, image_id = user_control.getimageid(user_id, image_id)
url = IMAGE_ROOT + img.getimagename(iid)
submit_time = row[2]
suggested_sentence = row[3]
rank = row[4]
submitted_sentence = row[5]
submitted_label = row[6]
set = {'image_id': image_id, 'url': url, 'submit_time': submit_time,
'suggested_sentence': suggested_sentence.encode('gbk'), 'rank': rank,
'submitted_sentence': submitted_sentence.encode('gbk'),
'submitted_label': submitted_label}
data = data + [set]
conn.close()
import math
return True, data, math.ceil(float(count) / PAGE_LIMIT)
def loadmat(fileName, arrayName='', dim=[], dimlen={}, dtype=None):
newImage = image.image()
try:
matVariables = sio.loadmat(fileName)
if not (arrayName):
for key in matVariables:
if type(matVariables[key]) == np.ndarray:
newImage.data = matVariables[key]
break
else:
print('Error Loading matlab file.')
return
except NotImplementedError:
import h5py
matVariables = h5py.File(fileName)
if not (arrayName):
for key in matVariables:
print(type(matVariables[key].value))
if type(matVariables[key].value) == np.ndarray:
newImage.data = matVariables[key].value
break
else:
print('Error Loading matlab file.')
return
if len(dim) != len(newImage.data.shape):
newImage.dim = image.DEFAULT_SEGMENTATION_DIMENSION[-len(newImage.data.
shape):]
else:
newImage.dim = dim[:]
newImage.dimlen = dict(dimlen)
if len(newImage.dim) != len(newImage.dimlen):
for dimension in newImage.dim:
if dimension not in newImage.dimlen:
newImage.dimlen[dimension] = 1.
if dtype is None:
newImage.dtype = newImage.data.dtype
else:
newImage.data = newImage.data.astype(dtype)
newImage.dtype = dtype
return newImage
def make_gallery_from_coefficients(self,norm=False):
'''Creates a gallery of shapelets according to their coefficients
If Norm set to true, all shapelets plotted as if coefficients are unity'''
xmin = 0.0
xmax = self.n1*self.n2
ymin = xmin
ymax = xmax
nx = 100
ny = 100
array = np.zeros((nx,ny))
image = im.image(array, xmin,xmax,ymin,ymax)
image.array[:,:] =0.0
for ni in range(self.n1):
for nj in range(self.n2):
shape = self.create_shapelet(ni, nj)
shape.add_to_image(image, offsetx = ni, offsety = nj)
return image
yn = 'mean3d.mhd' #yieldname
vn = 'var3d.mhd' #varname
yn4d = 'mean4d.mhd' #yieldname
vn4d = 'var4d.mhd' #varname
### tledata
tleprims = [1e3,1e4,1e5,1e6]
# tledirs = ['run.wzd0','run.Ex3U','run.NSYS','tle1M']
tledirs = ['tle1k','tle10k','tle100k','tle1M']
### analog
anprims = [1e6,1e7,1e8,1e9]
andirs = ['analog1M','analog10M','analog100M','analog1B']
### helpers, masks
mask90pc = image.image("analog1B/mean3d.mhd")
mask90pc.to90pcmask()
#mask90pc.save90pcmask()
maskbeam = image.image("mask-beamline/maskfile.mhd")
maskspect = image.image("mask-spect1-8/finalmask.mhd")
maskbox2 = image.image("mask-box2/phantom_Parodi_TNS_2005_52_3_modified.maskfile2.mhd")
maskbox8 = image.image("mask-box8/phantom_Parodi_TNS_2005_52_3_modified.maskfile8.mhd")
#worstcaseim = image.image("analog1B/var.mhd",pps=ppsanalog,nprim=1e9,type='var')
### init
tle3d = tle.load_tledata(tledirs,tleprims,[mask90pc],ppstle,yn,vn)
an3d = tle.load_tledata(andirs,anprims,[mask90pc],ppsan,yn,vn)
tle4d = tle.load_tledata(tledirs,tleprims,[mask90pc,maskspect],ppstle,yn4d,vn4d)
an4d = tle.load_tledata(andirs,anprims,[mask90pc,maskspect],ppsan,yn4d,vn4d)
tle4dbeam = tle.load_tledata(tledirs,tleprims,[mask90pc,maskbeam,maskspect],ppstle,yn4d,vn4d)
import image as im
import coefficients as c
import numpy as np
imagefile = raw_input("What is the image filename? ")
coeff_file = "coefficients_"+imagefile
n1 = input("What is the first index of the shapelet to subtract? ")
n2 = input("What is the second index of the shapelet to subtract? ")
n1 = int(n1)
n2 = int(n2)
# Define image and coefficient objects
inputimage = im.image(np.zeros((1,1)),0.0,0.0,0.0,0.0)
inputcoeff = c.coefficients(1.0,4.0)
# Load image
inputimage.load_image(imagefile)
# Load coefficients
inputcoeff.read_from_file(coeff_file)
# Define shapelet to subtract
shapelet = inputcoeff.create_shapelet(n1, n2)
#Subtract shapelet
shapelet.subtract_from_image(inputimage)
print "Image centroid after subtraction is ",inputimage.centroid()
import image as im
import coefficients as c
import numpy as np
inputfile = raw_input("What is the input filename? ")
nmax = input("What is the maximum order of decomposition? ")
sigmamin = input("Define minimum blur in physical units: ")
sigmamax = input("Define minimum blur in physical units: ")
nsigma = input("How many blurring evaluations? ")
# Read in image
print 'Reading in image from file',inputfile
initialimage = im.image(np.zeros((1,1)),0.0,0.0,0.0,0.0)
initialimage.load_image(inputfile)
dsigma = (sigmamax - sigmamin)/float(nsigma)
for i in range(nsigma):
sigma = sigmamin + i*dsigma
print 'Carrying out decomposition for sigma ', sigma
inputimage = initialimage.clone()
inputimage.gaussian_blur(sigma)
# Write this blurred image to file
blur_file = 'blur_'+str(sigma)+'_'+inputfile
inputimage.write_to_file(blur_file)
rtpfile = 'data/plan.txt'
doseimage = 'results.vF3d/dosespotid.2gy.mhd'
field = 2
geolayer = slice(-2, None)
#################################################################################
# CODE
orirtp = rtplan.rtplan([rtpfile], norm2nprim=False) #,MSWtoprotons=False)
MSW = []
for spot in orirtp.spots:
if spot[0] == 100 + field: #
MSW.append(spot)
spotim_ct = image.image(doseimage) #"results.vF3d/dosespotid.2gy.mhd")
ct = spotim_ct.imdata.reshape(spotim_ct.imdata.shape[::-1])
xhist = np.linspace(-150, 150, 76) #4mm voxels, endpoints
x = np.linspace(-148, 148, 75) #bincenters
#print x[0],x[1],x[-1],len(x)
#print xhist[0],xhist[1],xhist[-1],len(xhist)
falloffs = []
for spindex, spot in enumerate(ct):
crush = [0, 1, 1] #x
crush = crush[::-1]
#!/usr/bin/env python import sys,image im1 = image.image(sys.argv[-1]) im1.printpixel([0,76,6,21])
#!/usr/bin/env python
import image,argparse,numpy as np
parser = argparse.ArgumentParser(description='secret')
parser.add_argument('--ct')
parser.add_argument('--mask')
parser.add_argument('--frac')
args = parser.parse_args()
tmpval = -7389.
ctim = image.image(str(args.ct))
mskim = image.image(str(args.mask))
assert(ctim.imdata.shape == mskim.imdata.shape)
#binnen = np.ma.masked_where(mskim.imdata == 1., mskim.imdata)
#buiten = np.ma.masked_where(mskim2.imdata == 0., mskim2.imdata)
binnen = np.ma.masked_equal(mskim.imdata, 1.)
buiten = np.ma.masked_equal(mskim.imdata, 0.)
ct_mean = np.ma.masked_array(ctim.imdata, mask=buiten).mean() #daar waar pixel(buiten) = 1: negeer waarden.
#ct_mean = 0.
print 'Setting volume in mask to',ct_mean
print np.ma.masked_array(ctim.imdata, mask=binnen).mean()
ctim.imdata = np.ma.masked_array(ctim.imdata, mask=binnen).filled(ct_mean)
ctim.saveas('maskedtest')
#!/usr/bin/env python import image,numpy as np,rtplan,auger,pickle rtplan = rtplan.rtplan(['data/plan.txt'],norm2nprim=False)#,noproc=True) doseimage = 'output/new_dosespotid-ct.mhd' shifttolerance = 8 ################################################################################ im = image.image(doseimage) ct = im.imdata.reshape(im.imdata.shape[::-1]).squeeze() ct_xhist = np.linspace(-150,150,301) #2mm voxels, endpoints ct_x = np.linspace(-149.5,149.5,300) #bincenters falloffs = [] falloffs_valid = [] for spindex,spot in enumerate(ct): fop = auger.get_fop(ct_x,spot) falloffs.append(fop) #if shifttolerance: # ensure a shift calculated at 20% and 80% height within 1mm of shift computed at default 50% fop2 = auger.get_fop(ct_x,spot,threshold=0.2) fop8 = auger.get_fop(ct_x,spot,threshold=0.8) if np.isclose([fop2,fop8],fop,atol=float(shifttolerance)).all():
def detectAreaRatio(self, folder=None):
loadImg = LoadImages()
if folder == None:
folder = "../images/isolated_images/"
self.image_list = loadImg.load(folder)
# load the image and resize it to a smaller factor so that
# the shapes can be approximated better
index = 0
index_obj = 0
for img in self.image_list:
resized = imutils.resize(img, width=300)
ratio = img.shape[0] / float(resized.shape[0])
# convert the resized image to grayscale, blur it slightly,
# and threshold it
gray = cv2.cvtColor(resized, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
thresh = cv2.threshold(blurred, 60, 255, cv2.THRESH_BINARY)[1]
# find contours in the thresholded image and initialize the
# shape detector
cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)
sd = ShapeDetector()
# create image objects
img_obj = image(img)
img_obj.id = index
self.image_obj_list.append(img_obj)
# loop over the contours
for c in cnts:
#area = cv2.contourArea(c)
#print('area is:', area)
if cv2.contourArea(c) <= 200:
continue
# compute the center of the contour, then detect the name of the
# shape using only the contour
M = cv2.moments(c)
cX = 0
cY = 0
if M["m00"] != 0:
cX = int((M["m10"] / M["m00"]) * ratio)
cY = int((M["m01"] / M["m00"]) * ratio)
shape = sd.detect(c)
# multiply the contour (x, y)-coordinates by the resize ratio,
# then draw the contours and the name of the shape on the image
c = c.astype("float")
c *= ratio
c = c.astype("int")
cv2.drawContours(img, [c], -1, (0, 255, 0), 2)
#cv2.putText(img, shape, (cX, cY), cv2.FONT_HERSHEY_SIMPLEX,
# 0.5, (255, 255, 255), 2)
# Rotated Rectangle
rect = cv2.minAreaRect(c)
box = cv2.boxPoints(rect)
box = np.int0(box)
imgRotRect = cv2.drawContours(img, [box], 0, (0, 0, 255), 2)
# calculate the area
area_obj = cv2.contourArea(c)
area_box = self.findAreaRotRect(box)
# create dna_object
d_obj = dna_object()
d_obj.id = index_obj
d_obj.getAttributes(c, area_obj, area_box)
self.dna_object_list.append(d_obj)
r = d_obj.area_ratio
print("# ", index)
print("area obj: %.2f" % area_obj)
print("area box: %.2f" % area_box)
print("area ratio: %.2f" % r)
index_obj += 1
#cv2.imshow(str(index), imgRotRect)
#cv2.waitKey(0)
index += 1
count_line = 0
count_right_line = 0 # 行數且字數正確
count_wrong_line = 0 # 該頁行數錯誤
# del pages[0]
for page in pages:
print(page[0].split(".")[0]) # , right, "/", count_page
# print(page[1])
if page[1] == [] or len(page[0].split(".")) > 1 or page[0] not in files:
print("Not Exist!")
continue
# count_page += 1
# if count_page < 2642:
# continue
count_page += 1
p = image(
input_folder + "PDF_to_JPG" + "/" + page[0].split(".")[0] + '.jpg',
page[1])
# p = image("DD1379BX3000021-101.jpg")
p.pre_process()
p.new_Vertical()
img = p.new_CutWord()
for words in page[1]:
count_word += len(words)
count_line += len(page[1])
# print("切割行數： " + str(len(img)) + "/" + str(len(page[1])))
if len(page[1]) == len(img): # 行數正確
count = 0
for i in range(len(page[1])):
if len(page[1][i]) == len(img[i]):
count += 1
count_right_line += count
def rebuild_glyphs(self):
"""Recreate all glyphs to represent current state of text image."""
glyphs = []
indent = 0
linewrap = self.linewrap
px, py = self.pos
self.font.pygame_font.set_underline(self._underline)
self.font.pygame_font.set_italic(self._italic)
self.font.pygame_font.set_bold(self._bold)
skip = 0
num = 0
image_positions = {}
text = self.text
if self.font.images:
for s in self.font.images:
last = 0
while 1:
n = text.find(s, last)
if n >= 0:
image_positions[n] = s
last = n + len(s)
else:
break
if self.font.images and image_positions:
word = ""
indent = 0
downdent = 0
newh = 0
_w = 0
for i in text:
if skip:
skip -= 1
num += 1
continue
elif num in image_positions:
if word:
i = image.Image(
self.font.pygame_font.render(
word, True, (255, 255, 255)))
i.colorize = self.color
w, h = i.get_size()
if linewrap and indent and indent + w > linewrap:
if indent > _w:
_w = indent
indent = 0
downdent += newh
newh = h
newh = max((newh, h))
i.pos = (indent, downdent)
indent += w
word = ""
glyphs.append(i)
a = image_positions[num]
i = self.font.images[a].copy()
w, h = i.get_size()
if linewrap and indent and indent + w > linewrap:
if indent > _w:
_w = indent
indent = 0
downdent += newh
newh = h
newh = max((newh, h))
i.pos = (indent, downdent)
indent += w
glyphs.append(i)
skip = len(a) - 1
elif i == "\n":
if indent > _w:
_w = indent
indent = 0
downdent += newh
newh = 0
elif i == " " and linewrap and indent and (
indent + self.font.pygame_font.get_size(word + " ")[0]
> linewrap):
i = image.image(
self.font.pygame_font.render(word, True,
(255, 255, 255)))
i.colorize = self.color
i.pos = (indent, downdent)
w, h = i.get_size()
indent = 0
downdent += max((h, newh))
newh = 0
glyphs.append(i)
else:
word += i
num += 1
if word:
i = image.Image(
self.font.pygame_font.render(word, True, (255, 255, 255)))
i.colorize = self.color
w, h = i.get_size()
if linewrap and indent and indent + w > linewrap:
if indent > _w:
_w = indent
indent = 0
downdent += newh
newh = h
newh = max((newh, h))
i.pos = (indent, downdent)
indent += w
word = ""
glyphs.append(i)
if indent > _w:
_w = indent
if newh:
downdent += newh
else:
indent = 0
downdent = 0
newh = 0
_w = 0
for line in text.split("\n"):
_l = ""
for word in line.split(" "):
if linewrap and indent and (
indent +
self.font.pygame_font.size(_l + " " + word)[0] >
linewrap):
i = image.Image(
self.font.pygame_font.render(
_l, True, (255, 255, 255)))
i.colorize = self.color
x, y = i.get_size()
i.pos = (indent, downdent)
downdent += newh
newh = y
indent += x
if indent > _w:
_w = int(indent)
indent = 0
glyphs.append(i)
_l = word
else:
if _l:
_l += " " + word
else:
_l += word
i = image.Image(
self.font.pygame_font.render(_l, True, (255, 255, 255)))
i.colorize = self.color
x, y = i.get_size()
i.pos = (indent, downdent)
downdent += max((newh, y))
newh = 0
indent += x
if indent > _w:
_w = int(indent)
indent = 0
glyphs.append(i)
self.glyphs = glyphs
self.size = (_w, downdent)
if self._compiled:
self.compile()
self.font.pygame_font.set_underline(False)
self.font.pygame_font.set_italic(False)
self.font.pygame_font.set_bold(False)
def thread_func(self):
self.run = True
self.text = ""
self.text = "Loading Images ..."
self.img1 = image.image(self.ow, self.oh)
self.img2 = image.image(self.ow, self.oh)
self.nb = self.img1.get_all_images(self.b_dir)
self.nf = self.img2.get_all_images(self.f_dir)
self.text = self.text + " done !!!\n"
self.text = self.text + "\ncategory - beach"
self.text = self.text + "\n------------------\n"
miss1 = 0
for i in range(0, self.nb):
dataset = self.img1.get_data_set(i)
name = self.img1.get_name(i)
ct = int(self.s.find(dataset))
if ct < self.inpf:
cat = "forest"
miss1 = miss1 + 1
else:
ct = ct - self.inpf
cat = "beach"
self.text = self.text + "image " + name[0] + " = "
self.text = self.text + str(cat) + "\n"
self.text = self.text + "\nnumber of errors = " + str(miss1)
self.text = self.text + " total = " + str(self.nb) + "\n"
self.text = self.text + "\ncategory - forest"
self.text = self.text + "\n------------------\n"
miss2 = 0
for i in range(0, self.nf):
dataset = self.img2.get_data_set(i)
name = self.img2.get_name(i)
ct = int(self.s.find(dataset))
if ct < self.inpf:
cat = "forest"
else:
ct = ct - self.inpf
cat = "beach"
miss2 = miss2 + 1
self.text = self.text + "image " + name[0] + " = "
self.text = self.text + str(cat) + "\n"
self.text = self.text + "\nnumber of errors = " + str(miss2)
self.text = self.text + " total = " + str(self.nf) + "\n"
miss = miss1 + miss2
total = self.nb + self.nf
self.text = self.text + "\ntotal error = "
self.text = self.text + str(float(miss) / float(total))
self.text = self.text + "\n\n -----TESTING COMPLEATED----\n\n"
time.sleep(1)
self.run = False
#!/usr/bin/env python
import image,sys,numpy
infile = sys.argv[-1] #in goes mhd
print >> sys.stderr, 'Processing', infile
print "This tool will set all voxel to water (HU=0)."
img = image.image(infile)
img.towater()
img.saveas(".water")
def rebuild_glyphs(self):
"""Recreate all glyphs to represent current state of text image."""
glyphs = []
indent = 0
linewrap = self.linewrap
px, py = self.pos
self.font.pygame_font.set_underline(self._underline)
self.font.pygame_font.set_italic(self._italic)
self.font.pygame_font.set_bold(self._bold)
skip = 0
num = 0
image_positions = {}
text = self.text
if self.font.images:
for s in self.font.images:
last = 0
while 1:
n = text.find(s, last)
if n >= 0:
image_positions[n] = s
last = n + len(s)
else:
break
if self.font.images and image_positions:
word = ""
indent = 0
downdent = 0
newh = 0
_w = 0
for i in text:
if skip:
skip -= 1
num += 1
continue
elif num in image_positions:
if word:
i = image.Image(self.font.pygame_font.render(word, True, (255, 255, 255)))
i.colorize = self.color
w, h = i.get_size()
if linewrap and indent and indent + w > linewrap:
if indent > _w:
_w = indent
indent = 0
downdent += newh
newh = h
newh = max((newh, h))
i.pos = (indent, downdent)
indent += w
word = ""
glyphs.append(i)
a = image_positions[num]
i = self.font.images[a].copy()
w, h = i.get_size()
if linewrap and indent and indent + w > linewrap:
if indent > _w:
_w = indent
indent = 0
downdent += newh
newh = h
newh = max((newh, h))
i.pos = (indent, downdent)
indent += w
glyphs.append(i)
skip = len(a) - 1
elif i == "\n":
if indent > _w:
_w = indent
indent = 0
downdent += newh
newh = 0
elif (
i == " "
and linewrap
and indent
and (indent + self.font.pygame_font.get_size(word + " ")[0] > linewrap)
):
i = image.image(self.font.pygame_font.render(word, True, (255, 255, 255)))
i.colorize = self.color
i.pos = (indent, downdent)
w, h = i.get_size()
indent = 0
downdent += max((h, newh))
newh = 0
glyphs.append(i)
else:
word += i
num += 1
if word:
i = image.Image(self.font.pygame_font.render(word, True, (255, 255, 255)))
i.colorize = self.color
w, h = i.get_size()
if linewrap and indent and indent + w > linewrap:
if indent > _w:
_w = indent
indent = 0
downdent += newh
newh = h
newh = max((newh, h))
i.pos = (indent, downdent)
indent += w
word = ""
glyphs.append(i)
if indent > _w:
_w = indent
if newh:
downdent += newh
else:
indent = 0
downdent = 0
newh = 0
_w = 0
for line in text.split("\n"):
_l = ""
for word in line.split(" "):
if linewrap and indent and (indent + self.font.pygame_font.size(_l + " " + word)[0] > linewrap):
i = image.Image(self.font.pygame_font.render(_l, True, (255, 255, 255)))
i.colorize = self.color
x, y = i.get_size()
i.pos = (indent, downdent)
downdent += newh
newh = y
indent += x
if indent > _w:
_w = int(indent)
indent = 0
glyphs.append(i)
_l = word
else:
if _l:
_l += " " + word
else:
_l += word
i = image.Image(self.font.pygame_font.render(_l, True, (255, 255, 255)))
i.colorize = self.color
x, y = i.get_size()
i.pos = (indent, downdent)
downdent += max((newh, y))
newh = 0
indent += x
if indent > _w:
_w = int(indent)
indent = 0
glyphs.append(i)
self.glyphs = glyphs
self.size = (_w, downdent)
if self._compiled:
self.compile()
self.font.pygame_font.set_underline(False)
self.font.pygame_font.set_italic(False)
self.font.pygame_font.set_bold(False)
'std_dust_pixel_value': np.std(dust_pixels),
'percent_dust_pixels': dust_pixels.size / image.size
}
start = time.time()
np.seterr(all='ignore')
path, dirs, files = next(os.walk("PATH_TO_DIRECTORY_OF_IMAGES"))
print(f"Found {len(files)} files.")
a = []
for i, j in enumerate(files):
print(f"Processing file: {i+1} of {len(files)} - {j}", end="\r")
filedata = image(path + "\\" + j)
metadata = filedata.get_metadata()
quality = filedata.get_quality_indicators()
c4_cal_quality = quality['calibration_quality_flags'][:, 1]
c5_cal_quality = quality['calibration_quality_flags'][:, 2]
rad_to_temp_coeffs4 = [
metadata['ch_4_central_wavenumber'] / (10**3),
metadata['ch_4_constant_1'] / (10**5),
metadata['ch_4_constant_2'] / (10**6)
]
rad_to_temp_coeffs5 = [
metadata['ch_5_central_wavenumber'] / (10**3),
metadata['ch_5_constant_1'] / (10**5),
metadata['ch_5_constant_2'] / (10**6)
]
def do_image(self):
self.metadata()
from image import image
return image(), noduplicates()
def do_image(self):
from image import image
return image(), noduplicates()
def do_image(self):
from image import image
return image(), noduplicates()
def b_open_clicked(self):
filename = QFileDialog.getOpenFileName(
caption="Открыть изображение", filter="Файлы изображений (*.jpg)")
if filename != ('', ''):
self.im = image(filename[0])
self.output_image(self.im, 1)
def __init__(self, directory):
self.directory = directory
self.mslist = [ name for name in os.listdir(self.directory) if os.path.isdir(os.path.join(self.directory, name)) ]
self.images = []
for d in self.mslist:
self.images.append(image.image(d, directory + d))
#!/usr/bin/env python import image,sys if len(sys.argv) < 3: print "Supply an image and a mask." sys.exit() maskfile = sys.argv[-1] #mask infile = sys.argv[-2] #image print >> sys.stderr, 'Processing', infile, maskfile img = image.image(infile) msk = image.image(maskfile) img.applymask(msk) print img.getmean()
### params
ppsan1 = (72.0856+71.8095)/2
ppstle1 = (69.2312+67.7542)/2
ppsan2 = (72.2114+71.9978)/2
ppstle2 = (68.1091+69.5367)/2
ppsan5 = (72.2351+74.2769)/2
ppstle5 = (68.3652+69.5583)/2
# yn = 'mean3d.mhd' #yieldname
# vn = 'var3d.mhd' #varname
yn4d = 'mean4d.mhd' #yieldname
vn4d = 'var4d.mhd' #varname
### helpers, masks
# TODO make mask90pc for 1,5mm voxels
maskspect1 = image.image("vox/1mm1-8msk.mhd")
maskspect2 = image.image("mask-spect1-8/finalmask.mhd")
maskspect5 = image.image("vox/5mm1-8msk.mhd")
mask901 = image.image("vox/90pcmask1.mhd")
mask902 = image.image("analog1B/mean.90pcmask.mhd")
mask905 = image.image("vox/90pcmask5.mhd")
### init
tle1mm = tle.load_tledata(['vox/tle1mm'],[1e4],[mask901,maskspect1],ppstle1,yn4d,vn4d)
tle2mm = tle.load_tledata(['tle10k'],[1e4],[mask902,maskspect2],ppstle2,yn4d,vn4d)
tle5mm = tle.load_tledata(['vox/tle5mm'],[1e4],[mask905,maskspect5],ppstle5,yn4d,vn4d)
an1mm = tle.load_tledata(['vox/an1mm'],[1e7],[mask901,maskspect1],ppsan1,yn4d,vn4d)
an2mm = tle.load_tledata(['analog10M'],[1e7],[mask902,maskspect2],ppsan2,yn4d,vn4d)
an5mm = tle.load_tledata(['vox/an5mm'],[1e7],[mask905,maskspect5],ppsan5,yn4d,vn4d)
# to 3d
import ctypes, numpy as np, os, math, time
from os import path
import gpumcd, image
print('Start of program.')
sett = gpumcd.Settings("d:\\postdoc\\gpumcd_data")
print(sett.planSettings.goalSfom)
casedir = "d:\\postdoc\\analyses\\gpumcd_python"
ct_image = image.image(path.join(casedir, 'ct.xdr'))
ct_image.ct_to_hu(1000, 1)
ct_image.resample([3, 3, 3])
ct = gpumcd.CT(sett, ct_image) #for dicoms, dont set intercept,slope.
machfile = "d:/postdoc/gpumcd_data/machines/machine_van_sami/brentAgility.beamlets.gpumdt"
engine = gpumcd.Engine(sett, ct, machfile)
print('gpumcd init done.')
print(engine.lasterror())
start_time = time.time()
frame1size = 5
frame2size = 3
BeamFrames = gpumcd.make_c_array(gpumcd.BeamFrame, 2)
continue
newline=[x.strip() for x in newline.split('=')]
if 'ElapsedTime' in newline[0]:
runtime = newline[1]
dosephs = glob.glob(indir+"/**/epid-entry.root")[0] #1B doesnt have this, only without dash
doseim = glob.glob(indir+"/**/epiddose-Dose.mhd")[0]
doseuncim = glob.glob(indir+"/**/epiddose-Dose-Uncertainty.mhd")[0]
dosetleim = glob.glob(indir+"/**/epiddose-tle-Dose.mhd")[0]
dosetleuncim = glob.glob(indir+"/**/epiddose-tle-Dose-Uncertainty.mhd")[0]
#electronprod = glob.glob(indir+"/**/epid-entry.root")[0]
all = dump.get2D(dosephs,['X','Y'])
doseim_ = image.image(doseim,type='yield')
doseuncim_ = image.image(doseuncim,type='relunc')
doseuncim_.imdata = doseuncim_.imdata.squeeze()*100.
dosetleim_ = image.image(dosetleim,type='yield')
dosetleuncim_ = image.image(dosetleuncim,type='relunc')
dosetleuncim_.imdata = dosetleuncim_.imdata.squeeze()*100.
unc_axis = np.linspace(0,50,50)
f, ((ax1 ,ax2, ax3 ),(ax4, ax5, ax6))= plot.subplots(nrows=2, ncols=3, sharex=False, sharey=False)#,figsize=(28,10))
#f.subplots_adjust(hspace=.5)
#f.subplots_adjust(wspace=.5)
f.suptitle('Runtime: '+runtime+'s', fontsize=10)
ax1.set_title("PhS, X,Y")
#!/usr/bin/env python import image, sys infile = sys.argv[-1] #in goes mhd print >> sys.stderr, 'Processing', infile img = image.image(infile) img.savenormalize()
#!/usr/bin/env python
import plot, numpy as np,auger,image,rtplan
from scipy.ndimage.filters import gaussian_filter
###########################################################################################################
smooth_param = 8.5 #20 mm FWHM
volume_offset=-141.59+7.96#spot sources
##61
pgelay = image.image('data/ct/source-ct-LAYERID-elayspot61.mhd')
rppgelay = image.image('data/rpct/source-rpct-LAYERID-elayspot61.mhd')
pggeolay = image.image('data/ct/source-ct-LAYERID-geolayspot61.mhd')
rppggeolay = image.image('data/rpct/source-rpct-LAYERID-geolayspot61.mhd')
ctelay = image.image('../doseactortest/output/dose-ct-LAYERID-elayspot61-Dose.mhd')
rpctelay = image.image('../doseactortest/output/dose-rpct-LAYERID-elayspot61-Dose.mhd')
ctgeolay = image.image('../doseactortest/output/dose-ct-LAYERID-geolayspot61-Dose.mhd')
rpctgeolay = image.image('../doseactortest/output/dose-rpct-LAYERID-geolayspot61-Dose.mhd')
##40
#pgelay = image.image('data/ct/source-ct-LAYERID-elayspot61.mhd')
#rppgelay = image.image('data/rpct/source-rpct-LAYERID-elayspot61.mhd')
##pggeolay = image.image('data/ct/source-ct-LAYERID-geolayspot40.mhd')
##rppggeolay = image.image('data/rpct/source-rpct-LAYERID-geolayspot40.mhd')
#pggeolay = image.image('data/ct/source-ct-LAYERID-geolayspot40.mhd')
#rppggeolay = image.image('data/rpct/source-rpct-LAYERID-geolayspot40.mhd')
##29
#pgelay = image.image('data/ct/source-ct-LAYERID-elayspot29.mhd')
