shuffle(ld)
numTrainEx = len(listdir(indir+"tempTrain/"))
trainImages = np.zeros((numTrainEx,timeSteps,1,wSize,wSize),dtype=np.float)
trainTargets = np.zeros((numTrainEx,outsize),dtype=np.float)
trainCIDs = []
added = 0 #keep track of how many images have been added
count = 0
while added < numTrainEx:
x = ld[count]
if x.find(".sdf") > -1:
try:
try:
CID = x[:x.find(".sdf")]
image = helperFuncs.processImage(CID,trainFolder,binarize,blur,padding,size,noise=True)
#mi.imsave("../evaluation/"+str(CID)+".jpg",image)
subprocess.call("rm "+trainFolder+x,shell=True)
image = im2window(image,wSize,stride)
trainImages[added,:,:,:,:] = image
trainTargets[added] = targets[CID]
trainCIDs.append(CID)
added+=1
print added
except (IOError,ValueError) as e:
print e
except (KeyError, ValueError) as e:
subprocess.call("rm "+trainFolder+x,shell=True) #This means this molecule was too big
count+=1
if count > len(ld)-1:
numTrainEx = len(listdir(indir+"tempTrain/"))
trainImages = np.zeros((numTrainEx,1,size,size),dtype=np.float)
trainTargets = np.zeros((numTrainEx,outsize),dtype=np.float)
trainCIDs = []
added = 0
count = 0
while added < numTrainEx:
x = ld[count]
print x, added
if x.find(".sdf") > -1:
try:
try:
CID = x[:x.find(".sdf")]
image = helperFuncs.processImage(CID,trainFolder,binarize,blur,padding,size,noise=True)
subprocess.call("rm "+trainFolder+x,shell=True)
trainImages[added,0,:,:] = image
trainTargets[added] = targets[CID]
trainCIDs.append(CID)
added+=1
except (IOError,ValueError) as e:
print e
except (KeyError, ValueError) as e:
subprocess.call("rm "+trainFolder+x,shell=True) #This means this molecule was too big
count+=1
if count > len(ld)-1:
count = 0
ld = listdir(trainFolder)
while len(ld) == 0:
print x
try:
CID = x
print "reading in"
image = io.imread("/home/test/usan/" + x, as_grey=True)
image = minusOnes(image)
print "numpying"
image = np.array(image)
#image = convertIt(image)
print "resizing"
print image.shape
image = helperFuncs.processImage(None,
"/",
True,
0.3,
"random",
300,
noise=True,
image=image)
# image = myResize(image,imdim)
#image = putInSize(image,imdim)
# image = np.where(image >0.05, 1.,0)
# image = filters.gaussian_filter(image,0.2)
# image = 0.05*np.random.rand(image.shape[0], image.shape[1]) + image
#image = filters.gaussian_filter(image,0.2)
#print "binarizing"
print image.shape
#image = np.where(image>0.2,1,0)
# for countzor in range(0,image.shape[0]):
ld = listdir("/home/test/usan/")
images = np.zeros((1,1,imdim,imdim),dtype=np.float)
for x in ld:
print x
try:
CID = x
print "reading in"
image = io.imread("/home/test/usan/"+x,as_grey=True)
image = minusOnes(image)
print "numpying"
image = np.array(image)
#image = convertIt(image)
print "resizing"
print image.shape
image = helperFuncs.processImage(None,"/",True,0.3,"random",300,noise=True,image=image)
# image = myResize(image,imdim)
#image = putInSize(image,imdim)
# image = np.where(image >0.05, 1.,0)
# image = filters.gaussian_filter(image,0.2)
# image = 0.05*np.random.rand(image.shape[0], image.shape[1]) + image
#image = filters.gaussian_filter(image,0.2)
#print "binarizing"
print image.shape
#image = np.where(image>0.2,1,0)
# for countzor in range(0,image.shape[0]):
# print image[countzor,:]
# stop=raw_input("")
#image = np.where(image > 0.1,1.0,0.0)