def readImage(filename):
if os.path.exists(filename):
log.status("reading from " + filename)
imageMemmap = array(Image.open(filename).convert("L"))
log.status("successfully read from" + filename)
try:
os.remove(".temp.raw")
finally:
return imageMemmap
else:
log.error("can't read from " + filename)
return None
def readImage(filename):
if os.path.exists(filename):
log.status("reading from " + filename)
first = misc.imread(filename)
first.tofile('.temp.raw')
imageMemmap = np.memmap('.temp.raw', dtype=np.uint8, shape=first.shape)
log.status("successfully read from" + filename)
try:
os.remove(".temp.raw")
finally:
return imageMemmap
else:
log.error("can't read from " + filename)
return None
import time, argparse, imageIO, log
from gauss import gaussian_blur
from sobel import edge_detector
from laplacian import sharpening
parser = argparse.ArgumentParser()
parser.add_argument('--blur', action='store_true')
parser.add_argument('--edge', action='store_true')
parser.add_argument('--sharp', action='store_true')
parser.add_argument("input_file", help="The input image file.")
parser.add_argument("output_file", help="The output image file.")
args = parser.parse_args()
img = imageIO.readImage(args.input_file)
if img is not None:
startTime = time.time()
log.status("proccessing image")
if args.blur:
blurImage = gaussian_blur(img)
imageIO.writeImage(blurImage, args.output_file)
elif args.edge:
edgeImage = edge_detector(img)
imageIO.writeImage(edgeImage, args.output_file)
elif args.sharp:
sharpImage = sharpening(img)
imageIO.writeImage(sharpImage, args.output_file)
def writeImage(imageMemmap,filename):
log.status("writing image to "+filename)
imageio.imwrite(filename, imageMemmap)
log.status("image successfully write to " + filename)
def _statusDaemon():
while _enabled and threading.currentThread().getName() == _threadName:
try:
activeUsers, waitingUsers, isPaused = ezid.getStatus()
na = sum(activeUsers.values())
nw = sum(waitingUsers.values())
ndo = datacite.numActiveOperations()
uql = ezidapp.models.UpdateQueue.objects.count()
bql = binder_async.getQueueLength()
daql = datacite_async.getQueueLength()
cqs = crossref.getQueueStatistics()
doql = download.getQueueLength()
as_ = search_util.numActiveSearches()
no = log.getOperationCount()
log.resetOperationCount()
log.status("pid=%d" % os.getpid(),
"threads=%d" % threading.activeCount(),
"paused" if isPaused else "running",
"activeOperations=%d%s" % (na, _formatUserCountList(activeUsers)),
"waitingRequests=%d%s" % (nw, _formatUserCountList(waitingUsers)),
"activeDataciteOperations=%d" % ndo,
"updateQueueLength=%d" % uql,
"binderQueueLength=%d" % bql,
"dataciteQueueLength=%d" % daql,
"crossrefQueue:archived/unsubmitted/submitted=%d/%d/%d" %\
(cqs[2]+cqs[3], cqs[0], cqs[1]),
"downloadQueueLength=%d" % doql,
"activeSearches=%d" % as_,
"operationCount=%d" % no)
if _cloudwatchEnabled:
import boto3
# Disable annoying boto3 logging.
logging.getLogger("botocore").setLevel(logging.ERROR)
try:
c = boto3.client("cloudwatch",
region_name=_cloudwatchRegion)
d = [{
"Name": "InstanceName",
"Value": _cloudwatchInstanceName
}]
data = {
"ActiveOperations": na,
"WaitingRequests": nw,
"ActiveDataciteOperations": ndo,
"UpdateQueueLength": uql,
"BinderQueueLength": bql,
"DataciteQueueLength": daql,
"CrossrefQueueLength": cqs[0] + cqs[1],
"DownloadQueueLength": doql,
"ActiveSearches": as_,
"OperationRate": float(no) / _reportingInterval
}
r = c.put_metric_data(Namespace=_cloudwatchNamespace,
MetricData=[{ "MetricName": k, "Dimensions": d, "Value": float(v),
"Unit": "Count/Second" if k == "OperationRate" else "Count" }\
for k, v in data.items()])
assert r["ResponseMetadata"]["HTTPStatusCode"] == 200
except:
# Ignore CloudWatch exceptions, as it's not essential.
pass
except Exception, e:
log.otherError("status._statusDaemon", e)
django.db.connections["default"].close()
time.sleep(_reportingInterval)
parser.add_argument('--grayscale', action='store_true')
parser.add_argument('--edge', action='store_true')
parser.add_argument('--color_filter', action='store_true')
parser.add_argument('--color',
help='red,green,blue,brown',
type=str,
default="red")
parser.add_argument("input_file", help="The input image file.")
parser.add_argument("output_file", help="The output image file.")
args = parser.parse_args()
img = imageIO.readImage(args.input_file)
if img is not None:
startTime = time.time()
log.status("proccessing image")
if args.blur:
blurImage = blur(img, args.sigma)
imageIO.writeImage(blurImage, args.output_file)
elif args.edge:
edgeImage = edgeDetection(img)
imageIO.writeImage(edgeImage, args.output_file)
elif args.invert_colors:
invertImage = basicFilters.invertColors(img)
imageIO.writeImage(invertImage, args.output_file)
elif args.grayscale:
grayscaleImage = basicFilters.grayscaleFilter(img)
imageIO.writeImage(grayscaleImage, args.output_file)
elif args.color_filter:
color = colors.getColor(args.color)
if color is not None: