def serve_mosaic_image(time_series=None, pid=None, params='/'):
"""Generate a mosaic of ROIs from a sample bin.
params include the following, with default values
- series (mvco) - time series (FIXME: handle with resolver, clarify difference between namespace, time series, pid, lid)
- size (1024x1024) - size of the mosaic image
- page (1) - page. for typical image sizes the entire bin does not fit and so is split into pages.
- scale - scaling factor for image dimensions """
# parse params
params = parse_params(params, size='1024x1024',page=1,scale=1.0)
(w,h) = tuple(map(int,re.split('x',params[SIZE])))
scale = float(params[SCALE])
page = int(params[PAGE])
# parse pid/lid
hit = pid_resolver.resolve(pid=pid)
# perform layout operation
scaled_size = (int(w/scale), int(h/scale))
layout = get_mosaic_layout(hit.bin_pid, scaled_size, page)
# serve JSON on request
if hit.extension == 'json':
return jsonr(list(layout2json(layout, scale)))
# resolve ROI file
roi_path = resolve_roi(hit.bin_pid)
# read all images needed for compositing and inject into Tiles
with open(roi_path,'rb') as roi_file:
for tile in layout:
target = tile.image
# FIXME use fast stitching
tile.image = as_pil(get_fast_stitched_roi(hit.bin_pid, target[TARGET_NUMBER]))
# produce and serve composite image
mosaic_image = thumbnail(mosaic.composite(layout, scaled_size, mode='L', bgcolor=160), (w,h))
(pil_format, mimetype) = image_types(hit)
return image_response(mosaic_image, pil_format, mimetype)
def serve_mosaic_image(time_series=None, pid=None, params='/'):
"""Generate a mosaic of ROIs from a sample bin.
params include the following, with default values
- series (mvco) - time series (FIXME: handle with resolver, clarify difference between namespace, time series, pid, lid)
- size (1024x1024) - size of the mosaic image
- page (1) - page. for typical image sizes the entire bin does not fit and so is split into pages.
- scale - scaling factor for image dimensions """
# parse params
size, scale, page = parse_mosaic_params(params)
(w,h) = size
parsed = parse_pid(pid)
schema_version = parsed['schema_version']
try:
paths = get_fileset(parsed)
except NotFound:
abort(404)
adc_path = paths['adc_path']
roi_path = paths['roi_path']
bin_pid = canonicalize(get_url_root(), time_series, parsed['bin_lid'])
# perform layout operation
scaled_size = (int(w/scale), int(h/scale))
layout = list(get_mosaic_layout(adc_path, schema_version, bin_pid, scaled_size, page))
extension = parsed['extension']
# serve JSON on request
if extension == 'json':
return Response(json.dumps(list(layout2json(layout, scale))), mimetype=MIME_JSON)
mimetype = mimetypes.types_map['.' + extension]
# read all images needed for compositing and inject into Tiles
image_layout = []
with open(roi_path,'rb') as roi_file:
for tile in layout:
target = tile.image # in mosaic API, the record is called 'image'
# FIXME 1. replace PIL
image = get_target_image(parsed, target, file=roi_file, raw_stitch=True)
image_layout.append(Tile(PIL.Image.fromarray(image), tile.size, tile.position))
# produce and serve composite image
mosaic_image = thumbnail(mosaic.composite(image_layout, scaled_size, mode='L', bgcolor=160), (w,h))
#pil_format = filename2format('foo.%s' % extension)
return Response(as_bytes(mosaic_image), mimetype=mimetype)
from oii.ifcb import client
from oii.image import mosaic
import os
import re
from PIL import Image
DIR='/Users/jfutrelle/Pictures'
def get_images():
for filename in os.listdir(DIR):
if re.match(r'.*\.png$',filename) or re.match(r'.*\.jpg$',filename):
file = os.path.join(DIR,filename)
image = Image.open(file)
if image.size[0] < 1024 and image.size[1] < 1024:
print 'including %s...' % filename
yield image
images = list(get_images())
print 'laying out...'
layout = list(mosaic.layout(images, (5000, 2400000)))
print layout
print 'compositing...'
m = mosaic.composite(layout,None,'RGB')
file='/Users/jfutrelle/Pictures/a_mosaic.jpg'
print 'saving as %s...' % file
m.save(file,'JPEG')
print 'done'
from oii.ifcb import client
from oii.image import mosaic
# blob mask mosaic from http://ifcb-data.whoi.edu/mvco/IFCB5_2011_339_111025
def get_blobs(pid,limit=None):
count = 0
for target in client.list_targets(pid):
count += 1
if limit is not None and count > limit:
return
blob = target+'_blob.png'
print 'fetching %s...' % blob
yield client.fetch_image(blob)
PID='http://ifcb-data.whoi.edu/mvco/IFCB5_2011_339_111025'
print('loading images from %s...' % PID)
images = get_blobs(PID,500)
print 'laying out...'
layout = list(mosaic.layout(images, (2400, 2400000)))
print 'compositing...'
m = mosaic.composite(layout)
file='/Users/jfutrelle/Pictures/blob_mosaic.png'
print 'saving as %s...' % file
m.save(file,'PNG')
