Use multiprocessing to parallelize early tasks

Former-commit-id: 9beb0cc2e5
pull/1161/head
Seth Fitzsimmons 2016-09-30 02:42:10 -07:00
rodzic 75b0991cc1
commit cff1f6e75a
2 zmienionych plików z 70 dodań i 51 usunięć

Wyświetl plik

@ -1,12 +1,20 @@
import os
import ecto
from functools import partial
from multiprocessing import Pool
from opendm import context
from opendm import io
from opendm import types
from opendm import log
def make_odm_photo(force_focal, force_ccd, path_file):
return types.ODM_Photo(path_file,
force_focal,
force_ccd)
class ODMLoadDatasetCell(ecto.Cell):
def declare_params(self, params):
@ -49,13 +57,11 @@ class ODMLoadDatasetCell(ecto.Cell):
if files:
# create ODMPhoto list
photos = []
for f in files:
path_file = io.join_paths(images_dir, f)
photo = types.ODM_Photo(path_file,
self.params.force_focal,
self.params.force_ccd)
photos.append(photo)
path_files = [io.join_paths(images_dir, f) for f in files]
photos = Pool().map(
partial(make_odm_photo, self.params.force_focal, self.params.force_ccd),
path_files
)
log.ODM_INFO('Found %s usable images' % len(photos))
else:

Wyświetl plik

@ -2,12 +2,61 @@ import ecto
import cv2
import pyexiv2
from functools import partial
from multiprocessing import Pool
from opendm import log
from opendm import system
from opendm import io
from opendm import types
def resize(src_dir, target_dir, resize_to, rerun_cell, photo):
# define image paths
path_file = photo.path_file
new_path_file = io.join_paths(target_dir, photo.filename)
# set raw image path in case we want to rerun cell
if io.file_exists(new_path_file) and rerun_cell:
path_file = io.join_paths(src_dir, photo.filename)
if not io.file_exists(new_path_file) or rerun_cell:
# open and resize image with opencv
img = cv2.imread(path_file)
# compute new size
max_side = max(img.shape[0], img.shape[1])
if max_side <= resize_to:
log.ODM_WARNING('Resize Parameter is greater than the largest side of the image')
ratio = float(resize_to) / float(max_side)
img_r = cv2.resize(img, None, fx=ratio, fy=ratio)
# write image with opencv
cv2.imwrite(new_path_file, img_r)
# read metadata with pyexiv2
old_meta = pyexiv2.ImageMetadata(path_file)
new_meta = pyexiv2.ImageMetadata(new_path_file)
old_meta.read()
new_meta.read()
# copy metadata
old_meta.copy(new_meta)
# update metadata size
new_meta['Exif.Photo.PixelXDimension'] = img_r.shape[0]
new_meta['Exif.Photo.PixelYDimension'] = img_r.shape[1]
new_meta.write()
# update photos array with new values
photo.path_file = new_path_file
photo.width = img_r.shape[0]
photo.height = img_r.shape[1]
photo.update_focal()
# log message
log.ODM_DEBUG('Resized %s | dimensions: %s' %
(photo.filename, img_r.shape))
else:
# log message
log.ODM_WARNING('Already resized %s | dimensions: %s x %s' %
(photo.filename, photo.width, photo.height))
return photo
class ODMResizeCell(ecto.Cell):
def declare_params(self, params):
params.declare("resize_to", "resizes images by the largest side", 2400)
@ -51,49 +100,14 @@ class ODMResizeCell(ecto.Cell):
'resize' in args.rerun_from)
# loop over photos
for photo in photos:
# define image paths
path_file = photo.path_file
new_path_file = io.join_paths(tree.dataset_resize, photo.filename)
# set raw image path in case we want to rerun cell
if io.file_exists(new_path_file) and rerun_cell:
path_file = io.join_paths(tree.dataset_raw, photo.filename)
if not io.file_exists(new_path_file) or rerun_cell:
# open and resize image with opencv
img = cv2.imread(path_file)
# compute new size
max_side = max(img.shape[0], img.shape[1])
if max_side <= self.params.resize_to:
log.ODM_WARNING('Resize Parameter is greater than the largest side of the image')
ratio = float(self.params.resize_to) / float(max_side)
img_r = cv2.resize(img, None, fx=ratio, fy=ratio)
# write image with opencv
cv2.imwrite(new_path_file, img_r)
# read metadata with pyexiv2
old_meta = pyexiv2.ImageMetadata(path_file)
new_meta = pyexiv2.ImageMetadata(new_path_file)
old_meta.read()
new_meta.read()
# copy metadata
old_meta.copy(new_meta)
# update metadata size
new_meta['Exif.Photo.PixelXDimension'] = img_r.shape[0]
new_meta['Exif.Photo.PixelYDimension'] = img_r.shape[1]
new_meta.write()
# update photos array with new values
photo.path_file = new_path_file
photo.width = img_r.shape[0]
photo.height = img_r.shape[1]
photo.update_focal()
# log message
log.ODM_DEBUG('Resized %s | dimensions: %s' %
(photo.filename, img_r.shape))
else:
# log message
log.ODM_WARNING('Already resized %s | dimensions: %s x %s' %
(photo.filename, photo.width, photo.height))
photos = Pool().map(
partial(resize,
tree.dataset_raw,
tree.dataset_resize,
self.params.resize_to,
rerun_cell),
photos
)
log.ODM_INFO('Resized %s images' % len(photos))
@ -105,4 +119,3 @@ class ODMResizeCell(ecto.Cell):
log.ODM_INFO('Running ODM Resize Cell - Finished')
return ecto.OK if args.end_with != 'resize' else ecto.QUIT