kopia lustrzana https://github.com/OpenDroneMap/ODM
108 wiersze
4.0 KiB
Python
108 wiersze
4.0 KiB
Python
import ecto
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import cv2
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import pyexiv2
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from opendm import log
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from opendm import system
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from opendm import io
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from opendm import types
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class ODMResizeCell(ecto.Cell):
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def declare_params(self, params):
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params.declare("resize_to", "resizes images by the largest side", 2400)
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def declare_io(self, params, inputs, outputs):
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inputs.declare("tree", "Struct with paths", [])
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inputs.declare("args", "The application arguments.", [])
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inputs.declare("photos", "Clusters inputs. list of ODMPhoto's", [])
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outputs.declare("photos", "Clusters output. list of ODMPhoto's", [])
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def process(self, inputs, outputs):
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# Benchmarking
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start_time = system.now_raw()
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log.ODM_INFO('Running ODM Resize Cell')
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# get inputs
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args = self.inputs.args
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tree = self.inputs.tree
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photos = self.inputs.photos
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if not photos:
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log.ODM_ERROR('Not enough photos in photos to resize')
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return ecto.QUIT
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if self.params.resize_to <= 0:
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log.ODM_ERROR('Resize parameter must be greater than 0')
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return ecto.QUIT
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# create working directory
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system.mkdir_p(tree.dataset_resize)
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log.ODM_DEBUG('Resizing dataset to: %s' % tree.dataset_resize)
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# check if we rerun cell or not
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rerun_cell = (args.rerun is not None and
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args.rerun == 'resize') or \
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(args.rerun_all) or \
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(args.rerun_from is not None and
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'resize' in args.rerun_from)
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# loop over photos
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for photo in photos:
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# define image paths
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path_file = photo.path_file
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new_path_file = io.join_paths(tree.dataset_resize, photo.filename)
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# set raw image path in case we want to rerun cell
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if io.file_exists(new_path_file) and rerun_cell:
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path_file = io.join_paths(tree.dataset_raw, photo.filename)
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if not io.file_exists(new_path_file) or rerun_cell:
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# open and resize image with opencv
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img = cv2.imread(path_file)
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# compute new size
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max_side = max(img.shape[0], img.shape[1])
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if max_side <= self.params.resize_to:
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log.ODM_WARNING('Resize Parameter is greater than the largest side of the image')
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ratio = float(self.params.resize_to) / float(max_side)
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img_r = cv2.resize(img, None, fx=ratio, fy=ratio)
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# write image with opencv
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cv2.imwrite(new_path_file, img_r)
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# read metadata with pyexiv2
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old_meta = pyexiv2.ImageMetadata(path_file)
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new_meta = pyexiv2.ImageMetadata(new_path_file)
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old_meta.read()
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new_meta.read()
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# copy metadata
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old_meta.copy(new_meta)
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# update metadata size
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new_meta['Exif.Photo.PixelXDimension'].value = img_r.shape[0]
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new_meta['Exif.Photo.PixelYDimension'].value = img_r.shape[1]
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new_meta.write()
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# update photos array with new values
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photo.path_file = new_path_file
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photo.width = img_r.shape[0]
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photo.height = img_r.shape[1]
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photo.update_focal()
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# log message
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log.ODM_DEBUG('Resized %s | dimensions: %s' %
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(photo.filename, img_r.shape))
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else:
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# log message
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log.ODM_WARNING('Already resized %s | dimensions: %s x %s' %
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(photo.filename, photo.width, photo.height))
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log.ODM_INFO('Resized %s images' % len(photos))
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# append photos to cell output
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self.outputs.photos = photos
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if args.time:
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system.benchmark(start_time, tree.benchmarking, 'Resizing')
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log.ODM_INFO('Running ODM Resize Cell - Finished')
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return ecto.OK if args.end_with != 'resize' else ecto.QUIT
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