Loading autocnet/matcher/subpixel.py +15 −3 Original line number Diff line number Diff line Loading @@ -450,6 +450,12 @@ def subpixel_register_point(pointid, iterative_phase_kwargs={}, subpixel_templat measure.sample = new_template_x measure.line = new_template_y measure.weight = cost # In case this is a second run, set the ignore to False if this # measures passed. Also, set the source measure back to ignore=False measure.ignore = False source.ignore = False session.commit() session.close() Loading Loading @@ -494,6 +500,7 @@ def cluster_subpixel_register_points(iterative_phase_kwargs={'size': 251}, subpixel_template_kwargs={'image_size':(251,251)}, cost_func=lambda x,y: 1/x**2 * y, threshold=0.005, filters = {}, walltime='00:10:00', chunksize=1000, exclude=None): Loading Loading @@ -521,7 +528,9 @@ def cluster_subpixel_register_points(iterative_phase_kwargs={'size': 251}, threshold : numeric measures with a cost <= the threshold are marked as ignore=True in the database. filters : dict with keys equal to attributes of the Points mapping and values equal to some criteria. exclude : str string containing the name(s) of any slurm nodes to exclude when completing a cluster job. (e.g.: 'gpu1' or 'gpu1,neb12') Loading @@ -534,9 +543,12 @@ def cluster_subpixel_register_points(iterative_phase_kwargs={'size': 251}, # Push the job messages onto the queue queuename = config['redis']['processing_queue'] session = Session() for i, point in enumerate(session.query(Points)): query = session.query(Points) for attr, value in filters.items(): query = query.filter(getattr(Points, attr)==value) res = query.all() for i, point in enumerate(res): msg = {'id' : point.id, 'iterative_phase_kwargs' : iterative_phase_kwargs, 'subpixel_template_kwargs' : subpixel_template_kwargs, Loading Loading
autocnet/matcher/subpixel.py +15 −3 Original line number Diff line number Diff line Loading @@ -450,6 +450,12 @@ def subpixel_register_point(pointid, iterative_phase_kwargs={}, subpixel_templat measure.sample = new_template_x measure.line = new_template_y measure.weight = cost # In case this is a second run, set the ignore to False if this # measures passed. Also, set the source measure back to ignore=False measure.ignore = False source.ignore = False session.commit() session.close() Loading Loading @@ -494,6 +500,7 @@ def cluster_subpixel_register_points(iterative_phase_kwargs={'size': 251}, subpixel_template_kwargs={'image_size':(251,251)}, cost_func=lambda x,y: 1/x**2 * y, threshold=0.005, filters = {}, walltime='00:10:00', chunksize=1000, exclude=None): Loading Loading @@ -521,7 +528,9 @@ def cluster_subpixel_register_points(iterative_phase_kwargs={'size': 251}, threshold : numeric measures with a cost <= the threshold are marked as ignore=True in the database. filters : dict with keys equal to attributes of the Points mapping and values equal to some criteria. exclude : str string containing the name(s) of any slurm nodes to exclude when completing a cluster job. (e.g.: 'gpu1' or 'gpu1,neb12') Loading @@ -534,9 +543,12 @@ def cluster_subpixel_register_points(iterative_phase_kwargs={'size': 251}, # Push the job messages onto the queue queuename = config['redis']['processing_queue'] session = Session() for i, point in enumerate(session.query(Points)): query = session.query(Points) for attr, value in filters.items(): query = query.filter(getattr(Points, attr)==value) res = query.all() for i, point in enumerate(res): msg = {'id' : point.id, 'iterative_phase_kwargs' : iterative_phase_kwargs, 'subpixel_template_kwargs' : subpixel_template_kwargs, Loading