def load_rt_staff_removal():
task_class = RTStafflineRemovalTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(
job_name=task_class.name,
author="Deepanjan Roy",
description=
"Removes the staff lines usign Roach and Tatem Staffline removal algorithm.",
input_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": [
ONEBIT,
],
"name": "input"
},
output_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": [
ONEBIT,
],
"name": "output"
},
settings=task_class.settings,
enabled=True,
category="Staff Removal",
interactive=False)
j.save()
def load_dummy_job():
name = 'rodan.jobs.devel.dummy_job'
if not Job.objects.filter(job_name=name).exists():
j = Job(job_name=name,
author="Andrew Hankinson",
description=
"A Dummy Job for testing the Job loading and workflow system",
input_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (1, ),
"name": "input"
},
output_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (1, ),
"name": "output"
},
settings=[{}],
enabled=True,
category="Dummy",
interactive=False)
j.save()
def load_segmentation():
task_class = SegmentationTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(
job_name=task_class.name,
author="Deepanjan Roy",
description=
"Finds the staves using Miyao Staff Finder and masks out everything else.",
input_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (ONEBIT, ),
"name": "input"
},
output_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (ONEBIT, ),
"name": "output"
},
settings=task_class.settings,
enabled=True,
category="Segmentation",
interactive=True)
j.save()
def load_pitch_finder():
task_class = PitchFindingTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(
job_name=task_class.name,
author="Deepanjan Roy",
description=
"Classifies the neumes detected in the page using the classifier interface.",
input_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (GAMERA_XML, ),
"name": "input"
},
output_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (MEI, ),
"name": "output"
},
settings=task_class.settings,
enabled=True,
category="Pitch Finding",
interactive=False)
j.save()
def load_auto_border_removal():
task_class = AutoBorderRemovalTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(
job_name=task_class.name,
author="Deepanjan Roy",
description=
"Automatically tries to remove the border of a page. Non-interactive.",
input_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": [GREYSCALE, ONEBIT, RGB],
"name": "input"
},
output_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": [GREYSCALE, ONEBIT, RGB],
"name": "output"
},
settings=task_class.settings,
enabled=True,
category="Border Removal",
interactive=False)
j.save()
def load_crop_border_removal():
task_class = CropBorderRemovalTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(job_name=task_class.name,
author="Deepanjan Roy",
description=
"Manual masking crop. Uses the crop interface. Interactive.",
input_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": [GREYSCALE, ONEBIT, RGB],
"name": "input"
},
output_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": [GREYSCALE, ONEBIT, RGB],
"name": "output"
},
settings=task_class.settings,
enabled=True,
category="Border Removal",
interactive=True)
j.save()
def load_poly_mask():
task_class = PolyMaskTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(job_name=task_class.name,
author="Deepanjan Roy",
description="TO DO",
input_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (ONEBIT, ),
"name": "input"
},
output_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (ONEBIT, ),
"name": "output"
},
settings=task_class.settings,
enabled=True,
category="Border Removal",
interactive=True)
j.save()
def load_segmentation():
task_class = PitchCorrectionTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(job_name=task_class.name,
author="Deepanjan Roy",
description="Interactive pitch correction using Neon.",
input_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (MEI, ),
"name": "input"
},
output_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (MEI, ),
"name": "output"
},
settings=task_class.settings,
enabled=True,
category="Pitch Correction",
interactive=True)
j.save()
def load_module():
job = Job.objects.filter(job_name=JOB_NAME)
if job.exists():
return None
else:
j = Job(
job_name=JOB_NAME,
author="Andrew Hankinson",
description=
"Converts an image to a JPEG2000 image suitable for display in Diva",
input_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": [3],
"name": None
},
output_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": [7],
"name": "output"
},
settings={},
enabled=True,
category="Conversion",
interactive=False)
j.save()
def load_pixel_segment():
task_class = PixelSegmentTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(job_name=task_class.name,
author="Ryan Bannon",
description="TO DO",
input_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (RGB, ),
"name": "input"
},
output_types={
"default": None,
"has_default": False,
"list_of": False,
"pixel_types": (RGB, ),
"name": "output"
},
settings=task_class.settings,
enabled=True,
category="Lyric Extraction",
interactive=True)
j.save()
def test_delete(self):
job = Job(name="test job")
job.save()
retr_job = Job.objects.get(name="test job")
retr_job.delete()
retr_job2 = Job.objects.filter(name="test job")
self.assertFalse(retr_job2.exists())
def load_dummy_job():
name = 'rodan.jobs.devel.dummy_job'
if not Job.objects.filter(job_name=name).exists():
j = Job(job_name=name,
author="Andrew Hankinson",
description="A Dummy Job for testing the Job loading and workflow system",
input_types={"default": None, "has_default": False, "list_of": False, "pixel_types": (1,), "name": "input"},
output_types={"default": None, "has_default": False, "list_of": False, "pixel_types": (1,), "name": "output"},
settings=[{}],
enabled=True,
category="Dummy",
interactive=False
)
j.save()
def load_poly_mask():
task_class = PolyMaskTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(job_name=task_class.name,
author="Deepanjan Roy",
description="TO DO",
input_types={"default": None, "has_default": False, "list_of": False, "pixel_types": (ONEBIT,), "name": "input"},
output_types={"default": None, "has_default": False, "list_of": False, "pixel_types": (ONEBIT,), "name": "output"},
settings=task_class.settings,
enabled=True,
category="Border Removal",
interactive=True
)
j.save()
def load_segmentation():
task_class = SegmentationTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(job_name=task_class.name,
author="Deepanjan Roy",
description="Finds the staves using Miyao Staff Finder and masks out everything else.",
input_types={"default": None, "has_default": False, "list_of": False, "pixel_types": (ONEBIT,), "name": "input"},
output_types={"default": None, "has_default": False, "list_of": False, "pixel_types": (ONEBIT,), "name": "output"},
settings=task_class.settings,
enabled=True,
category="Segmentation",
interactive=True
)
j.save()
def load_rt_staff_removal():
task_class = RTStafflineRemovalTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(job_name=task_class.name,
author="Deepanjan Roy",
description="Removes the staff lines usign Roach and Tatem Staffline removal algorithm.",
input_types={"default": None, "has_default": False, "list_of": False, "pixel_types": [ONEBIT,], "name": "input"},
output_types={"default": None, "has_default": False, "list_of": False, "pixel_types": [ONEBIT,], "name": "output"},
settings=task_class.settings,
enabled=True,
category="Staff Removal",
interactive=False
)
j.save()
def load_segmentation():
task_class = PitchCorrectionTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(job_name=task_class.name,
author="Deepanjan Roy",
description="Interactive pitch correction using Neon.",
input_types={"default": None, "has_default": False, "list_of": False, "pixel_types": (MEI,), "name": "input"},
output_types={"default": None, "has_default": False, "list_of": False, "pixel_types": (MEI,), "name": "output"},
settings=task_class.settings,
enabled=True,
category="Pitch Correction",
interactive=True
)
j.save()
def load_pixel_segment():
task_class = PixelSegmentTask
if not Job.objects.filter(job_name=task_class.name).exists():
j = Job(job_name=task_class.name,
author="Ryan Bannon",
description="TO DO",
input_types={"default": None, "has_default": False, "list_of": False, "pixel_types": (RGB,), "name": "input"},
output_types={"default": None, "has_default": False, "list_of": False, "pixel_types": (RGB,), "name": "output"},
settings=task_class.settings,
enabled=True,
category="Lyric Extraction",
interactive=True
)
j.save()
def load_module():
job = Job.objects.filter(job_name=JOB_NAME)
if job.exists():
return None
else:
j = Job(job_name=JOB_NAME,
author="Andrew Hankinson",
description="Converts an image to a JPEG2000 image suitable for display in Diva",
input_types={"default": None, "has_default": False, "list_of": False, "pixel_types": [3], "name": None},
output_types={"default": None, "has_default": False, "list_of": False, "pixel_types": [7], "name": "output"},
settings={},
enabled=True,
category="Conversion",
interactive=False
)
j.save()
def create_jobs_from_module(gamera_module, interactive=False):
previously_loaded_modules = list(Job.objects.values_list('job_name', 'interactive'))
for fn in gamera_module.module.functions:
# we only want jobs that will return a result and has a known pixel type
if not fn.return_type:
continue
if "pixel_types" not in fn.return_type.__dict__.keys():
continue
module_task = GameraTask()
module_task.name = str(fn)
registry.tasks.register(module_task)
# skip the job creation if we've already
# stored a reference to this job in the database
if (str(fn), interactive) in previously_loaded_modules:
continue
input_types = argconvert.convert_input_type(fn.self_type)
output_types = argconvert.convert_output_type(fn.return_type)
settings = argconvert.convert_arg_list(fn.args.list)
j = Job(
job_name=str(fn),
author=fn.author,
description=fn.escape_docstring().replace("\\n", "\n").replace('\\"', '"'),
input_types=input_types,
output_types=output_types,
settings=settings,
enabled=True,
category=gamera_module.module.category,
interactive=interactive
)
j.save()
previously_loaded_modules += [(str(fn), interactive)]
def test_save(self):
job = Job(name="test job")
job.save()
retr_job = Job.objects.get(name="test job")
self.assertEqual(retr_job.name, job.name)
