ctask = SON([('transform_average', SON([('transform_name','translation'),('max',True)])),
('N',NUM_SPLITS),
('ntrain',NTRAIN),
('ntest',NTEST),
('overlap',OVERLAP),
('universe',SON([('image.bg_id',SON([('$ne','gray.tdl')]))])),
('query',[SON([('image.model_id',SON([('$in',CAT[cat1])]))]),
SON([('image.model_id',SON([('$in',CAT[cat2])]))])])
])
mtask = SON([('transform_average', SON([('transform_name','translation'),('max',True)])),
('N',NUM_SPLITS),
('ntrain',NTRAIN),
('ntest',NTEST),
('overlap',OVERLAP),
('universe',SON([('image.bg_id',SON([('$ne','gray.tdl')]))])),
('query',[SON([('image.model_id',SON([('$in',k)]))]) for k in mixup(CAT,[[cat1],[cat2]])])
])
t1 = copy.deepcopy(ctask)
t1['universe'].update(trans_q)
t1['task_label'] = cat1 + '/' + cat2 + ' trans'
task_set.append(t1)
t2 = copy.deepcopy(ctask)
t2['universe'].update(inrot_q)
t2['task_label'] = cat1 + '/' + cat2 + ' inrot'
task_set.append(t2)
t3 = copy.deepcopy(mtask)
t3['universe'].update(trans_q)
t3['task_label'] = cat1 + '/' + cat2 + ' trans mixed'
('N',10),
('ntrain',300),
('ntest',150),
('overlap',.75),
('universe',SON([('image.bg_id','gray.tdl')])),
('query',[SON([('image.model_id',SON([('$in',uset(CAT,k))]))]) for k in tenway_cats])
])
tenway_mixup_task = SON([
('transform_average', SON([('transform_name','translation'),('max',True)])),
('N',10),
('ntrain',300),
('ntest',150),
('overlap',.75),
('universe',SON([('image.bg_id','gray.tdl')])),
('query',[SON([('image.model_id',SON([('$in',k)]))]) for k in mixup(CAT,tenway_cats)])
])
car_plane_cats = [['cars'],['planes']]
car_vs_plane_task = SON([
('transform_average', SON([('transform_name','translation'),('max',True)])),
('N',10),
('ntrain',60),
('ntest',30),
('overlap',.75),
('universe',SON([('image.bg_id','gray.tdl')])),
('query',[SON([('image.model_id',SON([('$in',uset(CAT,k))]))]) for k in car_plane_cats])
])
[
SON([("image.model_id", SON([("$in", CAT[cat1])]))]),
SON([("image.model_id", SON([("$in", CAT[cat2])]))]),
],
),
]
)
mtask = SON(
[
("transform_average", SON([("transform_name", "translation"), ("max", True)])),
("N", NUM_SPLITS),
("ntrain", NTRAIN),
("ntest", NTEST),
("overlap", OVERLAP),
("universe", SON([("image.bg_id", "gray.tdl")])),
("query", [SON([("image.model_id", SON([("$in", k)]))]) for k in mixup(CAT, [[cat1], [cat2]])]),
]
)
t1 = copy.deepcopy(ctask)
t1["universe"].update(trans_q)
t1["task_label"] = cat1 + "/" + cat2 + " trans"
task_set.append(t1)
t2 = copy.deepcopy(ctask)
t2["universe"].update(inrot_q)
t2["task_label"] = cat1 + "/" + cat2 + " inrot"
task_set.append(t2)
t3 = copy.deepcopy(mtask)
t3["universe"].update(trans_q)
