from math import pi
from starflow.utils import ListUnion
from bson import SON
from model_categories import MODEL_CATEGORIES
MODELS = ListUnion(MODEL_CATEGORIES.values())
NUM_IMAGES = 20
USE_CANONICAL = True
NSEG = 20
base_images = [SON([('model_ids',[m]),
('num_images',NUM_IMAGES),
('use_canonical',USE_CANONICAL),
('generator','renderman'),
('selection','random'),
('ty',SON([('$gt',-.6),('$lt',.6)])),
('tz',SON([('$gt',-.6),('$lt',.6)])),
('ryz',SON([('$gt',2*pi*(ind % NSEG)/NSEG),('$lt',2*pi*((ind % NSEG) + 1)/NSEG)]))
])
for (ind,m) in enumerate(MODELS)]
import copy
imagesets = []
#gray background
for m in base_images:
from starflow.utils import ListUnion
import copy
from bson import SON
from model_categories import MODEL_CATEGORIES as CAT
all_models = ListUnion(CAT.values())
extraction = SON([ ('transform_average',SON([('transform_name','translation'),('percentile',[73,90,99])])),
('query',SON([('image.model_id',SON([('$in',all_models)])),
('image.bg_id','gray.tdl'),
('image.tx',SON([('$exists',False)])),
('image.s',SON([('$exists',False)])),
('image.rxy',SON([('$exists',False)])),
('image.rxz',SON([('$exists',False)])),
('$or',[SON([('image.ty',SON([('$exists',True)])),('image.tz',SON([('$exists',True)]))]),
SON([('image.ryz',SON([('$exists',True)]))])])
]))
])
config = {
'extractions' : [extraction]
}