# list_of_images = [list_of_images[0]]
save_to = save_to_dir+cur_dir[-11:]
while list_of_images:
current_image = list_of_images.pop()
image_id = os.path.split(current_image)[1].split('.')[0]
with open(current_image, 'r') as ff:
lbl = ff.readline().replace('\n', '').strip()
background_image.save(save_to+'/frame_files/'+'blank.png')
object_specs = os.path.split(glob.glob(cur_dir+'/*'+image_id+'*.png')[0])[1].split('.')
object_id = int(object_specs[-3])
##create a "one_object" instance
oo = imo.one_object(original_image_folder+image_id+'.png', original_object_map_folder+image_id+'.png', object_id)
##create a composition for the object
tc = imo.boring_composition(SIDE=SIDE, locations=box_centers, radius = radius)
##create a montage for presenting the object
mo = imo.montage(SIDE, background_image, tc)
##create the list
mo.object_list = [oo]*tc.number_of_objects
##make the pictures with objects, location cues and no labels for pcp runs
try:
object_pictures = mo.show_picture(mask_margin=mask_margin)
except:
1/0
##show them for good measure
mo.show_picture(flat=True)[0].show()
cnt = 0
##add text to each pasted object frame and save
for ii,op in enumerate(object_pictures):
imo.put_text(op, message = lbl, position = (.5, .5), fill=box_colors[ii],size = category_cue_font_size).save(save_to+'/frame_files/'+image_file_names % (image_id, object_id, cnt,'image'))
copy_background = Image.open('/Users/tnaselar/Data/Presentation/single.object.boxes/Boxes2.png')
imo.put_text(copy_background, message = lbl, position = (.5, .5), fill=box_colors[ii],size = category_cue_font_size).save(save_to+'/frame_files/'+image_file_names % (image_id, object_id, cnt,'cue'))
def find_object_values(mask):
'''
object_values = find_object_values(mask)
Find pixel values of each of the objects in an object mask
Returns a numpy array containing the values.
len(object_values) = total number of objects in the mask
'''
from numpy import unique, array
return unique(array(mask))
while im_ids:
##instantiate montage with random geometry
obj_comp = imo.simple_composition(SIDE, 1, min_radius=min_obj_size, max_radius=max_obj_size)
m = imo.montage(SIDE, background_image, obj_comp, mask_margin = mask_margin, object_background=background_contrast, reveal_corners = 5)
##loop over number of objects
while not m.full():
##sample an object
im, mask, object_id, imdx = grab_image(im_dir, im_ids)
m.add_one_object(im, mask, object_id)
##print picture to file
m.picture.save(save_to+imdx)
m.background_picture.save(save_to+'background.'+imdx)
labeled = imo.put_text(m.background_picture, message = labels.pop(), position = (.5, .5), size = font_size)
labeled.save(save_to+'label.background.'+imdx)
##create a "one_object" instance
oo = imo.one_object(
original_image_folder + image_id + ".png", original_object_map_folder + image_id + ".png", object_id
)
##create a "target_composition" for the object
tc = imo.target_composition(
target.shape[0],
number_of_locations,
oo,
target,
max_radius=max_object_radius,
min_radius=min_object_radius,
try_this_many=try_this_many,
)
##create a montage for presenting the object
mo = imo.montage(SIDE, imo.make_a_blank(SIDE, background_image_color, "RGB"), tc)
##create the list
mo.object_list = [oo] * tc.number_of_objects
##make the pictures with objects, location cues and no labels for pcp runs
object_pictures = mo.show_picture(mask_margin=mask_margin, reveal_corners=location_cue_size)
##show them for good measure
mo.show_picture(flat=True)[0].show()
cnt = 0
for op in object_pictures:
imo.reveal_center(op, fixation_dot_size, fill=fixation_dot_color).save(
save_to + "/frame_files/" + image_file_names % (image_id, object_id, cnt, "image")
)
cnt += 1
##make pictures with location cues only for both the pcp and img runs
cue_pictures = mo.show_picture(mask_margin=mask_margin, reveal_corners=location_cue_size, locations_only=True)