def scene_complete(fn_src, img_mask, img_target, query_name,
offset=(0, 0),
plot_figure=False, save_dir=None):
"""
Complete the scene
"""
print fn_src
img_src = io.imread(fn_src).astype(np.float64)
img_mask, img_src, offset_adj \
= create_mask(img_mask.astype(np.float64),
img_target, img_src, offset=offset)
img_sc = poisson_blend(img_mask, img_src, img_target, method='normal',
offset_adj=offset)
if plot_figure:
plt.imshow(img_sc)
plt.show()
if save_dir is not None:
sc_name = '%s+%s.jpg' % (
query_name.split('/')[-1].split('.jpg')[0],
fn_src.split('/')[-1].split('.jpg')[0])
sc_name = opj(save_dir, sc_name)
io.imsave(sc_name, img_sc)
return sc_name
def mask_complete(img_mask, img_target, query_name, save_dir=None,
plot_figure=False):
"""
Scene completion with mask
"""
img_sc = poisson_blend(img_mask, 1 - img_mask, img_target,
method='src', offset_adj=(0, 0))
mst_name = query_name.split('/')[-1].split('.jpg')[0]
mst_name = opj(save_dir, mst_name + 'mask.jpg')
if plot_figure:
print '\nOriginal image with mask.'
plt.imshow(img_sc)
plt.show()
if save_dir is not None:
io.imsave(mst_name, img_sc)
return mst_name
def get_matches(gist, gist_data, block_weight, file_names, img_mask,
query_name, mask_name, plot_figure=True,
save_dir=None):
"""
Using the gist value, get the closes matches from the database
"""
offset = (0, 0)
# find the close matches of a scene chosen using the
er = np.linalg.norm(
(gist_data - gist.reshape((len(gist_data), 1))) * block_weight, axis=0).flatten()
agst = np.argsort(er)
file_names = np.array(file_names)
fn_sorted = file_names[agst][1:7]
print '\nImages chosen from scene completion are:\n', fn_sorted
img_target = io.imread(query_name).astype(np.float64)
img_mask, _, offset_adj \
= create_mask(img_mask.astype(np.float64),
img_target, img_mask, offset=offset)
img_sc = poisson_blend(img_mask, 1-img_mask, img_target,
method='src', offset_adj=(0, 0))
mst_name = query_name.split('/')[-1].split('.jpg')[0]
mst_name = opj(save_dir, mst_name+'mask.jpg')
if plot_figure:
print '\nOriginal image with mask.'
plt.imshow(img_sc)
plt.show()
if save_dir is not None:
io.imsave(mst_name, img_sc)
print '\nCompleted images from 1st to 5th choices:'
sc_names = []
for i in range(len(fn_sorted)):
# img_target = io.imread(query_name).astype(np.float64)
print fn_sorted[i]
img_src = io.imread(fn_sorted[i]).astype(np.float64)
# img_mask = io.imread(mask_name, as_grey=True)
img_mask, img_src, offset_adj \
= create_mask(img_mask.astype(np.float64),
img_target, img_src, offset=offset)
img_sc = poisson_blend(img_mask, img_src, img_target, method='normal',
offset_adj=offset)
if plot_figure:
plt.imshow(img_sc)
plt.show()
if save_dir is not None:
sc_name = '%s+%s.jpg' %(
query_name.split('/')[-1].split('.jpg')[0],
fn_sorted[i].split('/')[-1].split('.jpg')[0])
sc_name = opj(save_dir, sc_name)
io.imsave(sc_name, img_sc)
sc_names.append(sc_name)
return mst_name, fn_sorted, sc_names
