def testSingleImg():
NetHelper.gpu()
#submission()
nh = NetHelper(deploy=cfgs.deploy_pt, model=cfgs.best_model_dir)
img = Data.imFromFile(os.path.join(cfgs.train_mask_path, "1_1_mask.tif"))
res = nh.bin_pred_map(img)
print(np.histogram(res))
def testSingleImg():
NetHelper.gpu()
#submission()
nh=NetHelper(deploy=cfgs.deploy_pt,model=cfgs.best_model_dir)
img=Data.imFromFile(os.path.join(cfgs.train_mask_path,"1_1_mask.tif"))
res=nh.bin_pred_map(img)
print(np.histogram(res))
def submission():
NetHelper.gpu(2)
#submission()
nh = NetHelper(deploy=cfgs.deploy_pt, model=cfgs.best_model_dir)
if debug:
l = Data.folder_opt(cfgs.train_data_path, func, nh)
else:
l = Data.folder_opt(cfgs.test_data_path, func, nh)
l = np.array(l, dtype=[('x', int), ('y', object)])
l.sort(order='x')
first_row = 'img,pixels'
file_name = 'submission.csv'
with open(file_name, 'w+') as f:
f.write(first_row)
for i in l:
s = str(i[0]) + ',' + i[1]
f.write(('\n' + s))
def submission():
NetHelper.gpu(2)
#submission()
nh=NetHelper(deploy=cfgs.deploy_pt,model=cfgs.best_model_dir)
if debug:
l=Data.folder_opt(cfgs.train_data_path,func,nh)
else:
l=Data.folder_opt(cfgs.test_data_path,func,nh)
l=np.array(l,dtype=[('x',int),('y',object)])
l.sort(order='x')
first_row = 'img,pixels'
file_name = 'submission.csv'
with open(file_name, 'w+') as f:
f.write(first_row)
for i in l:
s = str(i[0]) + ',' + i[1]
f.write(('\n'+s))