modified the transformation.py

README.md

@@ -46,9 +46,10 @@ You can skip steps "2" and modify the "test_generate_canvas.m" accordingly if yo
 ### Training
 1. Transformation network
 (1) cd "matlab_code";
-(2) run "test_generate_transform.m" to generate training data for the transformation network, training data is stored in folder "../traindata/transform/";
-(3) cd "../python-code";
-(4) run "transformation.py" with setting "training_phase = True".
+(2) run "train_generate_transform.m" to generate training data for the transformation network, training data is stored in folder "../traindata/transform/";
+(3) run "resize_transform.m"
+(4) cd "../python-code";
+(5) run "transformation.py" with setting "training_phase = True".
 2. Ordering network
 (1) cd "matlab_code";
 (2) run "train_generate_order.m" to generate training data for the ordering network, training data is stored in folder "../traindata/order/";

matlab_code/resize_transform.m

@@ -0,0 +1,9 @@
+dirs = dir('../traindata/label_refine/*.png');
+dirs = struct2cell(dirs);
+
+mkdir('../traindata/label_refine_512/');
+for i = 1:size(dirs,2)
+    img = imread(['../traindata/label_refine/' dirs{1,i}]);
+    img = imresize(img,[512,1024],'nearest');
+    imwrite(img,['../traindata/label_refine_512/' dirs{1,i}]);
+end

python_code/transformation.py

@@ -6,11 +6,11 @@
 from spatial_transformer import transformer
 import numpy as np
 
-training_phase = False
+training_phase = True
 if(training_phase):
     rgb_path = "../traindata/RGB512Full/"
     mat_path = "../traindata/transform/transform_512/"
-    label_path = "../traindata/label_refine/"
+    label_path = "../traindata/label_refine_512/"
     save_model_path = "../trainedmodels/transform"
     num_folder = 2
 else: