--- a
+++ b/code/gen_dataset.lua
@@ -0,0 +1,49 @@
+require 'torch';
+require 'image';
+
+folder = '/home/andrew/mitosis-detection'
+
+train_folder = paths.concat(folder,'mitosis-train')
+test_folder = paths.concat(folder,'mitosis-test')
+trainset = paths.concat(folder,'mitosis-train.t7')
+testset = paths.concat(folder,'mitosis-test.t7')
+
+function gen_dataset(data_folder, outfile)
+	true_folder = paths.concat(data_folder,'true')
+	false_folder = paths.concat(data_folder,'false')
+
+	true_files = {}
+	false_files = {}
+
+	for file in paths.files(true_folder,'.png') do
+		table.insert(true_files, paths.concat(true_folder,file))
+	end
+
+	for file in paths.files(false_folder,'.png') do
+		table.insert(false_files, paths.concat(false_folder,file))
+	end
+
+	data = torch.ByteTensor(#true_files+#false_files,3,101,101)
+	label = torch.ByteTensor(#true_files+#false_files)
+
+	for i,file in ipairs(true_files) do
+		print(i)
+		data[{{i},{},{},{}}] = image.load(file,3,'byte')
+		label[i] = 1
+	end
+
+	for i,file in ipairs(false_files) do
+		print(i + #true_files)
+		data[{{i + #true_files},{},{},{}}] = image.load(file,3,'byte')
+		label[i + #true_files] = 1
+	end
+
+	dataset = {}
+	dataset.data = data
+	dataset.label = label
+
+	torch.save(outfile, dataset)
+end
+
+gen_dataset(train_folder,trainset)
+gen_dataset(test_folder,testset)