gistfile1.c

diff --git a/bin/cifar-10.c b/bin/cifar-10.c
index 1552aae..ca975db 100644
--- a/bin/cifar-10.c
+++ b/bin/cifar-10.c
@@ -192,7 +192,7 @@ int main(int argc, char** argv)
 			},
 		},
 	};
-	ccv_convnet_t* convnet = ccv_convnet_new(1, ccv_size(32, 32), params, sizeof(params) / sizeof(ccv_convnet_layer_param_t));
+	ccv_convnet_t* convnet = ccv_convnet_new(0, ccv_size(31, 31), params, sizeof(params) / sizeof(ccv_convnet_layer_param_t));
 	assert(ccv_convnet_verify(convnet, 10) == 0);
 	assert(argc == 5);
 	int num1 = atoi(argv[2]);
@@ -208,18 +208,18 @@ int main(int argc, char** argv)
 		{
 			fread(bytes, 32 * 32 + 1, 1, r1);
 			int c = bytes[0];
-			ccv_dense_matrix_t* a = ccv_dense_matrix_new(32, 32, CCV_32F | CCV_C3, 0, 0);
-			for (i = 0; i < 32; i++)
-				for (j = 0; j < 32; j++)
-					a->data.f32[(j + i * 32) * 3] = bytes[j + i * 32 + 1];
+			ccv_dense_matrix_t* a = ccv_dense_matrix_new(31, 31, CCV_32F | CCV_C3, 0, 0);
+			for (i = 0; i < 31; i++)
+				for (j = 0; j < 31; j++)
+					a->data.f32[(j + i * 31) * 3] = bytes[j + i * 32 + 1] - 128;
 			fread(bytes, 32 * 32, 1, r1);
-			for (i = 0; i < 32; i++)
-				for (j = 0; j < 32; j++)
-					a->data.f32[(j + i * 32) * 3 + 1] = bytes[j + i * 32];
+			for (i = 0; i < 31; i++)
+				for (j = 0; j < 31; j++)
+					a->data.f32[(j + i * 31) * 3 + 1] = bytes[j + i * 32] - 128;
 			fread(bytes, 32 * 32, 1, r1);
-			for (i = 0; i < 32; i++)
-				for (j = 0; j < 32; j++)
-					a->data.f32[(j + i * 32) * 3 + 2] = bytes[j + i * 32];
+			for (i = 0; i < 31; i++)
+				for (j = 0; j < 31; j++)
+					a->data.f32[(j + i * 31) * 3 + 2] = bytes[j + i * 32] - 128;
 			ccv_categorized_t categorized = ccv_categorized(c, a, 0);
 			ccv_array_push(categorizeds, &categorized);
 		}
@@ -228,24 +228,24 @@ int main(int argc, char** argv)
 		{
 			fread(bytes, 32 * 32 + 1, 1, r2);
 			int c = bytes[0];
-			ccv_dense_matrix_t* a = ccv_dense_matrix_new(32, 32, CCV_32F | CCV_C3, 0, 0);
-			for (i = 0; i < 32; i++)
-				for (j = 0; j < 32; j++)
-					a->data.f32[(j + i * 32) * 3] = bytes[j + i * 32 + 1];
+			ccv_dense_matrix_t* a = ccv_dense_matrix_new(31, 31, CCV_32F | CCV_C3, 0, 0);
+			for (i = 0; i < 31; i++)
+				for (j = 0; j < 31; j++)
+					a->data.f32[(j + i * 31) * 3] = bytes[j + i * 32 + 1] - 128;
 			fread(bytes, 32 * 32, 1, r2);
-			for (i = 0; i < 32; i++)
-				for (j = 0; j < 32; j++)
-					a->data.f32[(j + i * 32) * 3 + 1] = bytes[j + i * 32];
+			for (i = 0; i < 31; i++)
+				for (j = 0; j < 31; j++)
+					a->data.f32[(j + i * 31) * 3 + 1] = bytes[j + i * 32] - 128;
 			fread(bytes, 32 * 32, 1, r2);
-			for (i = 0; i < 32; i++)
-				for (j = 0; j < 32; j++)
-					a->data.f32[(j + i * 32) * 3 + 2] = bytes[j + i * 32];
+			for (i = 0; i < 31; i++)
+				for (j = 0; j < 31; j++)
+					a->data.f32[(j + i * 31) * 3 + 2] = bytes[j + i * 32] - 128;
 			ccv_categorized_t categorized = ccv_categorized(c, a, 0);
 			ccv_array_push(tests, &categorized);
 		}
 		ccv_convnet_layer_train_param_t layer_params[9];
 		memset(layer_params, 0, sizeof(layer_params));