fixed some bugs threshold and gray image

Author: Ole Kroeger

.gitignore

@@ -1 +1,2 @@
 .idea/
+.MNIST_data/

MNIST_data/t10k-images-idx3-ubyte.gz

@@ -1,2 +1,2 @@
-model_checkpoint_path: "cps/model.ckpt"
-all_model_checkpoint_paths: "cps/model.ckpt"
+model_checkpoint_path: "model.ckpt"
+all_model_checkpoint_paths: "model.ckpt"

MNIST_data/t10k-labels-idx1-ubyte.gz

@@ -73,8 +73,9 @@ def shift(img,sx,sy):
 sess.run(init)
 
 # use 1000 batches with a size of 100 each to train our net
-for i in range(1000):
+for i in range(1):
   batch_xs, batch_ys = mnist.train.next_batch(100)
+  print(batch_xs)
   # run the train_step function with the given image values (x) and the real output (y_)
   sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
 
@@ -100,7 +101,7 @@ def shift(img,sx,sy):
 i = 0
 for no in [8,0,4,3]:
     # read the image
-    gray = cv2.imread("blog/own_"+str(no)+".png", cv2.CV_LOAD_IMAGE_GRAYSCALE)
+    gray = cv2.imread("blog/own_"+str(no)+".png", 0)
 
     # rescale it
     gray = cv2.resize(255-gray, (28, 28))
@@ -174,4 +175,3 @@ def shift(img,sx,sy):
 """
 print sess.run(prediction, feed_dict={x: images, y_: correct_vals})
 print sess.run(accuracy, feed_dict={x: images, y_: correct_vals})
-