From 4d13dd352825db3cabcd4a765d51d7bb604a9d47 Mon Sep 17 00:00:00 2001 From: Alexander Munch-Hansen Date: Thu, 25 Apr 2019 01:21:36 +0200 Subject: [PATCH] Hm --- tmp/tensor.py | 58 +++++++++++++++++++++++++++++++++++++++------------ 1 file changed, 45 insertions(+), 13 deletions(-) diff --git a/tmp/tensor.py b/tmp/tensor.py index 7d7afdc9..051ae2ca 100644 --- a/tmp/tensor.py +++ b/tmp/tensor.py @@ -18,19 +18,51 @@ training_labels = [] test_img = [] test_labels_ = [] -for piece in OUR_PIECES: - # training set - for _ in range(10): - for filename in glob.glob(f"../training_images/{piece}/*_square/*.png")[:-50]: - training_img.append(cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2GRAY)) - training_labels.append(piece) - # test set - for _ in range(5): - for filename in glob.glob(f"../training_images/{piece}/*_square/*.png")[-50:]: - test_img.append(cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2GRAY)) - test_labels_.append(piece) +# training set +for _ in range(10): + for filename in glob.glob(f"../training_images/rook/*_square/*.png")[:-50]: + training_img.append(cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2GRAY)) + training_labels.append(0) +for _ in range(10): + for filename in glob.glob(f"../training_images/knight/*_square/*.png")[:-50]: + training_img.append(cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2GRAY)) + training_labels.append(1) + +for _ in range(10): + for filename in glob.glob(f"../training_images/bishop/*_square/*.png")[:-50]: + training_img.append(cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2GRAY)) + training_labels.append(2) + +for _ in range(10): + for filename in glob.glob(f"../training_images/empty/*_square/*.png")[:-7300]: + training_img.append(cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2GRAY)) + training_labels.append(3) + +# test set +for _ in range(5): + for filename in glob.glob(f"../training_images/rook/*_square/*.png")[-50:]: + test_img.append(cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2GRAY)) + test_labels_.append(0) + +# test set +for _ in range(5): + for filename in glob.glob(f"../training_images/knight/*_square/*.png")[-50:]: + test_img.append(cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2GRAY)) + test_labels_.append(1) + +# test set +for _ in range(5): + for filename in glob.glob(f"../training_images/bishop/*_square/*.png")[-50:]: + test_img.append(cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2GRAY)) + test_labels_.append(2) + +# test set +for _ in range(5): + for filename in glob.glob(f"../training_images/empty/*_square/*.png")[-50:]: + test_img.append(cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2GRAY)) + test_labels_.append(3) width, height = training_img[0].shape @@ -51,7 +83,7 @@ model.add(tf.keras.layers.Conv2D(64, (3, 3), activation='relu')) model.add(tf.keras.layers.Flatten()) model.add(tf.keras.layers.Dense(64, activation='relu')) -model.add(tf.keras.layers.Dense(3, activation='softmax')) +model.add(tf.keras.layers.Dense(4, activation='softmax')) model.summary() @@ -66,5 +98,5 @@ test_loss, test_acc = model.evaluate(test_images, test_labels_) print(test_acc) # Save entire model to a HDF5 file -model.save('chess_model_3_pieces.h5') +model.save('pls_model.h5')