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```ここに言語を入力
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predict.py 文字数のため、変更部分のみ記入(他部分は参照サイトと同じ)
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```ここに言語を入力
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from keras.models import Sequential
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import
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from keras.layers import Activation, Dense, Dropout
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from
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from keras.utils.np_utils import to_categorical
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from keras.optimizers import Adagrad
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from keras.p
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from keras.optimizers import Adam
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import numpy as np
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import tensorflow as tf
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from PIL import Image
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import os
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# 学習用のデータを作る.
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image_list = []
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session_conf = tf.compat.v1.ConfigProto(
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intra_op_parallelism_threads=1, inter_op_parallelism_threads=1)
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tf.set_random_seed(0)
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sess = tf.Session(graph=tf.get_default_graph(), config=session_conf)
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K.set_session(sess)
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sess = tf.Session(config=tf.ConfigProto(device_count={'GPU': 0}))
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input_shape = (224, 224, 3)
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label_list = []
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n
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# ./data/train 以下のorange,appleディレクトリ以下の画像を読み込む。
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y = []
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for
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for dir in os.listdir("data/train"):
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if
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if dir == ".DS_Store":
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continue
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dir1 = "data/train/" + dir
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label = 0
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if dir == "次郎": # appleはラベル0
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label = 0
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elif dir == "次郎ではない": # orangeはラベル1
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label = 1
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if file != ".DS_Store":
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# 配列label_listに正解ラベルを追加(りんご:0 オレンジ:1)
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label_list.append(label)
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filepath = dir1 + "/" + file
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# 画像を25x25pixelに変換し、1要素が[R,G,B]3要素を含む配列の25x25の２次元配列として読み込む。
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# [R,G,B]はそれぞれが0-255の配列。
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image = np.array(Image.open(filepath).resize((25, 25)))
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print(filepath)
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# 配列を変換し、[[Redの配列],[Greenの配列],[Blueの配列]] のような形にする。
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image = image.transpose(2, 0, 1)
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# さらにフラットな1次元配列に変換。最初の1/3はRed、次がGreenの、最後がBlueの要素がフラットに並ぶ。
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image = image.reshape(
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1, image.shape[0] * image.shape[1] * image.shape[2]).astype("float32")[0]
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# 出来上がった配列をimage_listに追加。
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image_list.append(image / 255.)
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# kerasに渡すためにnumpy配列に変換。
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image_list = np.array(image_list)
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# ラベルの配列を1と0からなるラベル配列に変更
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# 0 -> [1,0], 1 -> [0,1] という感じ。
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Y = to_categorical(label_list)
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# モデルを生成してニューラルネットを構築
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model = Sequential()
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model.add(Dense(200, input_dim=1875))
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model.add(Activation("relu"))
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model.add(Dropout(0.2))
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model.add(Dense(200))
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model.add(Activation("relu"))
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model.add(Dropout(0.2))
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model.add(Dense(2))
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model.add(Activation("softmax"))
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# オプティマイザにAdamを使用
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opt = Adam(lr=0.001)
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# モデルをコンパイル
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model.compile(loss="categorical_crossentropy",
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optimizer=opt, metrics=["accuracy"])
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# 学習を実行。10%はテストに使用。
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model.fit(image_list, Y, nb_epoch=1500, batch_size=100, validation_split=0.1)
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# テスト用ディレクトリ(./data/train/)の画像でチェック。正解率を表示する。
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total = 0.
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ok_count = 0.
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for dir in os.listdir("data/train"):
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if dir == ".DS_Store":
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validation_data=(x_test, y_test))
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model.save_weights('param.hdfs')
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acc = history.history["accuracy"]
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val_acc = history.history["val_accuracy"]
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loss = history.history["loss"]
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val_loss = history.history["val_loss"]
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epochs = range(1, len(acc) + 1)
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plt.plot(history.history["accuracy"], label="Training Acc")
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plt.plot(history.history["val_accuracy"], label="Validation Acc")
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plt.ylabel('Accuracy')
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plt.xlabel('Epoch')
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plt.grid()
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plt.legend(['Train', 'Validation'], loc = 'upper left')
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plt.savefig('acc.png')
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plt.figure()
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plt.plot(history.history["loss"], label="Training Loss")
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plt.plot(history.history["val_loss"], label="Validation Loss")
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plt.ylabel('Loss')
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plt.xlabel('Epoch')
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plt.grid()
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plt.legend(['Train', 'Validation'], loc = 'upper left')
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plt.savefig('loss.png')
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plt.figure()
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plt.show()
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dir1 = "data/jirou-test/" + dir
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label = 0
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if dir == "次郎":
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label = 0
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elif dir == "次郎ではない":
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label = 1
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for file in os.listdir(dir1):
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if file != ".DS_Store":
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label_list.append(label)
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filepath = dir1 + "/" + file
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image = np.array(Image.open(filepath).resize((25, 25)))
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print(filepath)
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image = image.transpose(2, 0, 1)
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image = image.reshape(
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1, image.shape[0] * image.shape[1] * image.shape[2]).astype("float32")[0]
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result = model.predict_classes(np.array([image / 255.]))
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print("label:", label, "result:", result[0])
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total += 1.
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if label == result[0]:
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ok_count += 1.
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print("正解率: ", ok_count / total * 100, "%")
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```ここに言語を入力
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(base) xxxx@xxxx image-classfication-jiro % /opt/anaconda3/bin/python /Users/xxxx/Downloads/image-classfication-jiro/predict.py
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Using TensorFlow backend.
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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_np_qint8 = np.dtype([("qint8", np.int8, 1)])
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/Users/xxxx/Downloads/image-classfication-jiro/predict.py:70: UserWarning: The `nb_epoch` argument in `fit` has been renamed `epochs`.
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Traceback (most recent call last):
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File "/Users/xxxxx/Downloads/image-classfication-jiro/predict.py", line 70, in <module>
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File "/opt/anaconda3/lib/python3.7/site-packages/keras/engine/training.py", line 1154, in fit
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File "/opt/anaconda3/lib/python3.7/site-packages/keras/engine/training.py", line 621, in _standardize_user_data
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File "/opt/anaconda3/lib/python3.7/site-packages/keras/engine/training_utils.py", line 145, in standardize_input_data
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ValueError: Error when checking target: expected activation_3 to have shape (2,) but got array with shape (1,)
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```ここに言語を入力
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(base) xxxx@xxxx image-classfication-jiro % /opt/anaconda3/bin/python /Users/xxxx/Downloads/image-classfication-jiro/predict.py
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/opt/anaconda3/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
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/Users/xxxx/Downloads/image-classfication-jiro/predict.py:70: UserWarning: The `nb_epoch` argument in `fit` has been renamed `epochs`.
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File "/opt/anaconda3/lib/python3.7/site-packages/keras/engine/training.py", line 1154, in fit
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File "/opt/anaconda3/lib/python3.7/site-packages/keras/engine/training.py", line 621, in _standardize_user_data
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File "/opt/anaconda3/lib/python3.7/site-packages/keras/engine/training_utils.py", line 145, in standardize_input_data
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ValueError: Error when checking target: expected activation_3 to have shape (2,) but got array with shape (1,)
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```
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