정착소

2020_01_22 VGG16

def predict_vgg16(model, filename) : # 모델 사이즈로 이미지 파일을 읽기 image = load_img(filename, target_size=(224, 224)) # image = PIL.Image.Image image mode=RGB size=224x224 # 이미지 데이터를 numpy로 변환 image = img_to_array(image) # [ # [[211. 184. 163.] # [225. 193. 170.] # ... # [237. 202. 180.]] # ... # ] # # image.shape = (224, 224, 3) # 화면에 이미지 보여주기 plt.imshow(image.astype(int)) plt.show() # vgg16.preprocess_..

2020_01_22 CIFAR10

import numpy as np import matplotlib.pyplot as plt import tensorflow as tf from tensorflow import keras from tensorflow.keras import optimizers from tensorflow.keras.layers import Dense, Flatten, Conv2D, MaxPooling2D, BatchNormalization, Input import time ▶ 이전 CNN 코드 * CIFAR10 적용 전 CNN 복습 (raw_train_x, raw_train_y), (raw_test_x, raw_test_y) = tf.keras.datasets.mnist.load_data() train_x = raw_tra..

2020_01_21 CNN

※ 이전 DNN 코드 * CNN 들어가기 전 복습 import numpy as np import matplotlib.pyplot as plt import tensorflow as tf from tensorflow import keras from tensorflow.keras import optimizers from tensorflow.keras.layers import Dense, Flatten, Input import time (raw_train_x, raw_train_y), (raw_test_x, raw_test_y) = tf.keras.datasets.mnist.load_data() train_x = raw_train_x/255 test_x = raw_test_x/255 train_y = raw_t..

2020_01_21 IRIS

※ IRIS 데이터 분류 import numpy as np import pandas as pd import matplotlib.pyplot as plt import tensorflow as tf from tensorflow import keras from tensorflow.keras import optimizers from tensorflow.keras.layers import Dense !wget https://raw.githubusercontent.com/dhrim/oss_university/master/material/iris.csv !head iris.csv !wc iris.csv iris = pd.read_csv("iris.csv") iris.head() iris.info() data = ir..

2020_01_20 DL(Keras)

1. Keras 모듈 import import numpy as np import pandas as pd import matplotlib.pyplot as plt import tensorflow as tf from tensorflow import keras import time from tensorflow.keras import optimizers from tensorflow.keras.layers import Dense * Optimizers : 최적화 * Dense : 입출력을 모두 연결해주는 레이어 리스트 보기 from tensorflow.python.client import device_lib print(tf.test.gpu_device_name()) NVIDIA GPU 상태보기 !nvidia-sm..