import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from tensorflow.keras.datasets import cifar10
(x_train, y_train), (x_test, y_test) = cifar10.load_data()
print(x_train.shape)
plt.imshow(x_train[1])
plt.show()
plt.imshow(x_train[2])
plt.show()
https://keras.io/api/layers/convolution_layers/convolution2d/
https://www.tensorflow.org/tutorials/images/cnn
from tensorflow.keras import Sequential
from tensorflow.keras.layers import Dense, Flatten, Conv2D
model = Sequential()
model.add(Conv2D(32, (3,3), activation="relu")) #filters 32,kernel_size matrice (3,3)
model.add(Flatten()) #mettre dans un vect
model.add(Dense(300, activation='relu'))
model.add(Dense(10, activation='softmax')) #une couche dense
import tensorflow as tf
from tensorflow.keras.losses import SparseCategoricalCrossentropy as s2c
model.compile(optimizer='sgd',
loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
metrics=['accuracy'])
model.fit