keras

keras02

由 故事扮演 提交于 2021-01-04 07:34:35
本项目参考： https://www.bilibili.com/video/av31500120?t=4657 训练代码 1 # coding: utf-8 2 # Learning from Mofan and Mike G 3 # Recreated by Paprikatree 4 # Convolution NN Train 5 6 import numpy as np 7 from keras.datasets import mnist 8 from keras.utils import np_utils 9 from keras.models import Sequential 10 from keras.layers import Convolution2D, Activation, MaxPool2D, Flatten, Dense 11 from keras.optimizers import Adam 12 from keras.models import load_model 13 14 15 nb_class = 10 16 nb_epoch = 4 17 batchsize = 128 18 19 ''' 20 1st,准备参数 21 X_train: (0,255) --> (0,1) CNN中似乎没有必要？cnn自动转了吗？ 22

How to find the wrong predictions in Keras?

由 江枫思渺然 提交于 2021-01-04 04:37:09
问题 I have built a Keras model for extracting information from a raw input of text input. I am getting an accuracy of 0.9869. How can I know which of the training data is making the accuracy go low? I have pasted the code I am using below. import numpy as np from keras.models import Model, load_model from keras.layers import Input, Dense, LSTM, Activation, Bidirectional, Dot, Flatten from keras.callbacks import ModelCheckpoint x_nyha = np.load("data/x_nyha.npy") y_nyha = np.load("data/y/y_nyha

What is DepthwiseConv2D and SeparableConv2D? How is it different from normal Conv2D layer in keras?

由 左心房为你撑大大i 提交于 2021-01-04 03:12:48
问题 I was looking through the architecture of EfficientnetB0 and noticed DepthwiseConv2D operation. Did some digging and found that there's also a SeparableConv2D. What exactly are these operations? 来源： https://stackoverflow.com/questions/61967172/what-is-depthwiseconv2d-and-separableconv2d-how-is-it-different-from-normal-con

What is DepthwiseConv2D and SeparableConv2D? How is it different from normal Conv2D layer in keras?

由 我们两清 提交于 2021-01-04 03:12:14
问题 I was looking through the architecture of EfficientnetB0 and noticed DepthwiseConv2D operation. Did some digging and found that there's also a SeparableConv2D. What exactly are these operations? 来源： https://stackoverflow.com/questions/61967172/what-is-depthwiseconv2d-and-separableconv2d-how-is-it-different-from-normal-con

TypeError('Keyword argument not understood:', 'groups') in keras.models load_model

由 一曲冷凌霜 提交于 2021-01-04 02:37:15
问题 After training a model using Google Colab, I downloaded it using the following command (inside Google Colab): model.save('model.h5') from google.colab import files files.download('model.h5') My problem is that when I try to load the downloaded model.h5 using my local machine (outside Google Colab), I get the following error: [input] from keras.models import load_model model = load_model(model.h5) [output] Traceback (most recent call last): File "test.py", line 2, in <module> model = load

TypeError('Keyword argument not understood:', 'groups') in keras.models load_model

由 早过忘川 提交于 2021-01-04 02:36:06
问题 After training a model using Google Colab, I downloaded it using the following command (inside Google Colab): model.save('model.h5') from google.colab import files files.download('model.h5') My problem is that when I try to load the downloaded model.h5 using my local machine (outside Google Colab), I get the following error: [input] from keras.models import load_model model = load_model(model.h5) [output] Traceback (most recent call last): File "test.py", line 2, in <module> model = load

How to use tf.Lambda and tf.Variable at TensorFlow 2.0

由 扶醉桌前 提交于 2021-01-04 02:32:08
问题 I'm very new to TensorFlow 2.0. I wrote a code for Cyclic GAN as follows (I extract code only for building generator neural network): def instance_norm(x, epsilon=1e-5): scale = tf.Variable(initial_value=np.random.normal(1., 0.02, x.shape[-1:]), trainable=True, name='SCALE', dtype=tf.float32) offset = tf.Variable(initial_value=np.zeros(x.shape[-1:]), trainable=True, name='OFFSET', dtype=tf.float32) mean, variance = tf.nn.moments(x, axes=[1, 2], keepdims=True) inv = tf.math.rsqrt(variance +

Combining Two CNN's

由 馋奶兔 提交于 2021-01-04 02:05:11
问题 I Want to Combine Two CNN Into Just One In Keras, What I Mean Is that I Want The Neural Network To Take Two Images And Process Each One in Separate CNN, and Then Concatenate Them Together Into The Flattening Layer and Use Fully Connected Layer to Do The Last Work, Here What I Did: # Start With First Branch ############################################################ branch_one = Sequential() # Adding The Convolution branch_one.add(Conv2D(32, (3,3),input_shape = (64,64,3) , activation = 'relu'

Combining Two CNN's

由 萝らか妹 提交于 2021-01-04 02:03:08
问题 I Want to Combine Two CNN Into Just One In Keras, What I Mean Is that I Want The Neural Network To Take Two Images And Process Each One in Separate CNN, and Then Concatenate Them Together Into The Flattening Layer and Use Fully Connected Layer to Do The Last Work, Here What I Did: # Start With First Branch ############################################################ branch_one = Sequential() # Adding The Convolution branch_one.add(Conv2D(32, (3,3),input_shape = (64,64,3) , activation = 'relu'

Combining Two CNN's

由 生来就可爱ヽ(ⅴ＜●) 提交于 2021-01-04 02:02:44
问题 I Want to Combine Two CNN Into Just One In Keras, What I Mean Is that I Want The Neural Network To Take Two Images And Process Each One in Separate CNN, and Then Concatenate Them Together Into The Flattening Layer and Use Fully Connected Layer to Do The Last Work, Here What I Did: # Start With First Branch ############################################################ branch_one = Sequential() # Adding The Convolution branch_one.add(Conv2D(32, (3,3),input_shape = (64,64,3) , activation = 'relu'
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