Using the ResNet50 model to classify images
We’re going to use a pretrained model included in Keras to do image recognition. Keras comes with several image recognition models including
We’ll use the ResNet50 in this project. This paper describes ResNets. Check out this link for details on the model and ResNets in general.
We have a few images to pick from to see how well the image classifier performs
-p-1080.jpg){kind=link}
import numpy as np
# from tensorflow.keras import backend
from keras.preprocessing import image
from tensorflow.keras.applications import resnet50 # <model
#Image visualization
%pylab inline
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
Using TensorFlow backend.Populating the interactive namespace from numpy and matplotlib#Now we load the imported model
model =resnet50.ResNet50() #Create a new instance of the model After we load the model we can use summary() to look at the model’s layers and data flow structure.
model.summary()Model: "resnet50"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) [(None, 224, 224, 3) 0
__________________________________________________________________________________________________
conv1_pad (ZeroPadding2D) (None, 230, 230, 3) 0 input_1[0][0]
__________________________________________________________________________________________________
conv1 (Conv2D) (None, 112, 112, 64) 9472 conv1_pad[0][0]
__________________________________________________________________________________________________
bn_conv1 (BatchNormalizationV1) (None, 112, 112, 64) 256 conv1[0][0]
__________________________________________________________________________________________________
activation (Activation) (None, 112, 112, 64) 0 bn_conv1[0][0]
__________________________________________________________________________________________________
pool1_pad (ZeroPadding2D) (None, 114, 114, 64) 0 activation[0][0]
__________________________________________________________________________________________________
max_pooling2d (MaxPooling2D) (None, 56, 56, 64) 0 pool1_pad[0][0]
__________________________________________________________________________________________________
res2a_branch2a (Conv2D) (None, 56, 56, 64) 4160 max_pooling2d[0][0]
__________________________________________________________________________________________________
bn2a_branch2a (BatchNormalizati (None, 56, 56, 64) 256 res2a_branch2a[0][0]
__________________________________________________________________________________________________
activation_1 (Activation) (None, 56, 56, 64) 0 bn2a_branch2a[0][0]
__________________________________________________________________________________________________
res2a_branch2b (Conv2D) (None, 56, 56, 64) 36928 activation_1[0][0]
__________________________________________________________________________________________________
bn2a_branch2b (BatchNormalizati (None, 56, 56, 64) 256 res2a_branch2b[0][0]
__________________________________________________________________________________________________
activation_2 (Activation) (None, 56, 56, 64) 0 bn2a_branch2b[0][0]
__________________________________________________________________________________________________
res2a_branch2c (Conv2D) (None, 56, 56, 256) 16640 activation_2[0][0]
__________________________________________________________________________________________________
res2a_branch1 (Conv2D) (None, 56, 56, 256) 16640 max_pooling2d[0][0]
__________________________________________________________________________________________________
bn2a_branch2c (BatchNormalizati (None, 56, 56, 256) 1024 res2a_branch2c[0][0]
__________________________________________________________________________________________________
bn2a_branch1 (BatchNormalizatio (None, 56, 56, 256) 1024 res2a_branch1[0][0]
__________________________________________________________________________________________________
add (Add) (None, 56, 56, 256) 0 bn2a_branch2c[0][0]
bn2a_branch1[0][0]
__________________________________________________________________________________________________
activation_3 (Activation) (None, 56, 56, 256) 0 add[0][0]
__________________________________________________________________________________________________
res2b_branch2a (Conv2D) (None, 56, 56, 64) 16448 activation_3[0][0]
__________________________________________________________________________________________________
bn2b_branch2a (BatchNormalizati (None, 56, 56, 64) 256 res2b_branch2a[0][0]
__________________________________________________________________________________________________
activation_4 (Activation) (None, 56, 56, 64) 0 bn2b_branch2a[0][0]
__________________________________________________________________________________________________
res2b_branch2b (Conv2D) (None, 56, 56, 64) 36928 activation_4[0][0]
__________________________________________________________________________________________________
bn2b_branch2b (BatchNormalizati (None, 56, 56, 64) 256 res2b_branch2b[0][0]
__________________________________________________________________________________________________
activation_5 (Activation) (None, 56, 56, 64) 0 bn2b_branch2b[0][0]
__________________________________________________________________________________________________
res2b_branch2c (Conv2D) (None, 56, 56, 256) 16640 activation_5[0][0]
__________________________________________________________________________________________________
bn2b_branch2c (BatchNormalizati (None, 56, 56, 256) 1024 res2b_branch2c[0][0]
__________________________________________________________________________________________________
add_1 (Add) (None, 56, 56, 256) 0 bn2b_branch2c[0][0]
activation_3[0][0]
__________________________________________________________________________________________________
activation_6 (Activation) (None, 56, 56, 256) 0 add_1[0][0]
__________________________________________________________________________________________________
res2c_branch2a (Conv2D) (None, 56, 56, 64) 16448 activation_6[0][0]
__________________________________________________________________________________________________
bn2c_branch2a (BatchNormalizati (None, 56, 56, 64) 256 res2c_branch2a[0][0]
__________________________________________________________________________________________________
activation_7 (Activation) (None, 56, 56, 64) 0 bn2c_branch2a[0][0]
__________________________________________________________________________________________________
res2c_branch2b (Conv2D) (None, 56, 56, 64) 36928 activation_7[0][0]
__________________________________________________________________________________________________
bn2c_branch2b (BatchNormalizati (None, 56, 56, 64) 256 res2c_branch2b[0][0]
__________________________________________________________________________________________________
activation_8 (Activation) (None, 56, 56, 64) 0 bn2c_branch2b[0][0]
__________________________________________________________________________________________________
res2c_branch2c (Conv2D) (None, 56, 56, 256) 16640 activation_8[0][0]
__________________________________________________________________________________________________
bn2c_branch2c (BatchNormalizati (None, 56, 56, 256) 1024 res2c_branch2c[0][0]
__________________________________________________________________________________________________
add_2 (Add) (None, 56, 56, 256) 0 bn2c_branch2c[0][0]
activation_6[0][0]
__________________________________________________________________________________________________
activation_9 (Activation) (None, 56, 56, 256) 0 add_2[0][0]
__________________________________________________________________________________________________
res3a_branch2a (Conv2D) (None, 28, 28, 128) 32896 activation_9[0][0]
__________________________________________________________________________________________________
bn3a_branch2a (BatchNormalizati (None, 28, 28, 128) 512 res3a_branch2a[0][0]
__________________________________________________________________________________________________
activation_10 (Activation) (None, 28, 28, 128) 0 bn3a_branch2a[0][0]
__________________________________________________________________________________________________
res3a_branch2b (Conv2D) (None, 28, 28, 128) 147584 activation_10[0][0]
__________________________________________________________________________________________________
bn3a_branch2b (BatchNormalizati (None, 28, 28, 128) 512 res3a_branch2b[0][0]
__________________________________________________________________________________________________
activation_11 (Activation) (None, 28, 28, 128) 0 bn3a_branch2b[0][0]
__________________________________________________________________________________________________
res3a_branch2c (Conv2D) (None, 28, 28, 512) 66048 activation_11[0][0]
__________________________________________________________________________________________________
res3a_branch1 (Conv2D) (None, 28, 28, 512) 131584 activation_9[0][0]
__________________________________________________________________________________________________
bn3a_branch2c (BatchNormalizati (None, 28, 28, 512) 2048 res3a_branch2c[0][0]
__________________________________________________________________________________________________
bn3a_branch1 (BatchNormalizatio (None, 28, 28, 512) 2048 res3a_branch1[0][0]
__________________________________________________________________________________________________
add_3 (Add) (None, 28, 28, 512) 0 bn3a_branch2c[0][0]
bn3a_branch1[0][0]
__________________________________________________________________________________________________
activation_12 (Activation) (None, 28, 28, 512) 0 add_3[0][0]
__________________________________________________________________________________________________
res3b_branch2a (Conv2D) (None, 28, 28, 128) 65664 activation_12[0][0]
__________________________________________________________________________________________________
bn3b_branch2a (BatchNormalizati (None, 28, 28, 128) 512 res3b_branch2a[0][0]
__________________________________________________________________________________________________
activation_13 (Activation) (None, 28, 28, 128) 0 bn3b_branch2a[0][0]
__________________________________________________________________________________________________
res3b_branch2b (Conv2D) (None, 28, 28, 128) 147584 activation_13[0][0]
__________________________________________________________________________________________________
bn3b_branch2b (BatchNormalizati (None, 28, 28, 128) 512 res3b_branch2b[0][0]
__________________________________________________________________________________________________
activation_14 (Activation) (None, 28, 28, 128) 0 bn3b_branch2b[0][0]
__________________________________________________________________________________________________
res3b_branch2c (Conv2D) (None, 28, 28, 512) 66048 activation_14[0][0]
__________________________________________________________________________________________________
bn3b_branch2c (BatchNormalizati (None, 28, 28, 512) 2048 res3b_branch2c[0][0]
__________________________________________________________________________________________________
add_4 (Add) (None, 28, 28, 512) 0 bn3b_branch2c[0][0]
activation_12[0][0]
__________________________________________________________________________________________________
activation_15 (Activation) (None, 28, 28, 512) 0 add_4[0][0]
__________________________________________________________________________________________________
res3c_branch2a (Conv2D) (None, 28, 28, 128) 65664 activation_15[0][0]
__________________________________________________________________________________________________
bn3c_branch2a (BatchNormalizati (None, 28, 28, 128) 512 res3c_branch2a[0][0]
__________________________________________________________________________________________________
activation_16 (Activation) (None, 28, 28, 128) 0 bn3c_branch2a[0][0]
__________________________________________________________________________________________________
res3c_branch2b (Conv2D) (None, 28, 28, 128) 147584 activation_16[0][0]
__________________________________________________________________________________________________
bn3c_branch2b (BatchNormalizati (None, 28, 28, 128) 512 res3c_branch2b[0][0]
__________________________________________________________________________________________________
activation_17 (Activation) (None, 28, 28, 128) 0 bn3c_branch2b[0][0]
__________________________________________________________________________________________________
res3c_branch2c (Conv2D) (None, 28, 28, 512) 66048 activation_17[0][0]
__________________________________________________________________________________________________
bn3c_branch2c (BatchNormalizati (None, 28, 28, 512) 2048 res3c_branch2c[0][0]
__________________________________________________________________________________________________
add_5 (Add) (None, 28, 28, 512) 0 bn3c_branch2c[0][0]
activation_15[0][0]
__________________________________________________________________________________________________
activation_18 (Activation) (None, 28, 28, 512) 0 add_5[0][0]
__________________________________________________________________________________________________
res3d_branch2a (Conv2D) (None, 28, 28, 128) 65664 activation_18[0][0]
__________________________________________________________________________________________________
bn3d_branch2a (BatchNormalizati (None, 28, 28, 128) 512 res3d_branch2a[0][0]
__________________________________________________________________________________________________
activation_19 (Activation) (None, 28, 28, 128) 0 bn3d_branch2a[0][0]
__________________________________________________________________________________________________
res3d_branch2b (Conv2D) (None, 28, 28, 128) 147584 activation_19[0][0]
__________________________________________________________________________________________________
bn3d_branch2b (BatchNormalizati (None, 28, 28, 128) 512 res3d_branch2b[0][0]
__________________________________________________________________________________________________
activation_20 (Activation) (None, 28, 28, 128) 0 bn3d_branch2b[0][0]
__________________________________________________________________________________________________
res3d_branch2c (Conv2D) (None, 28, 28, 512) 66048 activation_20[0][0]
__________________________________________________________________________________________________
bn3d_branch2c (BatchNormalizati (None, 28, 28, 512) 2048 res3d_branch2c[0][0]
__________________________________________________________________________________________________
add_6 (Add) (None, 28, 28, 512) 0 bn3d_branch2c[0][0]
activation_18[0][0]
__________________________________________________________________________________________________
activation_21 (Activation) (None, 28, 28, 512) 0 add_6[0][0]
__________________________________________________________________________________________________
res4a_branch2a (Conv2D) (None, 14, 14, 256) 131328 activation_21[0][0]
__________________________________________________________________________________________________
bn4a_branch2a (BatchNormalizati (None, 14, 14, 256) 1024 res4a_branch2a[0][0]
__________________________________________________________________________________________________
activation_22 (Activation) (None, 14, 14, 256) 0 bn4a_branch2a[0][0]
__________________________________________________________________________________________________
res4a_branch2b (Conv2D) (None, 14, 14, 256) 590080 activation_22[0][0]
__________________________________________________________________________________________________
bn4a_branch2b (BatchNormalizati (None, 14, 14, 256) 1024 res4a_branch2b[0][0]
__________________________________________________________________________________________________
activation_23 (Activation) (None, 14, 14, 256) 0 bn4a_branch2b[0][0]
__________________________________________________________________________________________________
res4a_branch2c (Conv2D) (None, 14, 14, 1024) 263168 activation_23[0][0]
__________________________________________________________________________________________________
res4a_branch1 (Conv2D) (None, 14, 14, 1024) 525312 activation_21[0][0]
__________________________________________________________________________________________________
bn4a_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096 res4a_branch2c[0][0]
__________________________________________________________________________________________________
bn4a_branch1 (BatchNormalizatio (None, 14, 14, 1024) 4096 res4a_branch1[0][0]
__________________________________________________________________________________________________
add_7 (Add) (None, 14, 14, 1024) 0 bn4a_branch2c[0][0]
bn4a_branch1[0][0]
__________________________________________________________________________________________________
activation_24 (Activation) (None, 14, 14, 1024) 0 add_7[0][0]
__________________________________________________________________________________________________
res4b_branch2a (Conv2D) (None, 14, 14, 256) 262400 activation_24[0][0]
__________________________________________________________________________________________________
bn4b_branch2a (BatchNormalizati (None, 14, 14, 256) 1024 res4b_branch2a[0][0]
__________________________________________________________________________________________________
activation_25 (Activation) (None, 14, 14, 256) 0 bn4b_branch2a[0][0]
__________________________________________________________________________________________________
res4b_branch2b (Conv2D) (None, 14, 14, 256) 590080 activation_25[0][0]
__________________________________________________________________________________________________
bn4b_branch2b (BatchNormalizati (None, 14, 14, 256) 1024 res4b_branch2b[0][0]
__________________________________________________________________________________________________
activation_26 (Activation) (None, 14, 14, 256) 0 bn4b_branch2b[0][0]
__________________________________________________________________________________________________
res4b_branch2c (Conv2D) (None, 14, 14, 1024) 263168 activation_26[0][0]
__________________________________________________________________________________________________
bn4b_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096 res4b_branch2c[0][0]
__________________________________________________________________________________________________
add_8 (Add) (None, 14, 14, 1024) 0 bn4b_branch2c[0][0]
activation_24[0][0]
__________________________________________________________________________________________________
activation_27 (Activation) (None, 14, 14, 1024) 0 add_8[0][0]
__________________________________________________________________________________________________
res4c_branch2a (Conv2D) (None, 14, 14, 256) 262400 activation_27[0][0]
__________________________________________________________________________________________________
bn4c_branch2a (BatchNormalizati (None, 14, 14, 256) 1024 res4c_branch2a[0][0]
__________________________________________________________________________________________________
activation_28 (Activation) (None, 14, 14, 256) 0 bn4c_branch2a[0][0]
__________________________________________________________________________________________________
res4c_branch2b (Conv2D) (None, 14, 14, 256) 590080 activation_28[0][0]
__________________________________________________________________________________________________
bn4c_branch2b (BatchNormalizati (None, 14, 14, 256) 1024 res4c_branch2b[0][0]
__________________________________________________________________________________________________
activation_29 (Activation) (None, 14, 14, 256) 0 bn4c_branch2b[0][0]
__________________________________________________________________________________________________
res4c_branch2c (Conv2D) (None, 14, 14, 1024) 263168 activation_29[0][0]
__________________________________________________________________________________________________
bn4c_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096 res4c_branch2c[0][0]
__________________________________________________________________________________________________
add_9 (Add) (None, 14, 14, 1024) 0 bn4c_branch2c[0][0]
activation_27[0][0]
__________________________________________________________________________________________________
activation_30 (Activation) (None, 14, 14, 1024) 0 add_9[0][0]
__________________________________________________________________________________________________
res4d_branch2a (Conv2D) (None, 14, 14, 256) 262400 activation_30[0][0]
__________________________________________________________________________________________________
bn4d_branch2a (BatchNormalizati (None, 14, 14, 256) 1024 res4d_branch2a[0][0]
__________________________________________________________________________________________________
activation_31 (Activation) (None, 14, 14, 256) 0 bn4d_branch2a[0][0]
__________________________________________________________________________________________________
res4d_branch2b (Conv2D) (None, 14, 14, 256) 590080 activation_31[0][0]
__________________________________________________________________________________________________
bn4d_branch2b (BatchNormalizati (None, 14, 14, 256) 1024 res4d_branch2b[0][0]
__________________________________________________________________________________________________
activation_32 (Activation) (None, 14, 14, 256) 0 bn4d_branch2b[0][0]
__________________________________________________________________________________________________
res4d_branch2c (Conv2D) (None, 14, 14, 1024) 263168 activation_32[0][0]
__________________________________________________________________________________________________
bn4d_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096 res4d_branch2c[0][0]
__________________________________________________________________________________________________
add_10 (Add) (None, 14, 14, 1024) 0 bn4d_branch2c[0][0]
activation_30[0][0]
__________________________________________________________________________________________________
activation_33 (Activation) (None, 14, 14, 1024) 0 add_10[0][0]
__________________________________________________________________________________________________
res4e_branch2a (Conv2D) (None, 14, 14, 256) 262400 activation_33[0][0]
__________________________________________________________________________________________________
bn4e_branch2a (BatchNormalizati (None, 14, 14, 256) 1024 res4e_branch2a[0][0]
__________________________________________________________________________________________________
activation_34 (Activation) (None, 14, 14, 256) 0 bn4e_branch2a[0][0]
__________________________________________________________________________________________________
res4e_branch2b (Conv2D) (None, 14, 14, 256) 590080 activation_34[0][0]
__________________________________________________________________________________________________
bn4e_branch2b (BatchNormalizati (None, 14, 14, 256) 1024 res4e_branch2b[0][0]
__________________________________________________________________________________________________
activation_35 (Activation) (None, 14, 14, 256) 0 bn4e_branch2b[0][0]
__________________________________________________________________________________________________
res4e_branch2c (Conv2D) (None, 14, 14, 1024) 263168 activation_35[0][0]
__________________________________________________________________________________________________
bn4e_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096 res4e_branch2c[0][0]
__________________________________________________________________________________________________
add_11 (Add) (None, 14, 14, 1024) 0 bn4e_branch2c[0][0]
activation_33[0][0]
__________________________________________________________________________________________________
activation_36 (Activation) (None, 14, 14, 1024) 0 add_11[0][0]
__________________________________________________________________________________________________
res4f_branch2a (Conv2D) (None, 14, 14, 256) 262400 activation_36[0][0]
__________________________________________________________________________________________________
bn4f_branch2a (BatchNormalizati (None, 14, 14, 256) 1024 res4f_branch2a[0][0]
__________________________________________________________________________________________________
activation_37 (Activation) (None, 14, 14, 256) 0 bn4f_branch2a[0][0]
__________________________________________________________________________________________________
res4f_branch2b (Conv2D) (None, 14, 14, 256) 590080 activation_37[0][0]
__________________________________________________________________________________________________
bn4f_branch2b (BatchNormalizati (None, 14, 14, 256) 1024 res4f_branch2b[0][0]
__________________________________________________________________________________________________
activation_38 (Activation) (None, 14, 14, 256) 0 bn4f_branch2b[0][0]
__________________________________________________________________________________________________
res4f_branch2c (Conv2D) (None, 14, 14, 1024) 263168 activation_38[0][0]
__________________________________________________________________________________________________
bn4f_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096 res4f_branch2c[0][0]
__________________________________________________________________________________________________
add_12 (Add) (None, 14, 14, 1024) 0 bn4f_branch2c[0][0]
activation_36[0][0]
__________________________________________________________________________________________________
activation_39 (Activation) (None, 14, 14, 1024) 0 add_12[0][0]
__________________________________________________________________________________________________
res5a_branch2a (Conv2D) (None, 7, 7, 512) 524800 activation_39[0][0]
__________________________________________________________________________________________________
bn5a_branch2a (BatchNormalizati (None, 7, 7, 512) 2048 res5a_branch2a[0][0]
__________________________________________________________________________________________________
activation_40 (Activation) (None, 7, 7, 512) 0 bn5a_branch2a[0][0]
__________________________________________________________________________________________________
res5a_branch2b (Conv2D) (None, 7, 7, 512) 2359808 activation_40[0][0]
__________________________________________________________________________________________________
bn5a_branch2b (BatchNormalizati (None, 7, 7, 512) 2048 res5a_branch2b[0][0]
__________________________________________________________________________________________________
activation_41 (Activation) (None, 7, 7, 512) 0 bn5a_branch2b[0][0]
__________________________________________________________________________________________________
res5a_branch2c (Conv2D) (None, 7, 7, 2048) 1050624 activation_41[0][0]
__________________________________________________________________________________________________
res5a_branch1 (Conv2D) (None, 7, 7, 2048) 2099200 activation_39[0][0]
__________________________________________________________________________________________________
bn5a_branch2c (BatchNormalizati (None, 7, 7, 2048) 8192 res5a_branch2c[0][0]
__________________________________________________________________________________________________
bn5a_branch1 (BatchNormalizatio (None, 7, 7, 2048) 8192 res5a_branch1[0][0]
__________________________________________________________________________________________________
add_13 (Add) (None, 7, 7, 2048) 0 bn5a_branch2c[0][0]
bn5a_branch1[0][0]
__________________________________________________________________________________________________
activation_42 (Activation) (None, 7, 7, 2048) 0 add_13[0][0]
__________________________________________________________________________________________________
res5b_branch2a (Conv2D) (None, 7, 7, 512) 1049088 activation_42[0][0]
__________________________________________________________________________________________________
bn5b_branch2a (BatchNormalizati (None, 7, 7, 512) 2048 res5b_branch2a[0][0]
__________________________________________________________________________________________________
activation_43 (Activation) (None, 7, 7, 512) 0 bn5b_branch2a[0][0]
__________________________________________________________________________________________________
res5b_branch2b (Conv2D) (None, 7, 7, 512) 2359808 activation_43[0][0]
__________________________________________________________________________________________________
bn5b_branch2b (BatchNormalizati (None, 7, 7, 512) 2048 res5b_branch2b[0][0]
__________________________________________________________________________________________________
activation_44 (Activation) (None, 7, 7, 512) 0 bn5b_branch2b[0][0]
__________________________________________________________________________________________________
res5b_branch2c (Conv2D) (None, 7, 7, 2048) 1050624 activation_44[0][0]
__________________________________________________________________________________________________
bn5b_branch2c (BatchNormalizati (None, 7, 7, 2048) 8192 res5b_branch2c[0][0]
__________________________________________________________________________________________________
add_14 (Add) (None, 7, 7, 2048) 0 bn5b_branch2c[0][0]
activation_42[0][0]
__________________________________________________________________________________________________
activation_45 (Activation) (None, 7, 7, 2048) 0 add_14[0][0]
__________________________________________________________________________________________________
res5c_branch2a (Conv2D) (None, 7, 7, 512) 1049088 activation_45[0][0]
__________________________________________________________________________________________________
bn5c_branch2a (BatchNormalizati (None, 7, 7, 512) 2048 res5c_branch2a[0][0]
__________________________________________________________________________________________________
activation_46 (Activation) (None, 7, 7, 512) 0 bn5c_branch2a[0][0]
__________________________________________________________________________________________________
res5c_branch2b (Conv2D) (None, 7, 7, 512) 2359808 activation_46[0][0]
__________________________________________________________________________________________________
bn5c_branch2b (BatchNormalizati (None, 7, 7, 512) 2048 res5c_branch2b[0][0]
__________________________________________________________________________________________________
activation_47 (Activation) (None, 7, 7, 512) 0 bn5c_branch2b[0][0]
__________________________________________________________________________________________________
res5c_branch2c (Conv2D) (None, 7, 7, 2048) 1050624 activation_47[0][0]
__________________________________________________________________________________________________
bn5c_branch2c (BatchNormalizati (None, 7, 7, 2048) 8192 res5c_branch2c[0][0]
__________________________________________________________________________________________________
add_15 (Add) (None, 7, 7, 2048) 0 bn5c_branch2c[0][0]
activation_45[0][0]
__________________________________________________________________________________________________
activation_48 (Activation) (None, 7, 7, 2048) 0 add_15[0][0]
__________________________________________________________________________________________________
avg_pool (GlobalAveragePooling2 (None, 2048) 0 activation_48[0][0]
__________________________________________________________________________________________________
fc1000 (Dense) (None, 1000) 2049000 avg_pool[0][0]
==================================================================================================
Total params: 25,636,712
Trainable params: 25,583,592
Non-trainable params: 53,120
__________________________________________________________________________________________________#Load in the sample image we want to predict
imgloc='shark.jpg'
img =image.load_img(imgloc) #Load in the image
print(shape(img))#Size of image
#Look at loaded image
plt.figure()
plt.imshow(img)
plt.title('Original')
plt.show() # display it
#Because the image is too big we need to downsample it in order to
#pass it to Keras. Keras needs imagesize to be matched to
#the number of input nodes in the model in this case 224x224 pxls
imgName = imgloc#'bay.jpg'
#Re- Load in the sample image we want to predict
img =image.load_img(imgName, target_size=(224,224)) #Load in the image and resize
print(shape(img))#Size of image
#Look at loaded image
plt.figure()
plt.imshow(img)
plt.title('Downsampled')
plt.show() # display it(351, 624, 3)
(224, 224, 3)
#Convert image to array (flatten)
x=image.img_to_array(img)
#The neural network is actually expecting (a list) more than 1 image so we will trick it
#Add a 4th dimension to the array
x= np.expand_dims(x,axis=0)
#Normalize data to 0-1 instead of 0-255
x=resnet50.preprocess_input(x)#Now we run the normalized data through the network and predict
predictions =model.predict(x)
#We will get back a predictions object with 1000 element array.
#Each element reps a probability that the input matches each of the 1000 objects
#that the network was trained on.
#Here we use a function to tell us the names of the objects that
#the network predicted. We only want to top 10 so we ask for ony 10
prediction_classes =resnet50.decode_predictions(predictions, top=10)
#Print out all the predictions
for imagenet_id, name, likelihood in prediction_classes[0]:
print("-{}: {:2f} % likelihood".format(name, likelihood*100))
#Look at loaded image
plt.figure()
plt.imshow(img)
plt.title('Downsampled')
plt.show() # display it-hammerhead: 65.850562 % likelihood
-great_white_shark: 21.884859 % likelihood
-tiger_shark: 12.248133 % likelihood
-electric_ray: 0.006338 % likelihood
-albatross: 0.002689 % likelihood
-sturgeon: 0.002292 % likelihood
-stingray: 0.001961 % likelihood
-killer_whale: 0.001225 % likelihood
-grey_whale: 0.000721 % likelihood
-loggerhead: 0.000335 % likelihood
def imgClasser(locc):
imgName = locc
#Re- Load in the sample image we want to predict
img =image.load_img(imgName, target_size=(224,224)) #Load in the image and resize
#Convert image to array (flatten)
x=image.img_to_array(img)
#The neural network is actually expecting (a list) more than 1 image so we will trick it
#Add a 4th dimension to the array
x= np.expand_dims(x,axis=0)
#Normalize data to 0-1 instead of 0-255
x=resnet50.preprocess_input(x)
#Now we run the normalized data through the network and predict
predictions =model.predict(x)
#We will get back a predictions object with 1000 element array.
#Each element reps a probability that the input matches each of the 1000 objects
#that the network was trained on.
#Here we use a function to tell us the names of the objects that
#the network predicted. We only want to top 10 so we ask for ony 10
prediction_classes =resnet50.decode_predictions(predictions, top=10)
#Print out all the predictions
for imagenet_id, name, likelihood in prediction_classes[0]:
print("-{}: {:2f} % likelihood".format(name, likelihood*100))
#Look at loaded image
plt.figure()
plt.imshow(img)
plt.title('Downsampled')
plt.show() # display it
Finally, we use the model to identify an object in a new image. We pass the image to the model and print the top 10 most likely objects that the model thinks it is.
imgClasser('burger.jpg')-cheeseburger: 99.906200 % likelihood
-bagel: 0.070201 % likelihood
-hotdog: 0.012809 % likelihood
-bakery: 0.003466 % likelihood
-plate: 0.002827 % likelihood
-French_loaf: 0.002641 % likelihood
-chocolate_sauce: 0.000375 % likelihood
-ice_cream: 0.000308 % likelihood
-guacamole: 0.000269 % likelihood
-meat_loaf: 0.000222 % likelihood
We see that the model is able to successfully identify the image as containing a cheeseburger with a 99.9% liklihood!
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