Write a Python program for applying CNN with considering the following requirements: Shuffle the cifar 10 training set x_train( each input with corresponding label in y_train ) Select 2500 images and you must ensure that each class must contain at least 180 samples Apply CNN that keeps noisy examples. Overall, the pseudocode of CNN is as follows: The code must contain at least one lambda expression The code must contain at one comprehension list It is Not allowed to use the numpy library. Euclidean distance is the distance between two samples in Euclidean space. The formula can be expressed as: USE THIS CODE  import tensorflow import cv2 from tensorflow import keras from PIL import Image import numpy as p (x_train, y_train), (_, _) = tf.keras.datasets.cifar10.load_data() x_train = [cv2.cvtColor(image, cv2.COLOR_BGR2GRAY).flatten().tolist() for image in x_train] ##x_train=np.asarray(x_train) print(len(x_train)) print(len(x_train[0])) # 32*32 NOTE: PLEAS USE THE CODE I ATTACHED  THANK YOU

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Write a Python program for applying CNN with considering the following requirements:

  • Shuffle the cifar 10 training set x_train( each input with corresponding label in y_train )
  • Select 2500 images and you must ensure that each class must contain at least 180 samples
  • Apply CNN that keeps noisy examples. Overall, the pseudocode of CNN is as follows:
    • The code must contain at least one lambda expression
    • The code must contain at one comprehension list
    • It is Not allowed to use the numpy library.

    Euclidean distance is the distance between two samples in Euclidean space. The formula can be expressed as:

USE THIS CODE 

import tensorflow
import cv2
from tensorflow import keras
from PIL import Image
import numpy as p

(x_train, y_train), (_, _) = tf.keras.datasets.cifar10.load_data()

x_train = [cv2.cvtColor(image, cv2.COLOR_BGR2GRAY).flatten().tolist() for image in x_train]
##x_train=np.asarray(x_train)
print(len(x_train))
print(len(x_train[0])) # 32*32

NOTE: PLEAS USE THE CODE I ATTACHED 

THANK YOU

+
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pip install tensorflow
Then, use the following code:
In [63]: import tensorflow
import cv2
from tensorflow import keras
from PIL import Image
import numpy as p
(x_train, y_train), (, _) = tf.keras.datasets.cifar10.load_data()
x_train = [cv2.cvtcolor(image, cv2.COLOR_BGR2GRAY).flatten().tolist() for image in x_train]
##x_train=np.asarray(x_train)
print(len(x_train))
print (len(x_train[e])) # 32*32
<IPython.core.display.Javascript object>
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1024
Write a Python program for applying CNN with considering the following requirements:
• Shuffle the cifar 10 training set x_train( each input with corresponding label in y_train )
• Select 2500 images and you must ensure that each class must contain at least 180 samples
11:14 PM
P Type here to search
87°F A O O
DG 4) ENG
9/27/2021
Transcribed Image Text:+ و مترجم - بحث Go ogle X Untitled4 - Jupyter Noteb x CSC 605_HW1 - Jupyter N X Downloads/csc/ O x Answered: Write a Python b localhost:8888/notebooks/Downloads/csc/CSC%20605_HW1.ipynb O قائمة القراءة | bartleby b sQL for Beginners. û Black. - jolyó li>yo B Google biljs A YouTube Gmail M Släuhill jupyter cSC 1.°_HW' Last Checkpoint: :rio l dio ual (autosaved) Logout File Edit View Insert Cell Kernel Widgets Help Not Trusted Python 3 O 个 Run C » Markdown pip install tensorflow Then, use the following code: In [63]: import tensorflow import cv2 from tensorflow import keras from PIL import Image import numpy as p (x_train, y_train), (, _) = tf.keras.datasets.cifar10.load_data() x_train = [cv2.cvtcolor(image, cv2.COLOR_BGR2GRAY).flatten().tolist() for image in x_train] ##x_train=np.asarray(x_train) print(len(x_train)) print (len(x_train[e])) # 32*32 <IPython.core.display.Javascript object> 50000 1024 Write a Python program for applying CNN with considering the following requirements: • Shuffle the cifar 10 training set x_train( each input with corresponding label in y_train ) • Select 2500 images and you must ensure that each class must contain at least 180 samples 11:14 PM P Type here to search 87°F A O O DG 4) ENG 9/27/2021
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