CODEWITHSUNDEEP
keras
Mossand
Mossand

Reputation: 3

ValueError: Error when checking input: expected conv2d_1_input to have 4 dimensions, but got array with shape (80, 120, 3)

I am a learner who is just beginning to learn deep learning. I just started using Keras. I want to implement SRCNN. This problem occurs when I try to import a picture to test the model first.

Problem:

ValueError: Error when checking input: expected conv2d_1_input to have 4 dimensions, but got array with shape (80, 120, 3)

My code is as follows：

from PIL import Image
import numpy as np
from keras import Sequential
from keras.layers import Conv2D, Activation

input_image = Image.open('../../res/image/120x80/120x80 (1).png')
input_image_array = np.array(input_image)

model = Sequential()

model.add(Conv2D(64, (9, 9), data_format='channels_last', activation='relu', input_shape=(80, 120, 3)))
model.add(Conv2D(35, (1, 1), data_format='channels_last', activation='relu', input_shape=(80, 120, 3)))
model.add(Conv2D(1, (5, 5), data_format='channels_last', input_shape=(120, 80, 3)))
model.compile(loss='mean_squared_error', optimizer='sgd')
model.fit(input_image_array, input_image_array)
print(model.summary())

Upvotes: 0

Views: 907

Answers (1)

Dr. Snoopy
Dr. Snoopy

Reputation: 56347

To give a single input image, you need to include the samples dimension (the first one), so you need to add dimension with a value of one:

input_image_array = np.array(input_image)
input_image_array = input_image_array[np.newaxis, :, :, :]

This will change the shape to (1, 80, 120, 3) which corresponds to one image sample.

Upvotes: 1

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