Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error **Keras ValueError: Input 0 is incompatible with layer conv2d_1: expected ndim=4, found ndim=5** **in python**. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

Table of Contents

## How Keras ValueError: Input 0 is incompatible with layer conv2d_1: expected ndim=4, found ndim=5 Error Occurs?

Today I get the following error **Keras ValueError: Input 0 is incompatible with layer conv2d_1: expected ndim=4, found ndim=5** **in python**.

## How To Solve Keras ValueError: Input 0 is incompatible with layer conv2d_1: expected ndim=4, found ndim=5 Error ?

**How To Solve Keras ValueError: Input 0 is incompatible with layer conv2d_1: expected ndim=4, found ndim=5 Error ?**To Solve Keras ValueError: Input 0 is incompatible with layer conv2d_1: expected ndim=4, found ndim=5 Error It should actually contain 3 dimensions only. And internally keras will add the batch dimension making it 4.

**Keras ValueError: Input 0 is incompatible with layer conv2d_1: expected ndim=4, found ndim=5**To Solve Keras ValueError: Input 0 is incompatible with layer conv2d_1: expected ndim=4, found ndim=5 Error It should actually contain 3 dimensions only. And internally keras will add the batch dimension making it 4.

## Solution 1

The problem is `input_shape`

.

It should actually contain 3 dimensions only. And internally keras will add the batch dimension making it 4.

Since you probably used `input_shape`

with 4 dimensions (batch included), keras is adding the 5th.

You should use `input_shape=(32,32,1)`

.

## Solution 2

The problem is with `input_shape`

. Try adding an extra dimension/channel for letting keras know that you are working on a grayscale image ie –>`1`

`input_shape= (56,56,1)`

. Probably if you are using a normal Deep learning model then it won’t raise an issue but for Convnet it does.

**Summery**

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

**Also, Read**