Solving the OpenCV TypeError: Expected Ptr for argument 'src'

When working with OpenCV in Python, encountering errors is part of the learning curve. One common issue that puzzles many developers is the TypeError: Expected Ptr<cv::UMat> for argument 'src'. This error can be frustrating, especially when it's unclear what it means or how to fix it. In this post, we'll demystify this error and guide you through resolving it, ensuring your image processing tasks run smoothly.

Understanding the Error

The error message TypeError: Expected Ptr<cv::UMat> for argument 'src' typically arises when an OpenCV function expects an image object but receives an incompatible type instead. This mismatch can occur for various reasons, such as attempting to pass a non-image object or an improperly loaded image as an argument to an OpenCV function.

OpenCV functions that manipulate images often expect the image to be in a specific format, usually a NumPy array or a cv::UMat object. If the object passed does not match these expectations, OpenCV raises a TypeError.

Common Causes and Solutions

Incorrect Image Loading

One of the most common causes of this error is attempting to use an OpenCV function on an image that hasn't been loaded correctly. For instance, if cv2.imread() fails to load an image, it returns None instead of an image object. Passing this None value to another OpenCV function triggers the error.

Solution: Always check if the image has been loaded correctly before proceeding with further operations.

import cv2

# Attempt to load an image
image = cv2.imread('path/to/your/image.png')

# Check if the image has been loaded correctly
if image is None:
    print("Error loading image")
    # Proceed with your operations
    # For example, converting the image to grayscale
    gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

Incompatible Data Types

Another reason for this error could be passing an object of an incompatible data type to an OpenCV function. For example, mistakenly passing a list or a non-image object instead of an image.

Solution: Ensure the object passed to the OpenCV function is a NumPy array representing an image. If you're manipulating the image data, confirm that the manipulations preserve the array's structure and data type.

import cv2
import numpy as np

# Correctly loaded image
image = cv2.imread('path/to/your/image.png')

# Assuming 'image' is a valid image object
# An example of a manipulation that preserves the data type and structure
modified_image = np.copy(image)
# Now, 'modified_image' can be safely used with OpenCV functions

Incorrect Function Usage

Misusing OpenCV functions can also lead to this error. For example, using a function that expects a different kind of argument or misinterpreting the function's documentation.

Solution: Carefully review the documentation for the OpenCV function you're using. Ensure that you're passing the correct type and number of arguments.


The TypeError: Expected Ptr<cv::UMat> for argument 'src' in OpenCV is a common hurdle that many developers encounter. It usually points to issues with how images are loaded or passed to OpenCV functions. By checking image loading, ensuring data types are compatible, and correctly using OpenCV functions, you can overcome this error and proceed with your image processing tasks with confidence.

Remember, debugging is an iterative process. If you encounter this error, take a step back, review your code, and apply the solutions discussed. With patience and practice, you'll navigate through OpenCV's complexities like a pro.