Error: (-215:assertion failed) !ssize.empty() in function 'cv::resize'

Error: (-215:assertion failed) !ssize.empty() in function 'cv::resize'

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Understanding and Resolving the OpenCV Error: "(-215: Assertion Failed) !ssize.empty() in Function cv::resize"

OpenCV, a renowned library for computer vision tasks, occasionally presents users with challenging error messages, such as (-215: Assertion failed) !ssize.empty() in function cv::resize. This error, while common, can be a source of confusion, especially for those new to image processing. Our goal is to simplify this error, examining its causes and offering straightforward solutions.

Root Cause: Why Does This Error Occur?

The error occurs when the input image to cv::resize is empty or invalid. The cv::resize function in OpenCV is protected by an assertion statement to check if the source image size (ssize) is not empty. The assertion !ssize.empty() ensures that the function does not process an empty image, which is a common cause of the error.

In this article, we'll explore the common causes of this error and how to resolve it.

Understanding the cv::resize Function

The cv::resize function in OpenCV is used to resize images. It takes the following parameters:

  • src: The source image to be resized.
  • dst: The destination image where the resized image will be stored.
  • dsize: The desired size of the output image.
  • fx: The scale factor along the horizontal axis.
  • fy: The scale factor along the vertical axis.
  • interpolation: The interpolation method to be used.

The cv::resize function is protected by an assertion statement to check if the source image size (ssize) is not empty. The assertion !ssize.empty() ensures that the function does not process an empty image, an image which is corrupted or unreadable, or an image that is not loaded correctly. When the assertion fails, the error (-215: Assertion failed) !ssize.empty() in function cv::resize is triggered.

Tip: When working with image processing in OpenCV, always verify the integrity of your image files. Check that the file paths are correct and the files exist in your filesystem before loading them into your program. This practice helps prevent common errors associated with file path issues or corrupted image files, ensuring smoother processing and debugging.

Common Scenarios Leading to the Error

Some common scenarios that can lead to this error are:
- Image path not loaded correctly
- Corrupted image files
- Insufficient permissions

1. Image Not Loaded Properly

import cv2

# Incorrect path leading to a failure in loading the image
image = cv2.imread('nonexistent/path/to/image.jpg')
resized_image = cv2.resize(image, (100, 100))

Output:

error: OpenCV(4.x) (.../modules/imgproc/src/resize.cpp:4045: error: (-215:Assertion failed) !ssize.empty() in function 'resize'

The image path is incorrect, resulting in cv2.imread returning None. Attempting to resize a non-existent image triggers the error. When the image is not loaded correctly, the input to cv::resize is empty, triggering the error.

2. Corrupted Image Files

import cv2

# Trying to load a corrupted image file
image = cv2.imread('path/to/corrupted/image.jpg')
resized_image = cv2.resize(image, (100, 100))

Output:

error: OpenCV(4.x) (.../modules/imgproc/src/resize.cpp:4045: error: (-215:Assertion failed) !ssize.empty() in function 'resize' 

The image file is corrupted or unreadable, leading to a failure in loading the image. When the image is not loaded correctly, the input to cv::resize is empty, triggering the error.

3. Insufficient Permissions.

import cv2

# Image file with restricted permissions
image = cv2.imread('path/to/restricted/image.jpg')
resized_image = cv2.resize(image, (100, 100))

Output:

error: OpenCV(4.x) (.../modules/imgproc/src/resize.cpp:4045: error: (-215:Assertion failed) !ssize.empty() in function 'resize'

Lack of appropriate permissions prevents the image from being read, resulting in an empty input to cv::resize.

FAQ Can this error occur with other OpenCV functions?
Yes, similar errors can occur if the image is not loaded correctly. Functions that manipulate or analyze images rely on valid image inputs. Errors related to null or empty images are common across various OpenCV functions.
Is it necessary to check the image after every operation?
While not mandatory, it's a good practice to verify the image's validity after operations that could alter or affect it. This step ensures that subsequent functions in your code do not encounter null or invalid image data, preventing runtime errors.

Solutions: How to Fix the Error

Solution 1: Verify Image Path and File Integrity

Check the file permissions and ensure the user has read and write permissions on the image file. Always use the complete path in places where the image is located outside your environment or the root folder of your project.

import cv2

# Corrected image path
image = cv2.imread(`correct/path/to/image.jpg')

# Check if the image is loaded correctly
if image is not None:
    resized_image = cv2.resize(image, (100, 100))
    print("Image resized successfully.")
else:
    print("Error: Image not loaded. Check the file path.")

In the above code snippet, we check if the image is loaded correctly before proceeding to resize it. This step ensures that the input to cv::resize is not empty, preventing the error. Incase the image is not loaded correctly, we print an error message.

To catch the error if the image has no sufficient write permissions, we can use a try-except block.

import cv2

# Attempting to load an image
try:
    image = cv2.imread('path/to/image.jpg')
except OSError as e:
    print(f"Error: {e}")

# Check if the image is loaded correctly
if image is not None:
    resized_image = cv2.resize(image, (100, 100))
    print("Image resized successfully.")
else:
    print("Error: Image not loaded. Check the file path and file permissions.")
    

Output:

Image resized successfully.

This solution ensures that the image path is correct and the file is readable. By validating the image loading process, we prevent the resizing function from receiving an empty input.

Solution 2: Handle Image Loading Failures

Image loading failures can be handled by checking if the image is loaded correctly before proceeding to resize it. This step ensures that the input to cv::resize is not empty, preventing the error.

import cv2

# Attempting to load an image
image = cv2.imread('path/to/image.jpg')

# Validate image loading
if image is None:
    print("Failed to load image. Check the file path or file integrity.")
else:
    resized_image = cv2.resize(image, (100, 100))
    print("Image loaded and resized successfully.")

In the above code snippet, we check if the image is loaded correctly before proceeding to resize it. This step ensures that the input to cv::resize is not empty, preventing the error. Incase the image is not loaded correctly, we print an error message.

Output:

Image loaded and resized successfully.

This approach involves checking whether the image is loaded correctly before proceeding to resize it. It's a crucial step for debugging and ensuring the reliability of the code, especially for beginners.

FAQ Q: What does the assertion `!ssize.empty()` check in OpenCV?
A: It checks that the source image size is not empty before processing, which is crucial to avoid errors during image resizing operations.

Using imread and resize Together

The imread and resize functions are commonly used together in OpenCV. The imread function is used to load images, while the resize function is used to resize images. The imread function is protected by an assertion statement to check if the image is loaded correctly. The assertion !img.empty() ensures that the function does not process an empty image, which is a common cause of the error.

import cv2

# Attempting to load an image
image = cv2.imread('path/to/image.jpg')

# Validate image loading
if image is None:
    print("Failed to load image. Check the file path or file integrity.")
else:
    resized_image = cv2.resize(image, (100, 100))
    print("Image loaded and resized successfully.")

In the above code snippet, we check if the image is loaded correctly before proceeding to resize it. This step ensures that the input to cv::resize is not empty, preventing the error. Incase the image is not loaded correctly, we print an error message.

Note: The `imread` function in OpenCV is used to load an image from a specified file path. It's crucial to ensure that the path provided to `imread` is accurate and the file format is compatible with OpenCV. Supported formats include JPEG, PNG, BMP, and others. If `imread` fails to find the file or if the file is not in a supported format, it will return an empty matrix, which can lead to further errors in image processing.

Conclusion: Preventing Future Errors

Understanding the root causes of this error is key to avoiding it in future projects. Proper file path handling, ensuring file integrity, and appropriate error checking are essential best practices in programming. Functions that manipulate or analyze images rely on valid image inputs. Errors related to null or empty images are common across various OpenCV functions. Using imread and resize together is a common practice in OpenCV. The imread function is protected by an assertion statement to check if the image is loaded correctly. The assertion !img.empty() ensures that the function does not process an empty image, which is a common cause of the error. In this article, we explored the common causes of this error and how to resolve it. We also discussed best practices for handling image files and preventing future errors. Understanding the root causes of this error is key to avoiding it in future projects. Proper file path handling, ensuring file integrity, and appropriate error checking are essential best practices in programming. By implementing these solutions, we can effectively manage and prevent common errors in OpenCV, paving the way for smoother coding experiences, especially for those just starting in the field of computer vision and image processing.

Further Reading

  • OpenCV Documentation: Detailed documentation on the `cv::resize` function and image processing in OpenCV.
  • Python File Handling Guide: An introductory guide to handling files and paths in Python, which is crucial for loading images correctly.
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