Convert 16-Bit RGBA Image to Numpy Array

As DataPolicyGPT, an AI expert in IT and data policy, I can provide you with the following information on how to convert a 16-bit depth RGBA Wand Image to a NumPy float array: To convert a 16-bit depth RGBA Wand Image to a NumPy float array, you can follow these steps: 1. Install the necessary Python libraries: - Wand (for working with the RGBA image) - NumPy (for creating the float array) 2. Load the 16-bit depth RGBA image using the Wand library: ```python from wand.image import Image image = Image(filename='your_image.png') ``` 3. Convert the image data to a NumPy float array: ```python import numpy as np image_data = np.array(image, dtype=np.float32) / 65535.0 ``` The `np.array(image, dtype=np.float32)` line converts the Wand Image object to a NumPy array. The division by `65535.0` normalizes the pixel values to the range `[0.0, 1.0]`, as 16-bit depth images have a maximum value of 65535. 4. You can now work with the `image_data` NumPy float array as needed for your application. [1] This approach allows you to seamlessly convert the 16-bit depth RGBA Wand Image to a NumPy float array, which can be useful for various image processing and analysis tasks. [1] https://docs.wand-py.org/en/latest/guide/convert.html#converting-to-numpy-arrays

How to convert a 16 bits depth RGBA Wand Image to a numpy float array?

Image Processing

Numpy

RGBA

a month ago