Python: Read and write TIFF 16 bit , three channel , colour images

Python: Read and write TIFF 16 bit , three channel , colour images

To read and write 16-bit, three-channel color images in TIFF format in Python, you can use the imageio library. Here's how you can do it:

  1. Install imageio Library:

    If you haven't already installed the imageio library, you can do so using pip:

    pip install imageio[ffmpeg]

    The [ffmpeg] extra is added to support reading and writing video files, but it's not required for basic image reading and writing.

  2. Reading a TIFF Image:

    You can use imageio.imread() to read a TIFF image:

    import imageio # Read the TIFF image image = imageio.imread('input_image.tif') # Check the image shape (height, width, channels) print(f'Image shape: {image.shape}')

  3. Writing a TIFF Image:

    To write a 16-bit, three-channel color image to a TIFF file, you can use imageio.imsave():

    import imageio # Assuming you have a NumPy array with your image data called "image_data" # Replace 'image_data' with your actual image data image_data = ... # Replace with your image data # Write the image to a TIFF file imageio.imsave('output_image.tif', image_data.astype('uint16'))

    In the above code, you need to replace 'output_image.tif' with the desired output file name and provide your image data as a NumPy array with a data type of 'uint16' to ensure it's treated as a 16-bit image.

Make sure to replace 'input_image.tif' with the path to your input image file and customize the output file name and image data according to your specific use case.

With the imageio library, you can easily read and write 16-bit, three-channel color images in TIFF format.

Examples

  1. "Python: How to read 16-bit TIFF images with three color channels?"

    • Description: This query discusses how to read 16-bit TIFF images with three color channels, typically RGB.
    • Code:
      # Install required library !pip install Pillow 
    from PIL import Image # Load a 16-bit TIFF image with three channels (RGB) image = Image.open("image_16bit.tif") image.show() # Display the image

  2. "Python: How to write 16-bit TIFF images with three color channels?"

    • Description: This query explains how to write or save a 16-bit TIFF image with three color channels using Pillow or similar libraries.
    • Code:
      from PIL import Image import numpy as np # Create a 16-bit, three-channel image (example data) width, height = 100, 100 data = np.random.randint(0, 65535, (height, width, 3), dtype=np.uint16) # Create and save the TIFF image image = Image.fromarray(data, "RGB") image.save("output_image_16bit.tif", format="TIFF", bits=16)

  3. "Python: How to convert a 16-bit TIFF image to another format?"

    • Description: This query shows how to convert a 16-bit TIFF image to a different format, such as PNG or JPEG.
    • Code:
      from PIL import Image # Open a 16-bit TIFF image image = Image.open("image_16bit.tif") # Save as a PNG file image.save("converted_image.png", format="PNG")

  4. "Python: How to read metadata from a 16-bit TIFF image?"

    • Description: This query explains how to read metadata, such as EXIF data, from a 16-bit TIFF image.
    • Code:
      from PIL import Image # Open a 16-bit TIFF image image = Image.open("image_16bit.tif") # Extract metadata metadata = image.tag_v2 for tag, value in metadata.items(): print(f"{tag}: {value}")

  5. "Python: How to apply image processing on 16-bit TIFF images?"

    • Description: This query demonstrates basic image processing on 16-bit TIFF images, like resizing or filtering.
    • Code:
      from PIL import Image, ImageFilter # Open a 16-bit TIFF image image = Image.open("image_16bit.tif") # Apply a simple image processing operation, like blurring blurred_image = image.filter(ImageFilter.GaussianBlur(5)) blurred_image.show() # Display the processed image

  6. "Python: How to read and write 16-bit TIFF images with OpenCV?"

    • Description: This query shows how to read and write 16-bit TIFF images using OpenCV, which provides a flexible alternative to Pillow.
    • Code:
      # Install OpenCV if not installed !pip install opencv-python 
    import cv2 # Read a 16-bit TIFF image image = cv2.imread("image_16bit.tif", cv2.IMREAD_UNCHANGED) # Write the image to a new TIFF file cv2.imwrite("output_image_16bit.tif", image)

  7. "Python: How to visualize 16-bit TIFF images?"

    • Description: This query explains how to visualize 16-bit TIFF images, which might require conversion for proper viewing.
    • Code:
      import numpy as np from PIL import Image # Open a 16-bit TIFF image image = Image.open("image_16bit.tif") # Convert to 8-bit for visualization def to_8bit(img): arr = np.array(img, dtype=np.uint16) return Image.fromarray((arr / 256).astype(np.uint8)) image_8bit = to_8bit(image) image_8bit.show() # Display the converted image

  8. "Python: How to create a new 16-bit TIFF image from scratch?"

    • Description: This query demonstrates creating a 16-bit TIFF image from scratch and filling it with custom data.
    • Code:
      import numpy as np from PIL import Image # Create a 16-bit, three-channel image with specific color (white) width, height = 100, 100 data = np.full((height, width, 3), 65535, dtype=np.uint16) # White color image = Image.fromarray(data, "RGB") image.save("new_16bit_image.tif", format="TIFF", bits=16)

  9. "Python: How to compress 16-bit TIFF images?"

    • Description: This query explains how to apply compression when saving 16-bit TIFF images to reduce file size.
    • Code:
      from PIL import Image import numpy as np # Create a sample 16-bit image width, height = 100, 100 data = np.random.randint(0, 65535, (height, width, 3), dtype=np.uint16) # Create and save with compression (e.g., LZW) image = Image.fromarray(data, "RGB") image.save("compressed_16bit_image.tif", format="TIFF", compression="LZW")

  10. "Python: How to manipulate individual color channels in a 16-bit TIFF image?"

    • Description: This query discusses how to manipulate individual color channels (e.g., R, G, B) in a 16-bit TIFF image.
    • Code:
      import numpy as np from PIL import Image # Open a 16-bit TIFF image image = Image.open("image_16bit.tif") # Separate into individual color channels red, green, blue = image.split() # Modify the red channel (increase brightness) red_array = np.array(red, dtype=np.uint16) red_array = np.clip(red_array + 1000, 0, 65535) # Create new image from modified channel red_modified = Image.fromarray(red_array) new_image = Image.merge("RGB", (red_modified, green, blue)) new_image.show() # Display the modified image

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