Fixes #1659: Convert image mode I;16 to RGB

[haianhng31]

== Summary ==

• Fixes [pdq] ValueError when computing PDQ hash on some pngs #1659
• Convert image mode I;16 to RGB

== Test Plan ==

• Add test cases for images of mode LA, I;16, RGB

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[Dcallies]

Thanks a ton for taking this on! I am convinced by your unittests that your PR fixes this issue, but if you can confirm that you can generate a reproduction of the condition with them in your test plan in the summary, I'll be doubly convinced.

A few concerns about the test images, since they appear to be from reddit user data. We don't want to include images we don't have the rights to.

You have a few options for generating test data:

1. Produce the image yourself (essentially donating it the repo)
2. Algorithmically generate the image by generating noise, random data, etc.
3. Mody images in pdq/data/bridge_pics to generate the case, since those were generated by RFC: Python Library for ThreatExchange #1 by a previous author.

We cannot do:

1. Images on the internet that we find (even if they are sites purporting to be public domain, because people can re-host images there)
2. Known copyrighted images

Can you try and produce a local reproduction by using the bridge pics? That might be nicest because those hashes have a known value.

[16BitNarwhal]

Hi @Dcallies,
Made some changes and generated test images as follows.
I'm not sure why the quality of the i16 (16-bit grayscale) image is at 36 though

from PIL import Image
import numpy as np

width, height = 256, 256

def generate_i16_image():
    noise = np.random.randint(0, 65536, (height, width), dtype=np.uint16)
    image = Image.fromarray(noise, mode='I;16')
    image.save('noise_image_I16.png')

def generate_la_image():
    luminance = np.random.randint(0, 256, (height, width), dtype=np.uint8)
    alpha = np.random.randint(0, 256, (height, width), dtype=np.uint8)
    la_image_data = np.stack((luminance, alpha), axis=-1)
    la_image = Image.fromarray(la_image_data, mode='LA')
    la_image.save('noise_image_LA.png')

def generate_rgb_image():
    red = np.random.randint(0, 256, (height, width), dtype=np.uint8)
    green = np.random.randint(0, 256, (height, width), dtype=np.uint8)
    blue = np.random.randint(0, 256, (height, width), dtype=np.uint8)
    rgb_image_data = np.stack((red, green, blue), axis=-1)
    rgb_image = Image.fromarray(rgb_image_data, mode='RGB')
    rgb_image.save('noise_image_RGB.jpeg', 'JPEG')

generate_i16_image()
generate_la_image()
generate_rgb_image()