std.image

Decode, transform and encode PNG and JPEG. This is also what backs image input to ai.

import std.image

img = image.load("photo.jpg")
print(image.width(img))
print(image.height(img))
print(image.dimensions(img))

small = image.resize(img, 512, 512)
part  = image.crop(img, 10, 10, 100, 100)

image.save(small, "thumb.png")
data = image.encode(small, "png")
img2 = image.decode(bytes_from_somewhere)

image.free(img)

Handles

An image is a handle, not a value you copy around - which is why free exists. A handle holds decoded pixels, and a large photograph is a lot of memory: a 4000×3000 image is tens of megabytes decoded regardless of how small the JPEG was.

Free handles you are finished with in a loop over many files, and be conscious of how many you hold at once.

Feeding ai

ai "what does this chart show?" on image.load("chart.png")

A transform pipeline flows straight in, and resizing first is usually the right move:

ai "read the label" on image.resize(photo, 1024, 1024)

Images are tokens, often a great many. A 4000-pixel photograph rarely answers a question better than a 1000-pixel one and costs several times more. See Multimodal.

Formats

PNG and JPEG, in and out. PNG is lossless and right for screenshots, charts and anything with text or sharp edges; JPEG is lossy and right for photographs. Re-encoding a JPEG loses quality each time, so transform from the original where you can.

Untrusted images

Decoding attacker-supplied image data means running a decoder over hostile input, and a small file can decode to an enormous bitmap. Check dimensions before resizing, and bound what you accept:

img = image.decode(upload)
d = image.dimensions(img)
if d.width * d.height > 40000000 { image.free(img) ; reject("too large") }