unlimitedocr-c 0.2.3

Python frontend and native C/Metal inference engine for baidu/Unlimited-OCR

unlimitedocr.c

unlimitedocr.c runs the baidu/Unlimited-OCR model locally with a native C/Metal inference engine and a small Python API for OCR workflows.

Python handles the user-facing pieces — image loading, prompt construction, tokenization, and text decoding. The native library handles model loading, memory management, KV cache, logits processing, and GPU execution.

Quick start

from unlimitedocr_c import UnlimitedOCR

ocr = UnlimitedOCR()
text = ocr.generate("page.png")
print(text)
ocr.close()

Create one UnlimitedOCR instance, reuse it for as many images as you want, and call close() when finished.

from unlimitedocr_c import UnlimitedOCR

ocr = UnlimitedOCR()

for image_path in ["page-1.png", "page-2.png", "page-3.png"]:
    print(ocr.generate(image_path, profile="base"))

ocr.close()

Input types

generate() accepts the common image forms directly:

Input type	Example
local path	ocr.generate("page.png")
URL	ocr.generate("https://example.com/page.jpg")
bytes	ocr.generate(open("page.png", "rb").read())
file-like object	ocr.generate(BytesIO(image_bytes))
PIL image	ocr.generate(Image.open("page.png"))
base64/data URI string	ocr.generate("data:image/png;base64,...")

Example:

from io import BytesIO
from PIL import Image
from unlimitedocr_c import UnlimitedOCR

ocr = UnlimitedOCR()

text_from_path = ocr.generate("page.png")
text_from_url = ocr.generate("https://example.com/page.jpg")
text_from_bytes = ocr.generate(open("page.png", "rb").read())
text_from_file = ocr.generate(BytesIO(open("page.png", "rb").read()))
text_from_pil = ocr.generate(Image.open("page.png"))

ocr.close()