ddddsr 0.1.2

end-to-end super resolution toolkit

ddddsr

A python library for end-to-end image super-resolution.

Install

pip install ddddsr

Features

• End-to-end super resolution in one package (currently support waifu2x models).

• (experimental) OCR for better text super resolution quality.

Usage

import ddddsr
import cv2

# default is 2x upscaling on CPU using waifu2x cunet.
sr = ddddsr.SR()
x = cv2.imread('input.jpg', cv2.IMREAD_UNCHANGED)
y = sr.run(x)
cv2.imwrite('output.png', y)

API reference:

sr = ddddsr.SR( 
    # models: currently supports ['waifu2x_art', 'waifu2x_photo']
    model: str = 'waifu2x_art', 
    # scale
    scale: Optional[float] = None, 
    # output size (omitted if scale is set, if both scale and size are None, use scale = 2)
    size: Optional[Union[int, List[int], Tuple[int]]] = None, 
    # denoise level: range in [-1, 3], -1 means no denoising.
    denoise_level: int =  2, 
    # whether to use gpu
    use_gpu: bool = False, 
    # if use gpu, set the device id
    device_id: int = 0,
    # (experimental) use OCR for better text quality
    ocr_text: bool = False,
    # (experimental) OCR related configurations
    ocr_font_size: int = 28,
    ocr_font_color: Union[Tuple[int], List[int]] = (0, 0, 0),
    ocr_background_color: Union[Tuple[int], List[int]] = (255, 255, 255),
    ocr_font_ttf: Optional[str] = None, # path for ttf font file
)

sr.run(
    # image file, support [H, W, 3] or [H, W, 4]
    image: np.ndarray,
    # slide window size, -1 means no slide window. Change to e.g. 128 or 256 if OOM.
    window: int = -1,
)

References

• The original waifu2x.

• ONNX models are from waifu2x-onnx.

• OCR models are from ppocr-onnx and PaddleOCR.