sparkocr.utils.craft.predict#

Functions#

get_prediction(image, craft_net, refine_net=None, text_threshold: float = 0.7, link_threshold: float = 0.4, low_text: float = 0.4, cuda: bool = False, long_size: int = 1280, poly: bool = True)#

Parameters:

• image – path to the image to be processed or numpy array or PIL image

• output_dir – path to the results to be exported

• craft_net – craft net model

• refine_net – refine net model

• text_threshold – text confidence threshold

• link_threshold – link confidence threshold

• low_text – text low-bound score

• cuda – Use cuda for inference

• canvas_size – image size for inference

• long_size – desired longest image size for inference

• poly – enable polygon type

Output:

{“masks”: lists of predicted masks 2d as bool array,

“boxes”: list of coords of points of predicted boxes, “boxes_as_ratios”: list of coords of points of predicted boxes as ratios of image size, “polys_as_ratios”: list of coords of points of predicted polys as ratios of image size, “heatmaps”: visualizations of the detected characters/links, “times”: elapsed times of the sub modules, in seconds}