import numpy import sahi.predict import sahi.utils from PIL import Image TEMP_DIR = "temp" def sahi_yolov8m_inference( image, detection_model, slice_height=512, slice_width=512, overlap_height_ratio=0.1, overlap_width_ratio=0.1, image_size=1024, postprocess_match_threshold=0.75, ): # sliced inference prediction_result = sahi.predict.get_sliced_prediction( image=image, detection_model=detection_model, image_size = image_size, slice_height=slice_height, slice_width=slice_width, overlap_height_ratio=overlap_height_ratio, overlap_width_ratio=overlap_width_ratio, postprocess_match_threshold=postprocess_match_threshold, ) visual_result = sahi.utils.cv.visualize_object_predictions( image=numpy.array(image), object_prediction_list=prediction_result.object_prediction_list, ) output = Image.fromarray(visual_result["image"]) return output