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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 |