38 lines
947 B
Python
38 lines
947 B
Python
from typing import Any
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import numpy as np
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import supervision as sv
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import torch
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from PIL import Image
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from sam2.build_sam import build_sam2
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from sam2.sam2_image_predictor import SAM2ImagePredictor
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SAM_CHECKPOINT = "checkpoints/sam2_hiera_small.pt"
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SAM_CONFIG = "sam2_hiera_s.yaml"
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def load_sam_model(
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device: torch.device,
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config: str = SAM_CONFIG,
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checkpoint: str = SAM_CHECKPOINT
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) -> SAM2ImagePredictor:
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model = build_sam2(config, checkpoint, device=device)
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return SAM2ImagePredictor(sam_model=model)
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def run_sam_inference(
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model: Any,
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image: Image,
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detections: sv.Detections
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) -> sv.Detections:
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image = np.array(image.convert("RGB"))
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model.set_image(image)
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mask, score, _ = model.predict(box=detections.xyxy, multimask_output=False)
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# dirty fix; remove this later
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if len(mask.shape) == 4:
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mask = np.squeeze(mask)
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detections.mask = mask.astype(bool)
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return detections
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