70 lines
2.3 KiB
Python
Executable File
70 lines
2.3 KiB
Python
Executable File
# SAM segmentation module for fish detection
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# Uses SAM (Segment Anything Model) for segmentation with boxes from YOLO detection
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import cv2
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import numpy as np
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import torch
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import os
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import argparse
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import urllib.request
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from segment_anything import sam_model_registry, SamPredictor
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from tqdm import tqdm
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def download_models():
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"""
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下载所需的模型文件
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"""
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# 下载 SAM 模型
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sam_model_urls = {
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"vit_h": "https://dl.fbaipublicfiles.com/segment_anything/sam_vit_h_4b8939.pth",
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"vit_l": "https://dl.fbaipublicfiles.com/segment_anything/sam_vit_l_0b3195.pth",
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"vit_b": "https://dl.fbaipublicfiles.com/segment_anything/sam_vit_b_01ec64.pth"
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}
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# 下载 SAM 模型
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sam_checkpoint = "sam_vit_h_4b8939.pth"
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if not os.path.exists(sam_checkpoint):
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print(f"正在下载SAM模型...")
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urllib.request.urlretrieve(sam_model_urls["vit_h"], sam_checkpoint)
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print(f"SAM模型下载完成")
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def init_models(device="cpu", seg_model="sam", yolo_seg_weights=None):
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"""
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初始化模型
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Args:
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device: 运行设备
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seg_model: 分割模型类型 ("sam" 或 "yolov8_seg")
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yolo_seg_weights: YOLOv8分割模型权重路径（当seg_model="yolov8_seg"时必需）
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Returns:
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sam_predictor 或 yolo_seg_model: 分割模型
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"""
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if seg_model == "yolov8_seg":
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# 初始化YOLOv8分割模型
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if yolo_seg_weights is None:
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raise ValueError("使用yolov8_seg时必须提供yolo_seg_weights参数")
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try:
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from ultralytics import YOLO
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except ImportError:
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raise ImportError("未找到 ultralytics，请先安装: pip install ultralytics")
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print(f"正在加载YOLOv8分割模型: {yolo_seg_weights}")
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yolo_seg_model = YOLO(yolo_seg_weights)
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print("YOLOv8分割模型加载成功")
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return yolo_seg_model
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else:
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# 默认使用SAM
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# 下载模型
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download_models()
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# 初始化SAM
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print("正在加载SAM模型...")
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sam = sam_model_registry["vit_h"](checkpoint="sam_vit_h_4b8939.pth")
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sam.to(device=device)
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sam_predictor = SamPredictor(sam)
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print("SAM模型加载成功")
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return sam_predictor
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