49 lines
1.2 KiB
Markdown
49 lines
1.2 KiB
Markdown
# yolov11_cls_inference README
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## 概述
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该模块用于对米厂输入图像执行二分类推理，用于判断机械臂夹爪是否夹紧。
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类别定义：
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0 → 夹具未夹紧 (False)
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1 → 夹具夹紧 (True)
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rknn模型只加载一次，复用全局实例，提高推理效率。
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## 调用示例
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您可以直接调用 yolov11_cls_inference 函数，以便集成到其他项目中：
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示例 1: 测试仅获取单张图片的类别和布尔值
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```bash
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from yolov11_cls_inference import yolov11_cls_inference
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import cv2
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# 读取图像
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bgr_image = cv2.imread("11.jpg")
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rgb_image = cv2.cvtColor(bgr_image, cv2.COLOR_BGR2RGB)
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# 调用推理函数
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class_id, bool_value = yolov11_cls_inference(
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model_path="yolov11_cls.rknn",
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raw_image=rgb_image,
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target_size=(640, 640)
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)
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print(f"类别ID: {class_id}, 布尔值: {bool_value}")
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```
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示例 2: 直接在其他项目中集成使用
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```bash
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from yolov11_cls_inference import yolov11_cls_inference
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# raw_image 已经读取或处理好的图像
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class_id, bool_value = yolov11_cls_inference(model_path="yolov11_cls.rknn", raw_image=raw_image)
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if bool_value:
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print("夹具夹紧")
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else:
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print("夹具未夹紧")
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```
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