2.0
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@ -26,25 +26,50 @@
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pip install opencv-python numpy rknnlite
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```
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## 函数调用
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## 函数调用1.0
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您也可以直接调用 calculate_offset_from_image 函数,以便集成到其他项目中:
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示例 1: 仅获取偏移量(不画图)
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**
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```bash
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from calculate_offset import calculate_offset_from_image
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result = calculate_offset_from_image("your_image_path.jpg", visualize=False)
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if result['success']:
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print(f"Offset: DeltaX={result['dx_mm']:+.2f} mm, DeltaY={result['dy_mm']:+.2f} mm")
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else:
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print("Error:", result['message'])
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**
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```
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示例 2: 获取偏移量并保存可视化图
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**
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```bash
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from calculate_offset import calculate_offset_from_image
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result = calculate_offset_from_image("your_image_path.jpg", visualize=True)
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**
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```
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该函数返回一个包含下列字段的字典:
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## 函数调用2.0
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示例 1: 仅获取偏移量(不画图)
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```bash
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from caculate_diff2.0 import calculate_offset_from_image
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result = calculate_offset_from_image("11.jpg", visualize=False)
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if result['success']:
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print(f"Offset: DeltaX={result['dx_mm']:+.2f} mm, DeltaY={result['dy_mm']:+.2f} mm")
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else:
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print("Error:", result['message'])
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```
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示例 2: 获取偏移量并保存可视化图
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```bash
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from caculate_diff2.0 import calculate_offset_from_image
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result = calculate_offset_from_image("11.jpg", visualize=True)
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```
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##该函数返回一个包含下列字段的字典1.0:
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success: 成功标志(True/False)
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dx_mm: 水平偏移(毫米)
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@ -52,3 +77,18 @@ result = calculate_offset_from_image("your_image_path.jpg", visualize=True)
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cx: 中心点 x 坐标(像素)
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cy: 中心点 y 坐标(像素)
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message: 错误信息或成功提示
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##该函数返回一个包含下列字段的字典2.0:
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success: 成功标志(True/False)
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dx_mm: 水平偏移(毫米)
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dy_mm: 垂直偏移(毫米)
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cx: 中心点 x 坐标(像素)
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cy: 中心点 y 坐标(像素)
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message: 错误信息或成功提示
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class_id: 检测类别 ID #这里是bag的id是0
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obj_conf: 检测置信度 #这就是识别为料袋的置信度
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bbox: 检测矩形框 [x_left, y_top, width, height]
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message: 错误信息或成功提示
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