Java 类名：com.alibaba.alink.pipeline.image.WriteTensorToImage
Python 类名：WriteTensorToImage

功能介绍

将张量列转换为图片，并写入根目录对应的相对路径列中，然后原样输出结果。

参数说明

名称 中文名称 描述 类型 是否必须？ 取值范围 默认值
relativeFilePathCol 文件路径列 文件路径列 String ✓
rootFilePath 文件路径 文件路径 String ✓
tensorCol tensor列 tensor列 String ✓
imageType 图片类型 图片类型 String “PNG”, “JPEG” “PNG”
reservedCols 算法保留列名 算法保留列 String[] null

代码示例

Python 代码

  1. df_data = pd.DataFrame([
  2.     'sphx_glr_plot_scripted_tensor_transforms_001.png'
  3. ])
  5. batch_data = BatchOperator.fromDataframe(df_data, schemaStr = 'path string')
  7. readImageToTensorBatchOp = ReadImageToTensorBatchOp()\
  8.     .setRootFilePath("https://pytorch.org/vision/stable/_images/")\
  9.     .setRelativeFilePathCol("path")\
  10.     .setOutputCol("tensor")
  12. writeTensorToImageBatchOp = WriteTensorToImageBatchOp()\
  13.             .setRootFilePath("/tmp/write_tensor_to_image")\
  14.             .setTensorCol("tensor")\
  15.             .setImageType("png")\
  16.             .setRelativeFilePathCol("path")
  18. batch_data.link(readImageToTensorBatchOp).link(writeTensorToImageBatchOp).print()

Java 代码

  1. import org.apache.flink.types.Row;
  3. import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
  4. import com.alibaba.alink.params.image.HasImageType.ImageType;
  5. import com.alibaba.alink.pipeline.image.WriteTensorToImage;
  6. import org.junit.Test;
  8. import java.util.Collections;
  9. import java.util.List;
  11. public class WriteTensorToImageTest {
  13.     @Test
  14.     public void testWriteTensorToImage() throws Exception {
  16.         List <Row> data = Collections.singletonList(
  17.             Row.of("sphx_glr_plot_scripted_tensor_transforms_001.png")
  18.         );
  20.         MemSourceBatchOp memSourceBatchOp = new MemSourceBatchOp(data, "path string");
  22.         ReadImageToTensorBatchOp readImageToTensorBatchOp = new ReadImageToTensorBatchOp()
  23.             .setRootFilePath("https://pytorch.org/vision/stable/_images/")
  24.             .setRelativeFilePathCol("path")
  25.             .setOutputCol("tensor");
  27.         WriteTensorToImage writeTensorToImageBatchOp = new WriteTensorToImage()
  28.             .setRootFilePath("/tmp/write_tensor_to_image")
  29.             .setTensorCol("tensor")
  30.             .setImageType(ImageType.PNG)
  31.             .setRelativeFilePathCol("path");
  33.         writeTensorToImageBatchOp.transform(memSourceBatchOp.link(readImageToTensorBatchOp)).print();
  34.     }
  36. }

运行结果

可以在 /tmp/write_tensor_to_image/sphx_glr_plot_scripted_tensor_transforms_001.png 中找到 https://pytorch.org/vision/stable/_images/sphx_glr_plot_scripted_tensor_transforms_001.png
同时组件的输出结果为：
| path | tensor |
|—————————————————————————+————————————————|
| sphx_glr_plot_scripted_tensor_transforms_001.png | FLOAT#250,520,4#255.0 255.0… |