Function

Resizes the decoded YUV and RGB images with the specified width and height.

YUV_420 supports both 4K and 8K images.
Other types of YUV images, such as YUV422 and YUV444, support only 4K images.
The RGB format can be RGB888 or BGR888.

Synchronous/Asynchronous (Status)

Asynchronous

Constraints

Formats that support both 4K and 8K images:

MXPI_PIXEL_FORMAT_YUV_SEMIPLANAR_420 = 1, // 1, YUV420SP NV12 8bit
MXPI_PIXEL_FORMAT_YVU_SEMIPLANAR_420 = 2, // 2, YUV420SP NV21 8bit

Formats that support only 4K images:

MXPI_PIXEL_FORMAT_YUV_400 = 0, // 0, YUV400 8bit
MXPI_PIXEL_FORMAT_YUV_SEMIPLANAR_422 = 3, // 3, YUV422SP NV12 8bit
MXPI_PIXEL_FORMAT_YVU_SEMIPLANAR_422 = 4, // 4, YUV422SP NV21 8bit
MXPI_PIXEL_FORMAT_YUV_SEMIPLANAR_444 = 5, // 5, YUV444SP NV12 8bit
MXPI_PIXEL_FORMAT_YVU_SEMIPLANAR_444 = 6, // 6, YUV444SP NV21 8bit
MXPI_PIXEL_FORMAT_YUYV_PACKED_422 = 7, // 7, YUV422P YUYV 8bit
MXPI_PIXEL_FORMAT_UYVY_PACKED_422 = 8, // 8, YUV422P UYVY 8bit
MXPI_PIXEL_FORMAT_YVYU_PACKED_422 = 9, // 9, YUV422P YVYU 8bit
MXPI_PIXEL_FORMAT_VYUY_PACKED_422 = 10, // 10, YUV422P VYUY 8bit
MXPI_PIXEL_FORMAT_YUV_PACKED_444 = 11, // 11, YUV444P 8bit
MXPI_PIXEL_FORMAT_RGB_888 = 12,        // 12, RGB888 8bit
MXPI_PIXEL_FORMAT_BGR_888 = 13,        // 13, BGR888 8bit

The width and height of an 8K image range from 32 to 8192. The width and height of a 4K image range from 32 to 4096.

Plugin Base Class (Factory)

mxpi_imageresize

Input/Output

Input: buffer (data type: MxpiBuffer), metadata (data type: MxpiVisionList)
Output: buffer (data type: MxpiBuffer), metadata (data type: MxpiVisionList)

Port Format (Caps)

Static input: {"image/yuv","metadata/object","image/rgb"}
Static output: {"image/yuv","image/rgb"}

Property

For details, see Table 1.

**Table 1** mxpi_imageresize plugin properties
Property Name	Description	Mandatory or Not	Modifiable or Not
deviceId	Device ID, which is specified by the deviceId property in the stream_config field. You do not need to set the ID.	No	Yes
removeParentData	Whether to remove the original buffer data. The default value is 0. 0: retains the original buffer data. 1: removes the original buffer data.	No	Yes
parentName	Index of the input data (generally the name of the upstream element). This property will not evolve. Therefore, use dataSource instead.	No	Yes
dataSource	Index of the input data (generally the name of the upstream element). The default value is the key value of the output port of the upstream plugin.	Recommended	Yes
resizeHeight	Height after resizing in Resizer_Stretch and Resizer_KeepAspectRatio_Fit modes. By default, the image height of the downstream inference plugin is automatically adapted. The value range is [6, 4096]. The height after resizing is automatically 2-pixel aligned. You are advised to 2-pixel align the height of the resized image and ensure that it is within [1/32, 16] of the height in the image resolution. If the downstream of the resizing plugin is not an inference plugin, the resizing width and height must be set. If the downstream of the resizing plugin is an inference plugin, you do not need to set the resizing width and height, which can be automatically obtained.	No	Yes
resizeWidth	Width after resizing in Resizer_Stretch and Resizer_KeepAspectRatio_Fit modes. By default, the image width of the downstream inference plugin is automatically adapted. The value range is [32, 4096]. The width after resizing is automatically 16-pixel aligned. You are advised to 16-pixel align the width of the resized image and ensure that it is within [1/32, 16] of the width in the image resolution. If the downstream of the resizing plugin is not an inference plugin, the resizing width and height must be set. If the downstream of the resizing plugin is an inference plugin, you do not need to set the resizing width and height, which can be automatically obtained.	No	Yes
maxDimension	Maximum length of the resized image in Fast R-CNN resizing mode	No	Yes
minDimension	Minimum length of the resized image in Fast R-CNN resizing mode	No	Yes
resizeType	Resizing mode: Resizer_Stretch: indicates the stretching mode, which is the default resizing mode. OpenCV and Ascend modes are supported. Resizer_KeepAspectRatio_FastRCNN: corresponds to the Fast R-CNN resizing mode. OpenCV and Ascend modes are supported. Resizer_KeepAspectRatio_Fit: resizes the image proportionally to maximize the image area within the specified width and height. OpenCV and Ascend modes are supported. Resizer_OnlyPadding: supports padding only. OpenCV and Ascend modes are supported. Resizer_KeepAspectRatio_Long: proportionally resizes the maximum edge to a specified value. Only OpenCV is supported. Resizer_KeepAspectRatio_Short: proportionally resizes the minimum edge to a specified value. Only OpenCV is supported. Resizer_Rescale: performs the stretching and resizing proportionally based on the smaller ratio of the length and width. Only OpenCV is supported. Resizer_Rescale_Double: performs the stretching and resizing proportionally based on the smaller ratio of the length and width twice. Only OpenCV is supported. Resizer_PaddleOCR: performs height-based resizing with the aspect ratio preserved. Only OpenCV is supported. Resizer_MS_Yolov4: corresponds to the resizing mode of the YOLOv4 model. Only OpenCV is supported.	No	Yes
scaleValue	Value for image resizing. The default value is 32. The value range is [32, 8192]. Resizer_KeepAspectRatio_Long: resizes the maximum edge to a specified value. Resizer_KeepAspectRatio_Short: resizes the minimum edge to a specified value.	No	Yes
RGBValue	Value for color padding. Enter the R, G, and B values in sequence. By default, the value is empty and color padding is not performed. The default background color of DVPP is used. Only Ascend is supported.	No	Yes
interpolation	Interpolation mode of the resize plugin. The default value is 0. The following algorithms are supported by the Atlas 200/300/500 inference product: 0 (default): Huawei-developed high-order filtering algorithm. 1: conventional bilinear algorithm, whose compute accuracy is close to that of OpenCV. 2: conventional nearest neighbor algorithm, whose compute accuracy is close to that of OpenCV. 3: conventional bilinear algorithm, whose compute accuracy is close to that of TensorFlow. 4: conventional nearest neighbor algorithm, whose compute accuracy is close to that of TensorFlow. The following algorithms are supported by the Atlas 200I/500 A2 inference product: 0 (default): Huawei-developed high-order filtering algorithm. 1: conventional bilinear algorithm, whose compute accuracy is close to that of OpenCV. 2: conventional nearest neighbor algorithm, whose compute accuracy is close to that of OpenCV. 3: conventional bilinear algorithm, whose compute accuracy is close to that of TensorFlow. 4: conventional nearest neighbor algorithm, whose compute accuracy is close to that of TensorFlow. The following algorithms are supported by the Atlas inference product: 0 (default) and 1: conventional bilinear algorithm, whose compute process is similar to that of OpenCV. When the input and output images are both in RGB format and the resizing range is [1/32, 512], the maximum value difference of a single pixel from OpenCV is ±1. 2: conventional nearest neighbor algorithm, whose compute process is close to that of OpenCV.	No	Yes
cvProcessor	Processing method: ascend (default): Ascend DVPP interfaces are called for processing. opencv: OpenCV interfaces are called for processing.	No	Yes
paddingType	Padding mode: Padding_NO (default): no padding (for both Ascend and OpenCV). Padding_RightDown: padding in the lower right corner (for OpenCV only). Padding_Around: padding in the upper, lower, left, and right corner (for both Ascend and OpenCV).	No	Yes
paddingHeight	Height of the padded image, which must be greater than the height of the resized image. (This property takes effect only in OpenCV processing.)	No	Yes
paddingWidth	Width of the padded image, which must be greater than the width of the resized image. (This property takes effect only in OpenCV processing.)	No	Yes
paddingColorB	Color blue of the padded image. The value can be a floating point number ranging from 0 to 255. Only OpenCV is supported.	No	Yes
paddingColorG	Color green of the padded image. The value can be a floating point number ranging from 0 to 255. Only OpenCV is supported.	No	Yes
paddingColorR	Color red of the padded image. The value can be a floating point number ranging from 0 to 255. Only OpenCV is supported.	No	Yes
handleMethod	Reserved property. Use cvProcessor. Processing method: ascend (default) opencv	No	Yes