Crops and resizes an input image, and outputs the image to the Image object.
For details about the API, see crop_resize.
Before calling the image cropping and resizing APIs, prepare the image object to be cropped and resized.

Key steps are demonstrated as follows:
Construct the ImageProcessor object. You need to specify the device ID during the construction.
Decode the image based on services to generate an Image object that can be cropped and resized. Subsequently, the image can be processed by using the image processing APIs to generate a final Image object to be cropped and resized.
Based on the service requirements, select different modes to construct the input Rect and Size: single-input single-cropping single-resizing or single-input multi-cropping multi-resizing.
The following is a code example of key steps of functions and features, which is for reference only and cannot be directly copied for execution.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | from mindx.sdk import base from mindx.sdk.base import ImageProcessor, Rect, Size, Image def process(): # Image decoding # Initialize the ImageProcessor object. imageProcessor = ImageProcessor(device_id) image_path = "test_image.jpg" # Read the image path for decoding. The decoding format is nv12 (YUV_SP_420). decoded_image = imageProcessor.decode(image_path, base.nv12) # Image cropping and resizing crop_resize_para = [(Rect(300, 100, 550, 350), Size(100, 100))] crop_resize_image = imageProcessor.crop_resize(decoded_image, crop_resize_para) if __name__ == "__main__": base.mx_init() # Initialize resources. process() base.mx_deinit() # Deinitialize resources. |