Crops the input image and outputs it to the Image object.
For details about the API, see cropping (single image) or cropping (batch).
Before calling the image cropping APIs, prepare the image object to be cropped.

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. Subsequently, the image can be processed by using the image processing APIs to generate a final Image object to be cropped.
Select the one-to-many, one-to-one, or many-to-many cropping mode based on service requirements to construct the corresponding input Rect and output Image.
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, Image def prcoess(): # Image decoding # Initialize the ImageProcessor object. imageProcessor = ImageProcessor(device_id) image_path = "image_data/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 processing (image cropping) crop_para = [Rect(300, 100, 550, 350)] croped_images = imageProcessor.crop(decoded_image, crop_para) if __name__ == "__main__": base.mx_init() # Initialize resources. process() base.mx_deinit() # Deinitialize resources. |