panorama-yolox-preprocess.py

import cv2

class Application(panoramasdk.node):
    
    # ...

    def preprocess(self, img, input_size, swap=(2, 0, 1)):
        if len(img.shape) == 3:
            padded_img = np.ones((input_size[0], input_size[1], 3), dtype=np.uint8) * 114
        else:
            padded_img = np.ones(input_size, dtype=np.uint8) * 114

        r = min(input_size[0] / img.shape[0], input_size[1] / img.shape[1])
        resized_img = cv2.resize(
            img,
            (int(img.shape[1] * r), int(img.shape[0] * r)),
            interpolation=cv2.INTER_LINEAR,
        ).astype(np.uint8)
        padded_img[: int(img.shape[0] * r), : int(img.shape[1] * r)] = resized_img

        padded_img = padded_img.transpose(swap)
        padded_img = np.ascontiguousarray(padded_img, dtype=np.float32)
        return padded_img, r