| import argparse | |
| import cv2 | |
| import numpy as np | |
| import axengine as axe | |
| def parse_args() -> argparse.Namespace: | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument( | |
| "--img", | |
| type=str, | |
| required=True, | |
| help="Path to input image.", | |
| ) | |
| parser.add_argument( | |
| "--model", | |
| type=str, | |
| required=True, | |
| help="Path to axmodel model.", | |
| ) | |
| return parser.parse_args() | |
| def infer(img: str, model: str, viz: bool = False): | |
| img_raw = cv2.imread(img) | |
| image = cv2.cvtColor(img_raw, cv2.COLOR_BGR2RGB) | |
| orig_h, orig_w = image.shape[:2] | |
| image = cv2.resize(image, (518,518)) | |
| image = image[None] | |
| session = axe.InferenceSession(model) | |
| depth = session.run(None, {"input": image})[0] | |
| depth = cv2.resize(depth[0, 0], (orig_w, orig_h)) | |
| depth = (depth - depth.min()) / (depth.max() - depth.min()) * 255.0 | |
| depth = depth.astype(np.uint8) | |
| depth_color = cv2.applyColorMap(depth, cv2.COLORMAP_INFERNO) | |
| combined_result = cv2.hconcat([img_raw, depth_color]) | |
| cv2.imwrite("output-ax.png", combined_result) | |
| return depth | |
| if __name__ == "__main__": | |
| args = parse_args() | |
| infer(**vars(args)) | |