| 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)) |
|
|