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| import cv2 | |
| import warnings | |
| import numpy as np | |
| from pathlib import Path | |
| from hloc import logger | |
| from common.utils import ( | |
| get_matcher_zoo, | |
| load_config, | |
| device, | |
| ROOT, | |
| ) | |
| from common.api import ImageMatchingAPI | |
| def test_all(config: dict = None): | |
| img_path1 = ROOT / "datasets/sacre_coeur/mapping/02928139_3448003521.jpg" | |
| img_path2 = ROOT / "datasets/sacre_coeur/mapping/17295357_9106075285.jpg" | |
| image0 = cv2.imread(str(img_path1))[:, :, ::-1] # RGB | |
| image1 = cv2.imread(str(img_path2))[:, :, ::-1] # RGB | |
| matcher_zoo_restored = get_matcher_zoo(config["matcher_zoo"]) | |
| for k, v in matcher_zoo_restored.items(): | |
| if image0 is None or image1 is None: | |
| logger.error("Error: No images found! Please upload two images.") | |
| enable = config["matcher_zoo"][k].get("enable", True) | |
| if enable: | |
| logger.info(f"Testing {k} ...") | |
| api = ImageMatchingAPI(conf=v, device=device) | |
| api(image0, image1) | |
| log_path = ROOT / "experiments" / "all" | |
| log_path.mkdir(exist_ok=True, parents=True) | |
| api.visualize(log_path=log_path) | |
| else: | |
| logger.info(f"Skipping {k} ...") | |
| def test_one(): | |
| img_path1 = ROOT / "datasets/sacre_coeur/mapping/02928139_3448003521.jpg" | |
| img_path2 = ROOT / "datasets/sacre_coeur/mapping/17295357_9106075285.jpg" | |
| image0 = cv2.imread(str(img_path1))[:, :, ::-1] # RGB | |
| image1 = cv2.imread(str(img_path2))[:, :, ::-1] # RGB | |
| # sparse | |
| conf = { | |
| "feature": { | |
| "output": "feats-superpoint-n4096-rmax1600", | |
| "model": { | |
| "name": "superpoint", | |
| "nms_radius": 3, | |
| "max_keypoints": 4096, | |
| "keypoint_threshold": 0.005, | |
| }, | |
| "preprocessing": { | |
| "grayscale": True, | |
| "force_resize": True, | |
| "resize_max": 1600, | |
| "width": 640, | |
| "height": 480, | |
| "dfactor": 8, | |
| }, | |
| }, | |
| "matcher": { | |
| "output": "matches-NN-mutual", | |
| "model": { | |
| "name": "nearest_neighbor", | |
| "do_mutual_check": True, | |
| "match_threshold": 0.2, | |
| }, | |
| }, | |
| "dense": False, | |
| } | |
| api = ImageMatchingAPI(conf=conf, device=device) | |
| api(image0, image1) | |
| log_path = ROOT / "experiments" / "one" | |
| log_path.mkdir(exist_ok=True, parents=True) | |
| api.visualize(log_path=log_path) | |
| # dense | |
| conf = { | |
| "matcher": { | |
| "output": "matches-loftr", | |
| "model": { | |
| "name": "loftr", | |
| "weights": "outdoor", | |
| "max_keypoints": 2000, | |
| "match_threshold": 0.2, | |
| }, | |
| "preprocessing": { | |
| "grayscale": True, | |
| "resize_max": 1024, | |
| "dfactor": 8, | |
| "width": 640, | |
| "height": 480, | |
| "force_resize": True, | |
| }, | |
| "max_error": 1, | |
| "cell_size": 1, | |
| }, | |
| "dense": True, | |
| } | |
| api = ImageMatchingAPI(conf=conf, device=device) | |
| api(image0, image1) | |
| log_path = ROOT / "experiments" / "one" | |
| log_path.mkdir(exist_ok=True, parents=True) | |
| api.visualize(log_path=log_path) | |
| if __name__ == "__main__": | |
| import argparse | |
| config = load_config(ROOT / "common/config.yaml") | |
| test_one() | |
| test_all(config) | |