How do I try to search with my own data, I want to take my own data set and organize it in that form

[jxhoh]

self.database_utms = np.array([(path.split("@")[1], path.split("@")[2]) for path in self.database_paths]).astype(np.float)
self.queries_utms = np.array([(path.split("@")[1], path.split("@")[2]) for path in self.queries_paths]).astype(np.float)
I don't understand these two lines of code

[Lu-Feng]

The dataset preparation follows visual geo-localization benchmark. If you want to use it on your own dataset, you'll need to rewrite the image names in this standard format:
@ UTM_east @ UTM_north @ UTM_zone_number @ UTM_zone_letter @ latitude @ longitude @ pano_id @ tile_num @ heading @ pitch @ roll @ height @ timestamp @ note @ extension
where the only indispensable values are UTM coordinates (UTM_east and UTM_north). The character @ is used as the separator. So we can use path.split("@")[1], path.split("@")[2] to get the UTM coordinates, which are further used to calculate geographical distances.

[Lu-Feng]

If your images are labeled by latitude and longitude, you need to convert it to get UTM coordinates. If they are annotated by frame-level correspondence, you can create pseudo UTM coordinates. For example, you can rewrite the name of the i-th image in the Nordland-test dataset to @i@0@@@@@@@@@@@@@.jpg, and set the evaluation parameter val_positive_dist_threshold to 2 (i.e. the threshold is 2 frames).

[jxhoh]

假如我的数据，没有任何标识，我就是想从一大堆图片中找出 最相似的图像呢，虽然这样听起来不像地理定位，但是有时候更多的场景是盲定位吧

[Lu-Feng]

那估计还是得按这个命名格式改一下图片名字，你可以把原来的名字写到@note那个字段，然后开头的UTM坐标的两个值随便给（我不确定不赋值会不会报错，你也可以试一下留成空的），在计算完predictions之后直接输出结果就行，就不再计算Recall@N指标了

[jxhoh]

对，我试过了，不赋值是报错的，对，任何直接计算pre就行，这样就可以用做盲定位了