Closed cl886699 closed 3 years ago
Jakaria08
commented
3 years ago The model that I have uploaded might be trained on Potsdam only (I have several models: trained on the images from separate cities and trained on all data from different cities). I have to recheck the models that I trained. I have a final model trained on the images from different cities, and I will upload if I find it. Thank you for the question.
sagaragarwal2404
commented
3 years ago I tested your pretrained model. I got high score on Potsdam, but low score on Toronto. How dit you select the dataset Did you just train on Potsdam?
Potsdam IoU metric: bbox Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.982 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.990 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.990 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.982 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.985 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.229 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.937 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.993 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.993 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.994 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
Toronto IoU metric: bbox Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.235 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.388 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.246 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.256 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.106 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.270 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.275 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.275 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.280 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
bro I want your help implementing this code.if you could help
Frost-Mactavish
commented
1 year ago 请问你是怎么训练的？我这里很容易就训练跑飞了
I tested your pretrained model. I got high score on Potsdam, but low score on Toronto. How dit you select the dataset Did you just train on Potsdam?
Potsdam IoU metric: bbox Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.982 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.990 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.990 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.982 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.985 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.229 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.937 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.993 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.993 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.994 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
Toronto IoU metric: bbox Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.235 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.388 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.246 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.256 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.106 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.270 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.275 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.275 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.280 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000