lochenchou / dorn Goto Github PK
View Code? Open in Web Editor NEWDeep Ordinal Regression Network for Monocular Depth Estimation
Deep Ordinal Regression Network for Monocular Depth Estimation
Hey there,
Thanks for your work. Does the code works as expected?
Hi, I trained your code from strach, but the validation result seems not good.
<style> </style>ย | Dataset | cap | Delta 1 | Delta2 | Delta3 | Abs rel | aqua rel | rmse | rmse log |
---|---|---|---|---|---|---|---|---|---|
DORN(paper result) | test set | cap 80 | 0.932 | 0.984 | 0.994 | 0.072 | 0.307 | 2.727 | 0.12 |
DORN(coder result) | val set | cap 80 | 0.446 | 0.576 | 0.667 | 4.532 | 62.5 | 8.82 | 1.14 |
Your code use both image_02 and image_03, but the original paper seems only use one side of the camera, is this right?
Please tell me does the vliad result make sense?
Or I miss using some part of your code?
Or like NYU dataset, I need to do some processing for the downloaded data?
The KITTI data downloaded from KITTI/depth/depth_prediction
Thanks very much!
Hello, your implemention for Dorn on pytorch is very useful. While I can't train it, could you please provide the weight of your resnet?
The location of your code is in: DORN/model/resnet.py line:123
if pretrained: saved_state_dict = torch.load('/datasets/KITTI/depth_prediction/pretrained/resnet101-imagenet.pth', map_location="cpu")
Without this weight, the performance may not good, thanks very much.
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