hello，
i'm very interested in the paper. I have some questions about the execution of the entire process.
1."python train.py --machine ws --config configs/cityscapes_monodepth_highres_dec5_crop.yml
python train.py --machine ws --config configs/cityscapes_monodepth_highres_dec6_crop.yml"
Are these two commands referring to the part that says, "During the first 300k iterations, only the depth decoder and the pose network are trained. Afterwards, the depth encoder is fine-tuned with an ImageNet feature distance λF = 1 × 10−2 for another 50k iterations"?
2.What is the difference between "run_experiments.py" and "train.py"?
If I want to follow the training process described in the "Experiments.Training" section of the paper to train the depth network, pose network, and semantic segmentation network, how should I proceed?
hello，
i'm very interested in the paper. I have some questions about the execution of the entire process.
1."python train.py --machine ws --config configs/cityscapes_monodepth_highres_dec5_crop.yml
python train.py --machine ws --config configs/cityscapes_monodepth_highres_dec6_crop.yml"
Are these two commands referring to the part that says, "During the first 300k iterations, only the depth decoder and the pose network are trained. Afterwards, the depth encoder is fine-tuned with an ImageNet feature distance λF = 1 × 10−2 for another 50k iterations"?
2.What is the difference between "run_experiments.py" and "train.py"?
If I want to follow the training process described in the "Experiments.Training" section of the paper to train the depth network, pose network, and semantic segmentation network, how should I proceed?