Haseeb Raja
Haseeb Raja
> ``` > ce_loss = F.cross_entropy(input, target,reduction=self.reduction,weight=self.weight) > pt = torch.exp(-ce_loss) > focal_loss = ((1 - pt) ** self.gamma * ce_loss).mean() > ``` > > While `ce_loss` is correctly `-weight[y_t]log(p[y_t])`,...
> I tried gdb debugger to see more about segmentation fault and here is the output: > > ``` > (tandem) pankhuri@pankhuri-GE76-Raider-11UH:~/tandem/tandem$ gdb --args ./build/bin/tandem_dataset preset=gui result_folder=/home/pankhuri/tandem-dataset/results files=/home/pankhuri/tandem-dataset/images calib=/home/pankhuri/tandem-dataset/camera.txt mvsnet_folder=/home/pankhuri/tandem/tandem/exported/tandem...
@rancheng Hi and thank you for the `docker` support. It couldn't install it with official instructions but the your `dockerfile` helped me. I just wanted to say that maybe update...
> Hello, > > I get this in logs while running tandem for any dataset, > > ``` > (tandem) pankhuri@pankhuri-GE76-Raider-11UH:~/tandem/tandem$ ./build/bin/tandem_dataset preset=gui result_folder=/home/pankhuri/tandem-dataset/results files=/home/pankhuri/tandem-dataset/euroc_tandem_format/V1_01_easy/images calib=/home/pankhuri/tandem-dataset/euroc_tandem_format/V1_01_easy/camera.txt mvsnet_folder=/home/pankhuri/tandem/tandem/exported/tandem mode=1 > loading...
@Windson9 Not really. I ended up using some segmentation methods. It was long time ago so I do not remember all the details. Have a look at this repo, it...
@mahimairaja Can you test the following: https://github.com/pytholic/co-tracker If it is working well, I will open the PR. I cannot test it at the moment, I don't have Ubuntu system.
@pradyumnakulkarni87 Have you figured it out?
Can we please get some guide on this?
@bkhanal-11 Hi. I wrote the following code. ```python3 import glob import open3d as o3d import numpy as np import matplotlib.pyplot as plt class CameraPose: def __init__(self, meta, mat): self.metadata =...
@bkhanal-11 This is how my log.txt looks like. ``` 0 0 1 -1.0 0.0 0.0 0.0 0.0 -1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 1 1...