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Hello,
I retrained pointnet2 with provided codes on 99 point clouds which are produced by create_train_dataset.py and tested on 11 validation point clouds which are produced by create_train_dataset.py. But it is 6% lower than provided trained model. Does the baseline use a different split?

Thank you very much!

Memory error preventing 3d component of track1-3 metrics from being released. Updated metrics are on the way.

Where can I get access to unrectified images and corrected RPC or affine camera models?

The following is mentioned on page4 of the publication "Metadata such as RPC, epipolar rectifying homographies, and collection dates are retained for each stereo pair" I am not able to find RPC parameters in METADATA.json files or any of the .tif files.

Hello there, it's been several days since the release of the training and validation dataset. Yet I couldn't pull these data to the local till now, though I had registered on the official website to make the links visible, all as guided. For the first few days, the links contained in the BT files seemed invalid, as the resources couldn't be connected. And today found the links to the BT files and the net disks on the official page all gone.

As is the case, could you please show me another way to download the dataset? Sorry for any possible trouble on reading caused by languages issues as my English is not so good.

@pubgeo I am using this version of Pointnet++, my dataset has yxzRGB values in it. But when i tried to feed in the RGB values to the .las using the laspy somehow it is not happening.
Can you help please

I tried some of the provided torrents and all seem to be broken.

After setting up anaconda with conda env create --name dfc2019 --file=dev-gpu.yml
and running

conda activate dfc2019
cd track3
python ./mvs/test-mvs.py

I receive the following error message

Traceback (most recent call last):
  File "./mvs/test-mvs.py", line 693, in <module>
    predictor.build_seg_model(seg_weights_file)
  File "./mvs/test-mvs.py", line 103, in build_seg_model
    self.seg_model = build_icnet(self.height, self.width, self.bands, self.num_categories + 1,
  File "/mnt/Data-512GB/libraries_ml_geo/dfc2019/dfc2019/track3/mvs/model_icnet.py", line 52, in build_icnet
    y = Lambda(lambda x: tf.image.resize_bilinear(x, size=(int(x.shape[1])//2, int(x.shape[2])//2)), name='data_sub2')(inp)
  File "/home/sebastian/miniconda3/envs/dfc2019/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py", line 922, in __call__
    outputs = call_fn(cast_inputs, *args, **kwargs)
  File "/home/sebastian/miniconda3/envs/dfc2019/lib/python3.8/site-packages/tensorflow/python/keras/layers/core.py", line 888, in call
    result = self.function(inputs, **kwargs)
  File "/mnt/Data-512GB/libraries_ml_geo/dfc2019/dfc2019/track3/mvs/model_icnet.py", line 52, in <lambda>
    y = Lambda(lambda x: tf.image.resize_bilinear(x, size=(int(x.shape[1])//2, int(x.shape[2])//2)), name='data_sub2')(inp)
AttributeError: module 'tensorflow._api.v2.image' has no attribute 'resize_bilinear'

Hi, @pubgeo, I want to submit predictions to the leaderboard of the DFC2019 challenge, but it said "Your request to participate in this challenge has been received and a decision is pending." in the website https://competitions.codalab.org/competitions/20212#participate. Do you know how long it will take? Or whether the leaderboard has already closed?

the interface.py needs "import provider", but in the docker image, the python version is 3.5 which is lower than the minimum requirement(python >=3.6) of the "provider". Does anyone meet the same problem?

fetch: Fetching reference refs/heads/master
batch response: This repository is over its data quota. Purchase more data packs to restore access.
error: failed to fetch some objects from 'https://github.com/pubgeo/dfc2019.git/info/lfs'

Will you plan to provide the baseline results on val set?

When I git lfs clone this repo, the result is:
This repository is over its data quota. Account responsible for
LFS bandwidth should purchase more data packs to restore access.

Is there any other way to download the weight file? Thank you!

I am trying to run pointnet2 on my own data set, which has got a '_PC3.txt' file with xyzRGB values and a corresponding '_CLS.txt' file. I am getting a error like this when I ran create_train_dataset.py

But i checked the shape of CLS and PC3 file, both are same. Is it a problem because of multi-threading? If so how can I rectify it?
I tried in the LiNUX environment as well. But it gave the same error.
Please help