♻️ rename datasets to datasetss since it interferes with hugginface's module
+ ../../Data -> ./Data
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parent
680296878d
commit
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@ -35,11 +35,11 @@ from os import listdir
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from os.path import exists, join
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from os.path import exists, join
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# Dataset parent class
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# Dataset parent class
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from datasets.common import PointCloudDataset
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from datasetss.common import PointCloudDataset
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from torch.utils.data import Sampler, get_worker_info
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from torch.utils.data import Sampler, get_worker_info
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from utils.mayavi_visu import *
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from utils.mayavi_visu import *
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from datasets.common import grid_subsampling
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from datasetss.common import grid_subsampling
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from utils.config import bcolors
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from utils.config import bcolors
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# ----------------------------------------------------------------------------------------------------------------------
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# ----------------------------------------------------------------------------------------------------------------------
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@ -110,7 +110,7 @@ class ModelNet40Dataset(PointCloudDataset):
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self.ignored_labels = np.array([])
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self.ignored_labels = np.array([])
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# Dataset folder
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# Dataset folder
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self.path = '../../Data/ModelNet40'
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self.path = './Data/ModelNet40'
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# Type of task conducted on this dataset
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# Type of task conducted on this dataset
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self.dataset_task = 'classification'
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self.dataset_task = 'classification'
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@ -36,11 +36,11 @@ from os import listdir
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from os.path import exists, join, isdir
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from os.path import exists, join, isdir
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# Dataset parent class
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# Dataset parent class
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from datasets.common import PointCloudDataset
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from datasetss.common import PointCloudDataset
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from torch.utils.data import Sampler, get_worker_info
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from torch.utils.data import Sampler, get_worker_info
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from utils.mayavi_visu import *
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from utils.mayavi_visu import *
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from datasets.common import grid_subsampling
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from datasetss.common import grid_subsampling
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from utils.config import bcolors
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from utils.config import bcolors
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@ -83,7 +83,7 @@ class NPM3DDataset(PointCloudDataset):
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self.ignored_labels = np.array([0])
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self.ignored_labels = np.array([0])
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# Dataset folder
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# Dataset folder
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self.path = '../../Data/Paris'
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self.path = './Data/Paris'
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# Type of task conducted on this dataset
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# Type of task conducted on this dataset
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self.dataset_task = 'cloud_segmentation'
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self.dataset_task = 'cloud_segmentation'
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@ -37,11 +37,11 @@ from os import listdir
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from os.path import exists, join, isdir
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from os.path import exists, join, isdir
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# Dataset parent class
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# Dataset parent class
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from datasets.common import PointCloudDataset
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from datasetss.common import PointCloudDataset
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from torch.utils.data import Sampler, get_worker_info
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from torch.utils.data import Sampler, get_worker_info
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from utils.mayavi_visu import *
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from utils.mayavi_visu import *
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from datasets.common import grid_subsampling
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from datasetss.common import grid_subsampling
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from utils.config import bcolors
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from utils.config import bcolors
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@ -86,7 +86,7 @@ class S3DISDataset(PointCloudDataset):
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self.ignored_labels = np.array([])
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self.ignored_labels = np.array([])
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# Dataset folder
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# Dataset folder
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self.path = '../../Data/S3DIS'
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self.path = './Data/S3DIS'
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# Type of task conducted on this dataset
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# Type of task conducted on this dataset
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self.dataset_task = 'cloud_segmentation'
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self.dataset_task = 'cloud_segmentation'
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@ -36,12 +36,12 @@ from os import listdir
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from os.path import exists, join, isdir
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from os.path import exists, join, isdir
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# Dataset parent class
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# Dataset parent class
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from datasets.common import *
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from datasetss.common import *
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from torch.utils.data import Sampler, get_worker_info
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from torch.utils.data import Sampler, get_worker_info
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from utils.mayavi_visu import *
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from utils.mayavi_visu import *
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from utils.metrics import fast_confusion
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from utils.metrics import fast_confusion
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from datasets.common import grid_subsampling
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from datasetss.common import grid_subsampling
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from utils.config import bcolors
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from utils.config import bcolors
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@ -62,7 +62,7 @@ class SemanticKittiDataset(PointCloudDataset):
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##########################
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##########################
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# Dataset folder
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# Dataset folder
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self.path = '../../Data/SemanticKitti'
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self.path = './Data/SemanticKitti'
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# Type of task conducted on this dataset
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# Type of task conducted on this dataset
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self.dataset_task = 'slam_segmentation'
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self.dataset_task = 'slam_segmentation'
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@ -4,11 +4,11 @@
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### Data
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### Data
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We consider our experiment folder is located at `XXXX/Experiments/KPConv-PyTorch`. And we use a common Data folder
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We consider our experiment folder is located at `XXXX/Experiments/KPConv-PyTorch`. And we use a common Data folder
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loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `../../Data`.
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loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `./Data`.
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Regularly sampled clouds from ModelNet40 dataset can be downloaded
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Regularly sampled clouds from ModelNet40 dataset can be downloaded
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<a href="https://shapenet.cs.stanford.edu/media/modelnet40_normal_resampled.zip">here (1.6 GB)</a>.
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<a href="https://shapenet.cs.stanford.edu/media/modelnet40_normal_resampled.zip">here (1.6 GB)</a>.
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Uncompress the data and move it inside the folder `../../Data/ModelNet40`.
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Uncompress the data and move it inside the folder `./Data/ModelNet40`.
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N.B. If you want to place your data anywhere else, you just have to change the variable
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N.B. If you want to place your data anywhere else, you just have to change the variable
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`self.path` of `ModelNet40Dataset` class ([here](https://github.com/HuguesTHOMAS/KPConv-PyTorch/blob/e9d328135c0a3818ee0cf1bb5bb63434ce15c22e/datasets/ModelNet40.py#L113)).
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`self.path` of `ModelNet40Dataset` class ([here](https://github.com/HuguesTHOMAS/KPConv-PyTorch/blob/e9d328135c0a3818ee0cf1bb5bb63434ce15c22e/datasets/ModelNet40.py#L113)).
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@ -4,10 +4,10 @@
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### Data
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### Data
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We consider our experiment folder is located at `XXXX/Experiments/KPConv-PyTorch`. And we use a common Data folder
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We consider our experiment folder is located at `XXXX/Experiments/KPConv-PyTorch`. And we use a common Data folder
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loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `../../Data`.
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loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `./Data`.
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S3DIS dataset can be downloaded <a href="https://goo.gl/forms/4SoGp4KtH1jfRqEj2">here (4.8 GB)</a>.
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S3DIS dataset can be downloaded <a href="https://goo.gl/forms/4SoGp4KtH1jfRqEj2">here (4.8 GB)</a>.
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Download the file named `Stanford3dDataset_v1.2.zip`, uncompress the data and move it to `../../Data/S3DIS`.
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Download the file named `Stanford3dDataset_v1.2.zip`, uncompress the data and move it to `./Data/S3DIS`.
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N.B. If you want to place your data anywhere else, you just have to change the variable
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N.B. If you want to place your data anywhere else, you just have to change the variable
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`self.path` of `S3DISDataset` class ([here](https://github.com/HuguesTHOMAS/KPConv-PyTorch/blob/afa18c92f00c6ed771b61cb08b285d2f93446ea4/datasets/S3DIS.py#L88)).
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`self.path` of `S3DISDataset` class ([here](https://github.com/HuguesTHOMAS/KPConv-PyTorch/blob/afa18c92f00c6ed771b61cb08b285d2f93446ea4/datasets/S3DIS.py#L88)).
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@ -4,7 +4,7 @@
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### Data
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### Data
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We consider our experiment folder is located at `XXXX/Experiments/KPConv-PyTorch`. And we use a common Data folder
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We consider our experiment folder is located at `XXXX/Experiments/KPConv-PyTorch`. And we use a common Data folder
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loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `../../Data`.
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loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `./Data`.
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SemanticKitti dataset can be downloaded <a href="http://semantic-kitti.org/dataset.html#download">here (80 GB)</a>.
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SemanticKitti dataset can be downloaded <a href="http://semantic-kitti.org/dataset.html#download">here (80 GB)</a>.
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Download the three file named:
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Download the three file named:
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@ -12,13 +12,13 @@ Download the three file named:
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* [`data_odometry_calib.zip` (1 MB)](http://www.cvlibs.net/download.php?file=data_odometry_calib.zip)
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* [`data_odometry_calib.zip` (1 MB)](http://www.cvlibs.net/download.php?file=data_odometry_calib.zip)
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* [`data_odometry_labels.zip` (179 MB)](http://semantic-kitti.org/assets/data_odometry_labels.zip)
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* [`data_odometry_labels.zip` (179 MB)](http://semantic-kitti.org/assets/data_odometry_labels.zip)
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uncompress the data and move it to `../../Data/SemanticKitti`.
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uncompress the data and move it to `./Data/SemanticKitti`.
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You also need to download the files
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You also need to download the files
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[`semantic-kitti-all.yaml`](https://github.com/PRBonn/semantic-kitti-api/blob/master/config/semantic-kitti-all.yaml)
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[`semantic-kitti-all.yaml`](https://github.com/PRBonn/semantic-kitti-api/blob/master/config/semantic-kitti-all.yaml)
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and
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and
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[`semantic-kitti.yaml`](https://github.com/PRBonn/semantic-kitti-api/blob/master/config/semantic-kitti.yaml).
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[`semantic-kitti.yaml`](https://github.com/PRBonn/semantic-kitti-api/blob/master/config/semantic-kitti.yaml).
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Place them in your `../../Data/SemanticKitti` folder.
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Place them in your `./Data/SemanticKitti` folder.
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N.B. If you want to place your data anywhere else, you just have to change the variable
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N.B. If you want to place your data anywhere else, you just have to change the variable
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`self.path` of `SemanticKittiDataset` class ([here](https://github.com/HuguesTHOMAS/KPConv-PyTorch/blob/c32e6ce94ed34a3dd9584f98d8dc0be02535dfb4/datasets/SemanticKitti.py#L65)).
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`self.path` of `SemanticKittiDataset` class ([here](https://github.com/HuguesTHOMAS/KPConv-PyTorch/blob/c32e6ce94ed34a3dd9584f98d8dc0be02535dfb4/datasets/SemanticKitti.py#L65)).
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@ -37,9 +37,9 @@ from utils.metrics import IoU_from_confusions, smooth_metrics, fast_confusion
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from utils.ply import read_ply
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from utils.ply import read_ply
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# Datasets
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# Datasets
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from datasets.ModelNet40 import ModelNet40Dataset
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from datasetss.ModelNet40 import ModelNet40Dataset
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from datasets.S3DIS import S3DISDataset
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from datasetss.S3DIS import S3DISDataset
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from datasets.SemanticKitti import SemanticKittiDataset
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from datasetss.SemanticKitti import SemanticKittiDataset
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# ----------------------------------------------------------------------------------------------------------------------
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# ----------------------------------------------------------------------------------------------------------------------
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#
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#
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@ -29,9 +29,9 @@ import sys
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import torch
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import torch
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# Dataset
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# Dataset
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from datasets.ModelNet40 import *
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from datasetss.ModelNet40 import *
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from datasets.S3DIS import *
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from datasetss.S3DIS import *
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from datasets.SemanticKitti import *
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from datasetss.SemanticKitti import *
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from torch.utils.data import DataLoader
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from torch.utils.data import DataLoader
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from utils.config import Config
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from utils.config import Config
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@ -155,6 +155,7 @@ if __name__ == '__main__':
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print()
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print()
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print('Data Preparation')
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print('Data Preparation')
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print('****************')
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print('****************')
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print(config.dataset)
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if on_val:
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if on_val:
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set = 'validation'
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set = 'validation'
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import torch
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import torch
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# Dataset
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# Dataset
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from datasets.ModelNet40 import *
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from datasetss.ModelNet40 import *
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from torch.utils.data import DataLoader
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from torch.utils.data import DataLoader
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from utils.config import Config
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from utils.config import Config
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@ -26,7 +26,7 @@ import signal
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import os
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import os
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# Dataset
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# Dataset
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from datasets.NPM3D import *
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from datasetss.NPM3D import *
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from torch.utils.data import DataLoader
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from torch.utils.data import DataLoader
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from utils.config import Config
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from utils.config import Config
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@ -26,7 +26,7 @@ import signal
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import os
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import os
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# Dataset
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# Dataset
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from datasets.S3DIS import *
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from datasetss.S3DIS import *
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from torch.utils.data import DataLoader
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from torch.utils.data import DataLoader
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from utils.config import Config
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from utils.config import Config
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import torch
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import torch
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# Dataset
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# Dataset
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from datasets.SemanticKitti import *
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from datasetss.SemanticKitti import *
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from torch.utils.data import DataLoader
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from torch.utils.data import DataLoader
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from utils.config import Config
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from utils.config import Config
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import torch
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import torch
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# Dataset
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# Dataset
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from datasets.ModelNet40 import *
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from datasetss.ModelNet40 import *
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from datasets.S3DIS import *
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from datasetss.S3DIS import *
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from torch.utils.data import DataLoader
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from torch.utils.data import DataLoader
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from utils.config import Config
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from utils.config import Config
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