♻️ rename datasets to datasetss since it interferes with hugginface's module

+ ../../Data -> ./Data

datasetss/ModelNet40.py

@@ -35,11 +35,11 @@ from os import listdir
 from os.path import exists, join
 
 # Dataset parent class
-from datasets.common import PointCloudDataset
+from datasetss.common import PointCloudDataset
 from torch.utils.data import Sampler, get_worker_info
 from utils.mayavi_visu import *
 
-from datasets.common import grid_subsampling
+from datasetss.common import grid_subsampling
 from utils.config import bcolors
 
 # ----------------------------------------------------------------------------------------------------------------------
@@ -110,7 +110,7 @@ class ModelNet40Dataset(PointCloudDataset):
         self.ignored_labels = np.array([])
 
         # Dataset folder
-        self.path = '../../Data/ModelNet40'
+        self.path = './Data/ModelNet40'
 
         # Type of task conducted on this dataset
         self.dataset_task = 'classification'

datasetss/NPM3D.py

@@ -36,11 +36,11 @@ from os import listdir
 from os.path import exists, join, isdir
 
 # Dataset parent class
-from datasets.common import PointCloudDataset
+from datasetss.common import PointCloudDataset
 from torch.utils.data import Sampler, get_worker_info
 from utils.mayavi_visu import *
 
-from datasets.common import grid_subsampling
+from datasetss.common import grid_subsampling
 from utils.config import bcolors
 
 
@@ -83,7 +83,7 @@ class NPM3DDataset(PointCloudDataset):
         self.ignored_labels = np.array([0])
 
         # Dataset folder
-        self.path = '../../Data/Paris'
+        self.path = './Data/Paris'
 
         # Type of task conducted on this dataset
         self.dataset_task = 'cloud_segmentation'

datasetss/S3DIS.py

@@ -37,11 +37,11 @@ from os import listdir
 from os.path import exists, join, isdir
 
 # Dataset parent class
-from datasets.common import PointCloudDataset
+from datasetss.common import PointCloudDataset
 from torch.utils.data import Sampler, get_worker_info
 from utils.mayavi_visu import *
 
-from datasets.common import grid_subsampling
+from datasetss.common import grid_subsampling
 from utils.config import bcolors
 
 
@@ -86,7 +86,7 @@ class S3DISDataset(PointCloudDataset):
         self.ignored_labels = np.array([])
 
         # Dataset folder
-        self.path = '../../Data/S3DIS'
+        self.path = './Data/S3DIS'
 
         # Type of task conducted on this dataset
         self.dataset_task = 'cloud_segmentation'

datasetss/SemanticKitti.py

@@ -36,12 +36,12 @@ from os import listdir
 from os.path import exists, join, isdir
 
 # Dataset parent class
-from datasets.common import *
+from datasetss.common import *
 from torch.utils.data import Sampler, get_worker_info
 from utils.mayavi_visu import *
 from utils.metrics import fast_confusion
 
-from datasets.common import grid_subsampling
+from datasetss.common import grid_subsampling
 from utils.config import bcolors
 
 
@@ -62,7 +62,7 @@ class SemanticKittiDataset(PointCloudDataset):
         ##########################
 
         # Dataset folder
-        self.path = '../../Data/SemanticKitti'
+        self.path = './Data/SemanticKitti'
 
         # Type of task conducted on this dataset
         self.dataset_task = 'slam_segmentation'

doc/object_classification_guide.md

@@ -4,11 +4,11 @@
 ### Data
 
 We consider our experiment folder is located at `XXXX/Experiments/KPConv-PyTorch`. And we use a common Data folder 
-loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `../../Data`.
+loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `./Data`.
 
 Regularly sampled clouds from ModelNet40 dataset can be downloaded 
 <a href="https://shapenet.cs.stanford.edu/media/modelnet40_normal_resampled.zip">here (1.6 GB)</a>. 
-Uncompress the data and move it inside the folder `../../Data/ModelNet40`.
+Uncompress the data and move it inside the folder `./Data/ModelNet40`.
 
 N.B. If you want to place your data anywhere else, you just have to change the variable 
 `self.path` of `ModelNet40Dataset` class ([here](https://github.com/HuguesTHOMAS/KPConv-PyTorch/blob/e9d328135c0a3818ee0cf1bb5bb63434ce15c22e/datasets/ModelNet40.py#L113)).

doc/scene_segmentation_guide.md

@@ -4,10 +4,10 @@
 ### Data
 
 We consider our experiment folder is located at `XXXX/Experiments/KPConv-PyTorch`. And we use a common Data folder 
-loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `../../Data`.
+loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `./Data`.
 
 S3DIS dataset can be downloaded <a href="https://goo.gl/forms/4SoGp4KtH1jfRqEj2">here (4.8 GB)</a>. 
-Download the file named `Stanford3dDataset_v1.2.zip`, uncompress the data and move it to `../../Data/S3DIS`.
+Download the file named `Stanford3dDataset_v1.2.zip`, uncompress the data and move it to `./Data/S3DIS`.
 
 N.B. If you want to place your data anywhere else, you just have to change the variable 
 `self.path` of `S3DISDataset` class ([here](https://github.com/HuguesTHOMAS/KPConv-PyTorch/blob/afa18c92f00c6ed771b61cb08b285d2f93446ea4/datasets/S3DIS.py#L88)).

doc/slam_segmentation_guide.md

@@ -4,7 +4,7 @@
 ### Data
 
 We consider our experiment folder is located at `XXXX/Experiments/KPConv-PyTorch`. And we use a common Data folder 
-loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `../../Data`.
+loacated at `XXXX/Data`. Therefore the relative path to the Data folder is `./Data`.
 
 SemanticKitti dataset can be downloaded <a href="http://semantic-kitti.org/dataset.html#download">here (80 GB)</a>. 
 Download the three file named:
@@ -12,13 +12,13 @@ Download the three file named:
  * [`data_odometry_calib.zip` (1 MB)](http://www.cvlibs.net/download.php?file=data_odometry_calib.zip)
  * [`data_odometry_labels.zip` (179 MB)](http://semantic-kitti.org/assets/data_odometry_labels.zip)
 
-uncompress the data and move it to `../../Data/SemanticKitti`.
+uncompress the data and move it to `./Data/SemanticKitti`.
 
 You also need to download the files 
 [`semantic-kitti-all.yaml`](https://github.com/PRBonn/semantic-kitti-api/blob/master/config/semantic-kitti-all.yaml)
 and
 [`semantic-kitti.yaml`](https://github.com/PRBonn/semantic-kitti-api/blob/master/config/semantic-kitti.yaml).
-Place them in your `../../Data/SemanticKitti` folder.
+Place them in your `./Data/SemanticKitti` folder.
 
 N.B. If you want to place your data anywhere else, you just have to change the variable 
 `self.path` of `SemanticKittiDataset` class ([here](https://github.com/HuguesTHOMAS/KPConv-PyTorch/blob/c32e6ce94ed34a3dd9584f98d8dc0be02535dfb4/datasets/SemanticKitti.py#L65)).

plot_convergence.py

@@ -37,9 +37,9 @@ from utils.metrics import IoU_from_confusions, smooth_metrics, fast_confusion
 from utils.ply import read_ply
 
 # Datasets
-from datasets.ModelNet40 import ModelNet40Dataset
-from datasets.S3DIS import S3DISDataset
-from datasets.SemanticKitti import SemanticKittiDataset
+from datasetss.ModelNet40 import ModelNet40Dataset
+from datasetss.S3DIS import S3DISDataset
+from datasetss.SemanticKitti import SemanticKittiDataset
 
 # ----------------------------------------------------------------------------------------------------------------------
 #

test_models.py

@@ -29,9 +29,9 @@ import sys
 import torch
 
 # Dataset
-from datasets.ModelNet40 import *
-from datasets.S3DIS import *
-from datasets.SemanticKitti import *
+from datasetss.ModelNet40 import *
+from datasetss.S3DIS import *
+from datasetss.SemanticKitti import *
 from torch.utils.data import DataLoader
 
 from utils.config import Config
@@ -155,6 +155,7 @@ if __name__ == '__main__':
     print()
     print('Data Preparation')
     print('****************')
+    print(config.dataset)
 
     if on_val:
         set = 'validation'

train_ModelNet40.py

@@ -29,7 +29,7 @@ import sys
 import torch
 
 # Dataset
-from datasets.ModelNet40 import *
+from datasetss.ModelNet40 import *
 from torch.utils.data import DataLoader
 
 from utils.config import Config

train_NPM3D.py

@@ -26,7 +26,7 @@ import signal
 import os
 
 # Dataset
-from datasets.NPM3D import *
+from datasetss.NPM3D import *
 from torch.utils.data import DataLoader
 
 from utils.config import Config

train_S3DIS.py

@@ -26,7 +26,7 @@ import signal
 import os
 
 # Dataset
-from datasets.S3DIS import *
+from datasetss.S3DIS import *
 from torch.utils.data import DataLoader
 
 from utils.config import Config

train_SemanticKitti.py

@@ -29,7 +29,7 @@ import sys
 import torch
 
 # Dataset
-from datasets.SemanticKitti import *
+from datasetss.SemanticKitti import *
 from torch.utils.data import DataLoader
 
 from utils.config import Config

visualize_deformations.py

@@ -29,8 +29,8 @@ import sys
 import torch
 
 # Dataset
-from datasets.ModelNet40 import *
-from datasets.S3DIS import *
+from datasetss.ModelNet40 import *
+from datasetss.S3DIS import *
 from torch.utils.data import DataLoader
 
 from utils.config import Config