Fix table in README.md and some file headers.

README.md

@@ -47,14 +47,14 @@ source planercnn/bin/activate
 pip install -r requirements.txt
 ```
 Now, we compile nms and roialign as explained in the installation section of [pytorch-mask-rcnn](https://github.com/multimodallearning/pytorch-mask-rcnn). To be specific, you can build these two functions using the following commands with the right `--arch` option:
-	
-	| GPU | arch |
-	| --- | --- |
-    | TitanX | sm_52 |
-    | GTX 960M | sm_50 |
-    | GTX 1070 | sm_61 |
-    | GTX 1080 (Ti), Titan XP | sm_61 |
-	
+
+ | GPU                     | arch  |
+ |-------------------------|-------|
+ | TitanX                  | sm_52 |
+ | GTX 960M                | sm_50 |
+ | GTX 1070                | sm_61 |
+ | GTX 1080 (Ti), Titan XP | sm_61 |
+
 More details of the compute capability are shown in [NVIDIA](https://developer.nvidia.com/cuda-gpus)
 
 ```bash
@@ -84,7 +84,7 @@ python evaluate.py --methods=f --suffix=warping_refine --dataset=inference --cus
 Results are saved under "test/inference/". Besides visualizations, plane parameters (#planes x 3) are saved in "\*_plane_parameters_0.npy" and plane masks (#planes x 480 x 640) are saved in "\*_plane_masks_0.npy".
 
 ## Using custom data
-Please put your images (*.png* or *.jpg* files), and camera intrinsics under a folder ($YOUR_IMAGE_FOLDER). The camera parameters should be put under a *.txt* file with 6 values (fx, fy, cx, fy, image_width, image_height) separately by a space. If the camera intrinsics is the same for all images, please put these parameters in *camera.txt*. Otherwise, please add a separate intrinsics file for each image, and name it the same with the image (changing the file extension to *.txt*). And then run:
+Please put your images (*.png* or *.jpg* files), and camera intrinsics under a folder ($YOUR_IMAGE_FOLDER). The camera parameters should be put under a *.txt* file with 6 values (fx, fy, cx, cy, image_width, image_height) separately by a space. If the camera intrinsics is the same for all images, please put these parameters in *camera.txt*. Otherwise, please add a separate intrinsics file for each image, and name it the same with the image (changing the file extension to *.txt*). And then run:
 ```bash
 python evaluate.py --methods=f --suffix=warping_refine --dataset=inference --customDataFolder=$YOUR_IMAGE_FOLDER
 ```
@@ -146,6 +146,6 @@ Note that [PlaneNet](https://github.com/art-programmer/PlaneNet/blob/master/LICE
 If you have any questions, please contact the primary author [Chen Liu <chenliu@wustl.edu>](mailto:chenliu@wustl.edu), or [Kihwan Kim <kihwank@nvidia.com>](mailto:kihwank@nvidia.com).
 
 ## Acknowledgement
-A Part of our implementation uses the nms/roialign from the Mask R-CNN implementation from [pytorch-mask-rcnn](https://github.com/multimodallearning/pytorch-mask-rcnn) with the licensed under [MIT License](https://github.com/multimodallearning/pytorch-mask-rcnn/blob/master/LICENSE)
+Our implementation uses the nms/roialign from the Mask R-CNN implementation from [pytorch-mask-rcnn](https://github.com/multimodallearning/pytorch-mask-rcnn), which is licensed under [MIT License](https://github.com/multimodallearning/pytorch-mask-rcnn/blob/master/LICENSE)
 
 

config.py

@@ -1,13 +1,5 @@
 """
-Mask R-CNN
-Base Configurations class.
-
 Copyright (c) 2017 Matterport, Inc.
-Licensed under the MIT License (see LICENSE for details)
-Written by Waleed Abdulla
-"""
-
-"""
 Copyright (C) 2019 NVIDIA Corporation.  All rights reserved.
 Licensed under the CC BY-NC-SA 4.0 license
 (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).

models/model.py

@@ -1,13 +1,5 @@
 """
-Mask R-CNN
-The main Mask R-CNN model implemenetation.
-
 Copyright (c) 2017 Matterport, Inc.
-Licensed under the MIT License (see LICENSE for details)
-Written by Waleed Abdulla
-"""
-
-"""
 Copyright (C) 2019 NVIDIA Corporation.  All rights reserved.
 Licensed under the CC BY-NC-SA 4.0 license
 (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).

utils.py

@@ -1,13 +1,5 @@
 """
-Mask R-CNN
-Common utility functions and classes.
-
 Copyright (c) 2017 Matterport, Inc.
-Licensed under the MIT License (see LICENSE for details)
-Written by Waleed Abdulla
-"""
-
-"""
 Copyright (C) 2019 NVIDIA Corporation.  All rights reserved.
 Licensed under the CC BY-NC-SA 4.0 license
 (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).

visualize_utils.py

@@ -1,13 +1,5 @@
 """
-Mask R-CNN
-Common utility functions and classes.
-
 Copyright (c) 2017 Matterport, Inc.
-Licensed under the MIT License (see LICENSE for details)
-Written by Waleed Abdulla
-"""
-
-"""
 Copyright (C) 2019 NVIDIA Corporation.  All rights reserved.
 Licensed under the CC BY-NC-SA 4.0 license
 (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).