Merge branch 'pytorch-1.0'

.gitignore

@@ -7,3 +7,4 @@ shapenetcore_partanno_segmentation_benchmark_v0/
 .idea*
 cls/
 seg/
+*.egg-info/

README.md

@@ -1,25 +1,66 @@
 # PointNet.pytorch
-This repo is implementation for PointNet(https://arxiv.org/abs/1612.00593) in pytorch. The model is in `pointnet.py`.
+This repo is implementation for PointNet(https://arxiv.org/abs/1612.00593) in pytorch. The model is in `pointnet/model.py`.
 
+It is tested with pytorch-1.0.
 
 # Download data and running
 
 ```
+git clone https://github.com/fxia22/pointnet.pytorch
+cd pointnet.pytorch
+pip install -e .
+```
+
+Download and build visualization tool
+```
+cd script
 bash build.sh #build C++ code for visualization
 bash download.sh #download dataset
-python train_classification.py #train 3D model classification
-python python train_segmentation.py # train 3D model segmentaion
+```
 
-python show_seg.py --model seg/seg_model_20.pth  # show segmentation results
+Training 
 ```
+cd utils
+python train_classification.py --dataset <dataset path> --nepoch=<number epochs> --dataset_type <modelnet40 | shapenet>
+python train_segmentation.py --dataset <dataset path> --nepoch=<number epochs> 
+```
+
+Use `--feature_transform` to use feature transform.
 
 # Performance
-Without heavy tuning, PointNet can achieve 80-90% performance in classification and segmentaion on this [dataset](http://web.stanford.edu/~ericyi/project_page/part_annotation/index.html). 
+
+## Classification performance
+
+On ModelNet40:
+
+|  | Overall Acc | 
+| :---: | :---: | 
+| Original implementation | 89.2 | 
+| this implementation(w/o feature transform) | 86.4 | 
+| this implementation(w/ feature transform) | 86.8 | 
+
+On [A subset of shapenet](http://web.stanford.edu/~ericyi/project_page/part_annotation/index.html)
+
+|  | Overall Acc | 
+| :---: | :---: | 
+| Original implementation | N/A | 
+| this implementation(w/o feature transform) | 98.1 | 
+| this implementation(w/ feature transform) | 96.8 | 
+
+## Segmentation performance
+
+Segmentation on  [A subset of shapenet](http://web.stanford.edu/~ericyi/project_page/part_annotation/index.html).
+
+| Class(mIOU) | Airplane | Bag| Cap|Car|Chair|Earphone|Guitar|Knife|Lamp|Laptop|Motorbike|Mug|Pistol|Rocket|Skateboard|Table
+| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | 
+| Original implementation |  83.4 | 78.7 | 82.5| 74.9 |89.6| 73.0| 91.5| 85.9| 80.8| 95.3| 65.2| 93.0| 81.2| 57.9| 72.8| 80.6| 
+| this implementation(w/o feature transform) | 73.5 | 71.3 | 64.3 | 61.1 | 87.2 | 69.5 | 86.1|81.6| 77.4|92.7|41.3|86.5|78.2|41.2|61.0|81.1|
+
+Note that this implementation trains each class separately, so classes with fewer data will have slightly lower performance than reference implementation.
 
 Sample segmentation result:
 ![seg](https://raw.githubusercontent.com/fxia22/pointnet.pytorch/master/misc/show3d.png?token=AE638Oy51TL2HDCaeCF273X_-Bsy6-E2ks5Y_BUzwA%3D%3D)
 
-
 # Links
 
 - [Project Page](http://stanford.edu/~rqi/pointnet/)

misc/modelnet_id.txt

@@ -0,0 +1,40 @@
+airplane	0
+bathtub	1
+bed	2
+bench	3
+bookshelf	4
+bottle	5
+bowl	6
+car	7
+chair	8
+cone	9
+cup	10
+curtain	11
+desk	12
+door	13
+dresser	14
+flower_pot	15
+glass_box	16
+guitar	17
+keyboard	18
+lamp	19
+laptop	20
+mantel	21
+monitor	22
+night_stand	23
+person	24
+piano	25
+plant	26
+radio	27
+range_hood	28
+sink	29
+sofa	30
+stairs	31
+stool	32
+table	33
+tent	34
+toilet	35
+tv_stand	36
+vase	37
+wardrobe	38
+xbox	39

misc/num_seg_classes.txt

@@ -0,0 +1,16 @@
+Airplane	4
+Bag	2
+Cap	2
+Car	4
+Chair	4
+Earphone	3
+Guitar	3
+Knife	2
+Lamp	4
+Laptop	2
+Motorbike	6
+Mug	2
+Pistol	3
+Rocket	3
+Skateboard	3
+Table	3