readme: ---
  license: apache-2.0
  library_name: keras
  tags:
  - image-classification
  - image-segmentation
  ---
  
  ## Model Description
  ### Keras Implementation of Point cloud classification with PointNet
  
  This repo contains the trained model of [Point cloud classification with PointNet](https://keras.io/examples/vision/pointnet/).
  
  The full credit goes to: [David Griffiths](https://dgriffiths3.github.io/)
  
  ## Intended uses & limitations
  - As stated in the paper, PointNet is 3D perception model, applying deep learning to point clouds for object classification and scene semantic segmentation. 
  - PointNet takes raw point cloud data as input, which is typically collected from either a lidar or radar sensor.
  
  ## Training and evaluation data
  - The dataset used for training is ModelNet10, the smaller 10 class version of the ModelNet40 dataset.
  
  ## Training procedure
  ### Training hyperparameter 
  The following hyperparameters were used during training:
  - optimizer: 'adam'
  - loss: 'sparse_categorical_crossentropy'
  - epochs: 20
  - batch_size: 32
  - learning_rate: 0.001
  
  ## Model Plot
  
  <details>
  <summary>View Model Plot</summary>
  
  ![Model Image](./model.png)
  
  </details>