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README.md

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 ---
 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>