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---
library_name: tf-keras
license: apache-2.0
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>
</details> |