- Base on NVIDIA end-to-end CNN
- Summary of the model architectures
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
batch_normalization_1 (Batch (None, 66, 200, 3) 264
_________________________________________________________________
conv2d_1 (Conv2D) (None, 31, 98, 24) 1824
_________________________________________________________________
conv2d_2 (Conv2D) (None, 14, 47, 36) 21636
_________________________________________________________________
conv2d_3 (Conv2D) (None, 5, 22, 48) 43248
_________________________________________________________________
conv2d_4 (Conv2D) (None, 3, 20, 64) 27712
_________________________________________________________________
conv2d_5 (Conv2D) (None, 1, 18, 64) 36928
_________________________________________________________________
flatten_1 (Flatten) (None, 1152) 0
_________________________________________________________________
dense_1 (Dense) (None, 1164) 1342092
_________________________________________________________________
dense_2 (Dense) (None, 100) 116500
_________________________________________________________________
dense_3 (Dense) (None, 50) 5050
_________________________________________________________________
dense_4 (Dense) (None, 10) 510
_________________________________________________________________
dense_5 (Dense) (None, 2) 22
=================================================================
Total params: 1,595,786
Trainable params: 1,595,654
Non-trainable params: 132
_________________________________________________________________
- Hiện tại đang lấy dựa trên simulator của udacity, download here
- Chỉ cần tải về giải nén and run
python3 main.py.