This repository has been archived by the owner on Apr 7, 2020. It is now read-only.
Weekly Report 19 (08.19. ~ 08.23.)
| Layer (type) | Output Shape | Param # |
|---|---|---|
| conv2d_1 (Conv2D) | (None, 148, 82, 96) | 2688 |
| max_pooling2d_1 (MaxPooling2D) | (None, 74, 41, 96) | 0 |
| conv2d_2 (Conv2D) | (None, 72, 39, 384) | 332160 |
| max_pooling2d_2 (MaxPooling2D) | (None, 36, 19, 384) | 0 |
| conv2d_3 (Conv2D) | (None, 34, 17, 512) | 1769984 |
| max_pooling2d_3 (MaxPooling2D) | (None, 17, 8, 512) | 0 |
| flatten_1 (Flatten) | (None, 69632) | 0 |
| dropout_1 (Dropout) | (None, 69632) | 0 |
| dense_1 (Dense) | (None, 512) | 35652096 |
| dense_2 (Dense) | (None, 1) | 513 |
- Total params: 37,757,441
- Trainable params: 37,757,441
- Non-trainable params: 0
- First attempt at full image resolution (960x540) took >40h and produced a network too big to load in jupyter notebook (0.9GB)
- Second attempt at greatly reduced resolution (150x84) took 21:53:38 to train
- currently same structure with 200 epochs in training (estimated training time 4.4h)
- review network structure and refine training