(width, height, frame_count, lr, output=9)
| 579 | |
| 580 | |
| 581 | def sentnet2(width, height, frame_count, lr, output=9): |
| 582 | network = input_data(shape=[None, width, height, frame_count, 1], name='input') |
| 583 | network = conv_3d(network, 96, 11, strides=4, activation='relu') |
| 584 | network = max_pool_3d(network, 3, strides=2) |
| 585 | #network = local_response_normalization(network) |
| 586 | network = conv_3d(network, 256, 5, activation='relu') |
| 587 | network = max_pool_3d(network, 3, strides=2) |
| 588 | #network = local_response_normalization(network) |
| 589 | network = conv_3d(network, 384, 3, activation='relu') |
| 590 | network = conv_3d(network, 384, 3, activation='relu') |
| 591 | network = conv_3d(network, 256, 3, activation='relu') |
| 592 | network = max_pool_3d(network, 3, strides=2) |
| 593 | #network = local_response_normalization(network) |
| 594 | network = fully_connected(network, 4096, activation='tanh') |
| 595 | network = dropout(network, 0.5) |
| 596 | network = fully_connected(network, 4096, activation='tanh') |
| 597 | network = dropout(network, 0.5) |
| 598 | network = fully_connected(network, 3, activation='softmax') |
| 599 | network = regression(network, optimizer='momentum', |
| 600 | loss='categorical_crossentropy', |
| 601 | learning_rate=lr, name='targets') |
| 602 | |
| 603 | model = tflearn.DNN(network, checkpoint_path='model_alexnet', |
| 604 | max_checkpoints=1, tensorboard_verbose=0, tensorboard_dir='log') |
| 605 | |
| 606 | return model |
| 607 | |
| 608 | |
| 609 | def sentnet(width, height, frame_count, lr, output=9): |
nothing calls this directly
no outgoing calls
no test coverage detected