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Reproducing Other DeepDream Project Results
First download the image used in the tutorial via wget (Linux) or manually on Windows:
wget https://www.tensorflow.org/tutorials/generative/deepdream_files/output_Y5BPgc8NNbG0_0.png
Download the Keras Inception V3 model either manually or by using the download_models.py script:
python models/download_models.py -models keras-inceptionv3
Now you can run neural-dream with:
python neural_dream.py -backend cudnn -dream_layers mixed4,mixed5 -content_image output_Y5BPgc8NNbG0_0.png
To use tiling:
python neural_dream.py -backend cudnn -dream_layers mixed4,mixed5 -content_image output_Y5BPgc8NNbG0_0.png -tile_size 256 -print_tile 1
The -jitter parameter controls random image shifts, and the -disable_roll flag will disable the random full image shifts used when tiling (only random shifts on tiles will be used if -disable_roll is enabled when tiling).
Download the Inception5h model either manually or by using the download_models.py script:
python models/download_models.py -models tensorflow-inception5h
To reproduce the basic output:
python neural_dream.py -content_image input.png -dream_layers mixed4d_3x3_bottleneck_pre_relu_conv -channels 139 -model_file models/inception5h.pth -loss_mode mean
With Laplacian Pyramid Gradient Normalization:
python neural_dream.py -content_image input.png -dream_layers mixed3b_1x1_pre_relu_conv -channels 139 -model_file models/inception5h.pth -loss_mode mean -lap_scale 4 -sigma 1,4
- Source: Protobuf-Dreamer
Download the Inception5h model either manually or by using the download_models.py script:
python models/download_models.py -models tensorflow-inception5h
To replicate the advanced command set:
python neural_dream.py -content_image input.png -dream_layers mixed4d_3x3_bottleneck_pre_relu_conv -channels 139 -octave_iter 10 --tile_size 512 -image_size 1024 -model_file models/inception5h.pth
- Source: deepdreamer
Download the Places 205 GoogleNet model either manually or by using the download_models.py script:
python models/download_models.py -models caffe-googlenet-places205
Now you can run neural-dream with:
python neural_dream.py -backend cudnn -dream_layers inception_4c_output -model_file models/googlenet_places205.pth -clamp -zoom 98
To adjust the contrast of the output image:
python neural_dream.py -backend cudnn -dream_layers inception_4c_output -model_file models/googlenet_places205.pth -adjust_contrast 99.98
To create an output GIF:
mkdir outputs # Or manually create folder named "outputs" on Windows
python neural_dream.py -backend cudnn -dream_layers inception_4c_output -model_file models/googlenet_places205.pth -output_images outputs/out.png -create_gif -frame_duration 100