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Project description
Dreamify
A function that applies deep dream to an image using a pre-trained CNN trained on the ImageNet dataset.
Testing it
dreamify
Installation
pip install dreamify
Usage
To apply Dreamify to an image, use the following Python script:
from dreamify.deepdream import deepdream
image_path = "example.jpg"
deepdream(image_path)
You may customize the behavior of the dreamifyer by selecting a different pre-trained model, saving it as a video, etc.:
from dreamify.deepdream import deepdream
image_path = "example.jpg"
deepdream(
image_path,
output_path="deepdream.png",
model_name="inception_v3",
iterations=100,
learning_rate=0.01,
octaves=range(-2, 3),
octave_scale=1.3,
save_video=False,
save_gif=False,
duration=3,
vid_duration=3,
gif_duration=3,
mirror_video=False,
seed=None,
)
Available Models
Dreamify supports the following models:
| Model Name | Enum Value |
|---|---|
| VGG19 | vgg19 |
| ConvNeXt-XL | convnext_xl |
| DenseNet121 | densenet121 |
| EfficientNet-V2L | efficientnet_v2l |
| Inception-ResNet-V2 | inception_resnet_v2 |
| Inception-V3 (Default) | inception_v3 |
| ResNet152V2 | resnet152v2 |
| Xception | xception |
| MobileNet-V2 | mobilenet_v2 |
Other Examples
DeepDream
Dream (shallow) -- See documentation of dream (shallow).
Project details
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