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Project description

Dreamify

A function that applies deep dream to an image using pre-trained CNNs trained on the ImageNet dataset.

Installation

pip install dreamify

Usage

To apply Dreamify to an image, use the following Python script:

from dreamify.dream import generate_dream_image


image_path = "example.jpg"

generate_dream_image(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.dream import generate_dream_image


image_path = "example.jpg"

generate_dream_image(
    image_path,
    output_path="dream.png",
    model_name="xception",
    step=20.0,
    num_octave=3,
    octave_scale=1.4,
    iterations=30,
    max_loss=15.0,
    save_video=False,
    duration=10,
)

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 inception_v3
ResNet152V2 resnet152v2
Xception (Default) xception
MobileNet-V2 mobilenet_v2

Cat

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