init

.gitignore

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+venv

app.py

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+from huggingface_hub import from_pretrained_keras
+import keras_cv
+import gradio as gr
+from tensorflow import keras
+
+keras.mixed_precision.set_global_policy("mixed_float16")
+# load keras model
+resolution = 512
+dreambooth_model = keras_cv.models.StableDiffusion(
+        img_width=resolution, img_height=resolution, jit_compile=True, 
+    )
+loaded_diffusion_model = from_pretrained_keras("johko/dreambooth_marvin_paranoid_android")
+dreambooth_model._diffusion_model = loaded_diffusion_model
+
+
+def generate_images(prompt: str, negative_prompt:str, num_imgs_to_gen: int, num_steps: int):
+    """
+    This function is used to generate images using our fine-tuned keras dreambooth stable diffusion model.
+    Args:
+        prompt (str): The text input given by the user based on which images will be generated.
+        num_imgs_to_gen (int): The number of images to be generated using given prompt.
+        num_steps (int): The number of denoising steps
+    Returns:
+        generated_img (List): List of images that were generated using the model
+    """
+    generated_img = dreambooth_model.text_to_image(
+        prompt, 
+        negative_prompt=negative_prompt,
+        batch_size=num_imgs_to_gen,
+        num_steps=num_steps,
+    )
+   
+    return generated_img
+    
+with gr.Blocks() as demo:
+    gr.HTML("<h2 style=\"font-size: 2em; font-weight: bold\" align=\"center\">Keras Dreambooth - Marvin the Paranoid Android</h2>")    
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(lines=1, value="paranoid marvin a robot", label="Base Prompt")
+            negative_prompt = gr.Textbox(lines=1, value="deformed", label="Negative Prompt")
+            samples = gr.Slider(minimum=1, maximum=10, default=1, step=1, label="Number of Images")
+            num_steps = gr.Slider(label="Inference Steps",value=50)
+            run = gr.Button(value="Submit")
+        with gr.Column():
+            gallery = gr.Gallery(label="Outputs").style(grid=(1,2))
+
+    run.click(generate_images, inputs=[prompt,negative_prompt, samples, num_steps], outputs=gallery)
+    
+    gr.Examples([["A pillow looking like paranoid marvin a robot, 4k, high quality","deformed", 1, 50]],
+                [prompt,negative_prompt, samples,num_steps], gallery, generate_images)
+    gr.Markdown('\n Demo created by: <a href=\"https://huggingface.co/johko/\">johko</a>')

requirements.txt

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+keras_cv
+tensorflow