Update app.py

app.py

@@ -1,25 +1,53 @@
-from utils_app import keras_stable_diffusion_app
+from huggingface_hub import from_pretrained_keras
+import keras_cv
 import gradio as gr
+from tensorflow import keras
 
-app = gr.Blocks()
-with app:
-    gr.HTML(
-        """
-        <h1 style='text-align: center'>
-        Keras Diffusion WebUI
-        </h1>
-        """
+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, 
     )
-    gr.Markdown(
-        """
-        <h4 style='text-align: center'>
-        Follow me for more! 
-        <a href='https://twitter.com/kadirnar_ai' target='_blank'>Twitter</a> | <a href='https://github.com/kadirnar' target='_blank'>Github</a> | <a href='https://www.linkedin.com/in/kadir-nar/' target='_blank'>Linkedin</a>
-        </h4>
-        """
+loaded_diffusion_model = from_pretrained_keras("keras-dreambooth/keras_diffusion_lowpoly_world")
+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 - Traditional Furniture Demo</h2>")    
     with gr.Row():
         with gr.Column():
-            keras_diffusion_app = keras_stable_diffusion_app()
+            prompt = gr.Textbox(lines=1, value="lowpoly_world", 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 Image")
+            num_steps = gr.Slider(label="Inference Steps",value=50)
+            run = gr.Button(value="Run")
+        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([["photo of lowpoly_world","bad, ugly", 1, 50]],
+                [prompt,negative_prompt, samples,num_steps], gallery, generate_images)
+    gr.Markdown('\n Demo created by: <a href=\"https://huggingface.co/kadirnar/\">Kadir Nar</a>')
 
-app.queue().launch(debug=True)  
+demo.launch(debug=True)