Update app.py

app.py

@@ -4,25 +4,16 @@ 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("keras-dreambooth/keras-diffusion-traditional-furniture")
+loaded_diffusion_model = from_pretrained_keras("ashishtanwer/shoe")
 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,
@@ -33,10 +24,10 @@ def generate_images(prompt: str, negative_prompt:str, num_imgs_to_gen: int, num_
     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>")    
+    gr.HTML("<h2 style=\"font-size: 2em; font-weight: bold\" align=\"center\">Radiance Shoe Demo</h2>")    
     with gr.Row():
         with gr.Column():
-            prompt = gr.Textbox(lines=1, value="sks traditional furniture", label="Base Prompt")
+            prompt = gr.Textbox(lines=1, value="sshh shoe", 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)
@@ -46,8 +37,7 @@ with gr.Blocks() as demo:
 
     run.click(generate_images, inputs=[prompt,negative_prompt, samples, num_steps], outputs=gallery)
     
-    gr.Examples([["photo of traditional furniture","deformed", 1, 50]],
+    gr.Examples([["photo of sshh shoe","deformed", 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>')
 
 demo.launch(debug=True)