Create app.py

app.py

@@ -0,0 +1,39 @@
+rom huggingface_hub import from_pretrained_keras
+from keras_cv import models
+import gradio as gr
+
+sd_dreambooth_model = models.StableDiffusion(
+    img_width=512, img_height=512
+)
+db_diffusion_model = from_pretrained_keras("merve/dreambooth-bioshock")
+sd_dreambooth_model._diffusion_model = db_diffusion_model
+
+# generate images
+def infer(prompt, negative_prompt, num_imgs_to_gen, num_steps, guidance_scale):
+    generated_images = sd_dreambooth_model.text_to_image(
+        prompt,
+        negative_prompt=negative_prompt,
+        batch_size=num_imgs_to_gen,
+        num_steps=num_steps,
+        unconditional_guidance_scale=guidance_scale
+    )
+    return generated_images 
+    
+    
+# output = gr.Gallery(label="Outputs").style(grid=(2,2))
+
+# pass function, input type for prompt, the output for multiple images
+gr.Interface(
+    infer, [
+        gr.Textbox(label="Positive Prompt", value="a highly detailed photo of sks bskscnry"),
+        gr.Textbox(label="Negative Prompt", value="ugly, low quality"),
+        gr.Slider(label='Number of gen image', minimum=1, maximum=4, value=2, step=1),
+        gr.Slider(label="Inference Steps",value=50),
+        gr.Number(label='Guidance scale', value=7.5),
+    ], [
+        gr.Gallery(show_label=False),
+    ],
+    title="Dreambooth Teddy",
+    description = "This is a dreambooth model fine-tuned on images of Bioshock sceneries. To play with the demo, input the concept with {sks bskscnry}.",
+    examples = [["a highly detailed photo of sks bskscnry", "", 2, 50, 7.5]],
+    ).launch()