Delete keras_txt2img.py

keras_txt2img.py

@@ -1,116 +0,0 @@
-from huggingface_hub import from_pretrained_keras
-from keras_cv import models
-from tensorflow import keras
-
-import gradio as gr
-
-stable_model_list = [
-    "keras-dreambooth/dreambooth_diffusion_model"
-]
-
-stable_prompt_list = [
-        "a photo of a man.",
-        "a photo of a girl."
-    ]
-
-stable_negative_prompt_list = [
-        "bad, ugly",
-        "deformed"
-    ]
-
-def keras_stable_diffusion(
-    model_path:str,
-    prompt:str,
-    negative_prompt:str,
-    guidance_scale:int,
-    num_inference_step:int,
-    height:int,
-    width:int,
-    ):
-
-    keras.mixed_precision.set_global_policy("mixed_float16")
-
-    sd_dreambooth_model = models.StableDiffusion(
-        img_width=height, 
-        img_height=width
-        )
-    
-    db_diffusion_model = from_pretrained_keras(model_path)
-    sd_dreambooth_model._diffusion_model = db_diffusion_model
-
-    generated_images = sd_dreambooth_model.text_to_image(
-        prompt=prompt,
-        negative_prompt=negative_prompt,
-        num_steps=num_inference_step,
-        unconditional_guidance_scale=guidance_scale
-    )
-
-    return generated_images
-
-def keras_stable_diffusion_app():
-    with gr.Tab('Keras Diffusion'):
-        keras_text2image_model_path = gr.Dropdown(
-            choices=stable_model_list, 
-            value=stable_model_list[0], 
-            label='Text-Image Model Id'
-        )
-
-        keras_text2image_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_prompt_list[0], 
-            label='Prompt'
-        )
-
-        keras_text2image_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
-        )
-
-        with gr.Accordion("Advanced Options", open=False):
-            keras_text2image_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            keras_text2image_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-            keras_text2image_height = gr.Slider(
-                minimum=128, 
-                maximum=1280, 
-                step=32, 
-                value=512, 
-                label='Image Height'
-            )
-
-            keras_text2image_width = gr.Slider(
-                minimum=128, 
-                maximum=1280, 
-                step=32, 
-                value=768, 
-                label='Image Height'
-            )
-
-        keras_text2image_predict = gr.Button(value='Generator')
-    
-    variables = {
-        "model_path": keras_text2image_model_path,
-        "prompt": keras_text2image_prompt,
-        "negative_prompt": keras_text2image_negative_prompt,
-        "guidance_scale": keras_text2image_guidance_scale,
-        "num_inference_step": keras_text2image_num_inference_step,
-        "height": keras_text2image_height,
-        "width": keras_text2image_width,
-        "predict": keras_text2image_predict
-    }
-
-    return variables