Upload keras_txt2img.py

diffusion_webui/stable_diffusion/keras_txt2img.py

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+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