Spaces:
Runtime error
Runtime error
| import logging | |
| import gradio as gr | |
| import keras_cv | |
| import numpy as np | |
| import tensorflow as tf | |
| from huggingface_hub import from_pretrained_keras | |
| logging.basicConfig(level=logging.INFO) | |
| logger = logging.getLogger(__file__) | |
| prompt_token = "<token>" | |
| text_encoder_url = "Dimitre/stablediffusion-canarinho_pistola" | |
| logger.info(f'Inversed token used: "{prompt_token}"') | |
| logger.info(f'Loading text encoder from: "{text_encoder_url}"') | |
| stable_diffusion = keras_cv.models.StableDiffusion() | |
| stable_diffusion.tokenizer.add_tokens(prompt_token) | |
| text_encoder = from_pretrained_keras("Dimitre/stablediffusion-canarinho_pistola") | |
| stable_diffusion._text_encoder = text_encoder | |
| stable_diffusion._text_encoder.compile(jit_compile=True) | |
| def generate_fn(input_prompt: str) -> np.ndarray: | |
| """Generates images from a text prompt | |
| Args: | |
| input_prompt (str): Text input prompt | |
| Returns: | |
| np.ndarray: Generated image | |
| """ | |
| generated = stable_diffusion.text_to_image( | |
| prompt=input_prompt, batch_size=1, num_steps=50 | |
| ) | |
| return generated[0] | |
| iface = gr.Interface( | |
| fn=generate_fn, | |
| title="Textual Inversion", | |
| description=f'Textual Inversion Demo, use "{prompt_token}" as the textual inversion token as shown in the examples', | |
| article="Note: Keras-cv uses lazy initialization, so the first use will be slower while the model is initialized.", | |
| inputs=gr.Textbox( | |
| label="Prompt", | |
| show_label=False, | |
| max_lines=2, | |
| placeholder="Enter your prompt", | |
| elem_id="input-prompt", | |
| ), | |
| outputs=gr.Image(), | |
| examples=[[f"A {prompt_token} portrait, 4k, highly detailed, highest quality, 8k"]], | |
| ) | |
| if __name__ == "__main__": | |
| app, local_url, share_url = iface.launch() | |