Spaces:
Sleeping
Sleeping
| import gradio as gr | |
| import replicate | |
| import time | |
| DEPLOYMENT_URIS = { | |
| "Lora 500": "dd-ds-ai/abendblatt-lora-500", | |
| "Lora 1000": "dd-ds-ai/lora-test-01-deployment-test", | |
| "Lora 2000": "dd-ds-ai/abendblatt-lora-2000" | |
| } | |
| def generate_image(model_selection, lora_scale, guidance_scale, prompt_strength, num_steps, prompt): | |
| # deployment_uri = DEPLOYMENT_URIS[model_selection] | |
| # deployment = replicate.deployments.get(deployment_uri) | |
| # | |
| # prediction = deployment.predictions.create( | |
| # input={ | |
| # "model": "dev", | |
| # "lora_scale": lora_scale, | |
| # "num_outputs": 1, | |
| # "aspect_ratio": "1:1", | |
| # "output_format": "webp", | |
| # "guidance_scale": guidance_scale, | |
| # "output_quality": 90, | |
| # "prompt_strength": prompt_strength, | |
| # "extra_lora_scale": 1, | |
| # "num_inference_steps": num_steps, | |
| # "prompt": prompt | |
| # } | |
| # ) | |
| # prediction.wait() | |
| # output = prediction.output | |
| # image_url = output[0] if output else None | |
| time.sleep(20) | |
| image_url = "https://external-content.duckduckgo.com/iu/?u=https%3A%2F%2Fi1.sndcdn.com%2Fartworks-000207677710-z7mg8u-t500x500.jpg&f=1&nofb=1&ipt=54d62f19e1816c166bec632275277c4118a940853b2cd93d1c673ea487d9dfee&ipo=images" | |
| return image_url | |
| # Gradio-Interface erstellen | |
| def create_gradio_interface(): | |
| model_selection = gr.Radio(choices=["Lora 500", "Lora 1000", "Lora 2000"], label="Model Selection", value="Lora 1000") | |
| lora_scale = gr.Slider(0, 2, value=1, step=0.1, label="Lora Scale") | |
| guidance_scale = gr.Slider(1, 10, value=3.5, step=0.1, label="Guidance Scale") | |
| prompt_strength = gr.Slider(0, 1, value=0.8, step=0.1, label="Prompt Strength") | |
| num_steps = gr.Slider(1, 50, value=28, step=1, label="Number of Inference Steps") | |
| prompt = gr.Textbox(label="Prompt", value="a person reading the hamburger abendblatt newspaper") | |
| generate_btn = gr.Button("Bild generieren") | |
| interface = gr.Interface( | |
| fn=generate_image, | |
| inputs=[model_selection, lora_scale, guidance_scale, prompt_strength, num_steps, prompt], | |
| outputs=gr.Image(label="Generated Image"), | |
| ) | |
| interface.launch(share=True) | |
| # Starte die Gradio-App | |
| if __name__ == "__main__": | |
| create_gradio_interface() | |