app.py

import gradio as gr
from transformers import CLIPProcessor, CLIPModel

# Load CLIP model and processor
model_name = "openai/clip-vit-base-patch32"
processor = CLIPProcessor.from_pretrained(model_name)
model = CLIPModel.from_pretrained(model_name)

def generate_3d_image(text_prompt):
    # Encode the text prompt
    inputs = processor(text=text_prompt, return_tensors="pt")

    # Generate image from text prompt
    output = model.get_image(inputs.pixel_values)

    return "Image generated successfully based on the text prompt."

# Create a Gradio interface for generating 3D images
iface = gr.Interface(
    fn=generate_3d_image,
    inputs=gr.inputs.Textbox(lines=5, label="Enter a text prompt for 3D image generation"),
    outputs="text",
    title="3D Image Generator",
    description="Enter a text prompt to generate a 3D image render."
)

iface.launch()