Delete Image_Generator.py

Image_Generator.py

@@ -1,109 +0,0 @@
-import streamlit as st
-from diffusers import DiffusionPipeline
-import torch
-from PIL import Image
-# Custom CSS to improve the appearance
-st.markdown("""
-<style>
-    .stApp {
-        background-image:linear-gradient(to bottom, #000000 ,#000814 ,#001d3d, #003566);
-    }
-    .main-title {
-        font-size: 3rem !important;
-        color: #f1faee;
-        text-align: center;
-        padding: 1rem 0;
-    }
-    .subtitle {
-        font-size: 1.2rem;
-        color: #f1faee;
-        text-align: center;
-        margin-bottom: 2rem;
-    }
-    .stTextInput > div > div > input {
-        font-size: 1.2rem;
-    }
-    .generate-button {
-        font-size: 1.2rem;
-        border-radius: 10px;
-        padding: 0.5rem 1rem;
-    }
-    .info-section {
-        background-color: #ffffff;
-        padding: 1rem;
-        border-radius: 10px;
-        margin-top: 2rem;
-    }
-</style>
-""", unsafe_allow_html=True)
-
-# Initialize the Stable Diffusion pipeline
-@st.cache_resource
-def load_image_model():
-    # Ensure that you are using the correct device (GPU if available)
-    pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
-    if torch.cuda.is_available():
-        pipe.to("cuda")
-    return pipe
-
-pipe = load_image_model()
-
-# Streamlit interface
-st.markdown("<h1 class='main-title'>🖼️ AI Image Generator</h1>", unsafe_allow_html=True)
-st.markdown("<p class='subtitle'>Describe the image you want to create, and the AI will generate it for you.</p>", unsafe_allow_html=True)
-
-# Main interaction area
-image_description = st.text_input("🖊️ Describe the image you want to create", 
-                                  placeholder="E.g., A sunset over a mountain range")
-
-if st.button("🎨 Generate Image"):
-    if image_description.strip():
-        with st.spinner("🎨 Generating your image..."):
-            st.warning("Image generation may take some time. Please be patient.")  # Display warning message
-            try:
-                # Generate the image
-                image = pipe(image_description).images[0]
-
-                # Display the generated image
-                st.image(image, caption="Generated Image", use_column_width=True)
-
-                # Provide download button for the generated image
-                img_path = "generated_image.png"
-                image.save(img_path)
-
-                with open(img_path, "rb") as file:
-                    st.download_button(
-                        label="📥 Download Image",
-                        data=file,
-                        file_name="generated_image.png",
-                        mime="image/png"
-                    )
-            except Exception as e:
-                st.error(f"😕 Oops! An error occurred: {str(e)}")
-    else:
-        st.warning("🤔 Please enter a description for your image.")
-
-# Information sections
-st.markdown("---")
-
-col1, col2 = st.columns(2)
-
-with col1:
-    st.markdown("### 🌟 How it works")
-    st.markdown("""
-    1. 📝 Describe the image you want
-    2. 🖱️ Click 'Generate Image'
-    3. 🎨 View your AI-generated artwork
-    4. 📥 Download and share!
-    """)
-
-with col2:
-    st.markdown("### 🎨 Tips for great results")
-    st.markdown("""
-    - Be specific about objects and settings
-    - Mention style, genre, or mood
-    - Describe the colors and lighting
-    """)
-
-# Footer
-st.markdown("---")