add cgange

app.py

@@ -0,0 +1,30 @@
+import streamlit as st
+import torch
+from diffusers import AutoPipelineForImage2Image
+from PIL import Image
+
+st.title("Stable Diffusion Image-to-Image")
+
+# Load the pipeline
+pipeline = AutoPipelineForImage2Image.from_pretrained(
+    "stabilityai/stable-diffusion-2-1",
+    torch_dtype=torch.float16,
+    variant="fp16",
+    use_safetensors=True
+)
+pipeline.enable_model_cpu_offload()
+# pipeline.enable_xformers_memory_efficient_attention()  # ❌ REMOVE OR COMMENT THIS LINE
+
+# Upload an image
+uploaded_file = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])
+
+if uploaded_file:
+    init_image = Image.open(uploaded_file).convert("RGB")
+    st.image(init_image, caption="Uploaded Image", use_column_width=True)
+
+    prompt = st.text_input("Enter a prompt", "A futuristic city at sunset")
+
+    if st.button("Generate Image"):
+        with st.spinner("Generating..."):
+            image = pipeline(prompt, image=init_image).images[0]
+            st.image(image, caption="Generated Image", use_column_width=True)