Create app.py

app.py

@@ -0,0 +1,75 @@
+import streamlit as st
+from io import BytesIO
+import base64
+import os
+from replicate import Client
+from PIL import Image
+
+illuse = Client(api_token=os.getenv('REPLICATE'))
+model_name = "andreasjansson/illusion:75d51a73fce3c00de31ed9ab4358c73e8fc0f627dc8ce975818e653317cb919b"
+example_image = "https://replicate.delivery/pbxt/hHJNV9QteKX8DK2ckkUeXsqbEIKNGFXU1fN0MJoizz3iPlOjA/output-0.png"
+
+def generate(prompt, negative_prompt, qr_content, pattern_image, num_inference_steps, guidance_scale, width, height, seed, num_outputs, controlnet_conditioning_scale, border, qrcode_background):
+    try:
+        inputs = {
+            'prompt': prompt,
+            'negative_prompt': negative_prompt,
+            'qr_code_content': qr_content,
+            'num_inference_steps': num_inference_steps,
+            'guidance_scale': guidance_scale,
+            'width': width,
+            'height': height,
+            'seed': seed,
+            'num_outputs': num_outputs,
+            'controlnet_conditioning_scale': controlnet_conditioning_scale,
+            'border': border,
+            'qrcode_background': qrcode_background
+        }
+        if pattern_image is not None:
+            image = Image.open(pattern_image)
+            image_bytes = BytesIO()
+            image.save(image_bytes, format='PNG')
+            inputs['image'] = image_bytes
+
+        result_uris = illuse.run(
+            model_name,
+            input=inputs
+        )
+
+        return result_uris
+
+    except Exception as e:
+        print(e)
+        st.error(str(e))
+        return
+
+st.title("Illusion Diffusion by Aiconvert.online")
+st.markdown('<style>h1{color: #191970; text-align: center;}</style>', unsafe_allow_html=True)
+
+prompt = st.text_input("Prompt")
+negative_prompt = st.text_input("Negative")
+
+qr_content = st.text_input("QR Code Content", "https://youtube.com/")
+pattern_input = st.file_uploader("Pattern Image (if used, QR Code Content won't be used)", type=["jpg", "png", "jpeg"])
+
+st.sidebar.markdown("## Advanced Settings")
+
+with st.sidebar.expander("Advanced Settings", expanded=True):
+    num_inference_steps = st.slider("num_inference_steps", min_value=20, max_value=100, step=1, value=42)
+    guidance_scale = st.slider("guidance_scale", min_value=0.1, max_value=30.0, step=0.01, value=14.5)
+    width = st.slider("width", min_value=128, max_value=1024, step=8, value=768)
+    height = st.slider("height", min_value=128, max_value=1024, step=8, value=768)
+    seed = st.number_input("seed", value=-1)
+    num_outputs = st.slider("num_outputs", min_value=1, max_value=4, step=1, value=1)
+    controlnet_conditioning_scale = st.slider("controlnet_conditioning_scale", min_value=0, max_value=4, step=1, value=1)
+    border = st.slider("border", min_value=0, max_value=4, step=1, value=4)
+    qrcode_background = st.selectbox("qrcode_background", options=['gray', 'white'], index=1)
+
+if st.button("Generate"):
+    with st.spinner("Running..."):
+        result_uris = generate(prompt, negative_prompt, qr_content, pattern_input, num_inference_steps, guidance_scale, width, height, seed, num_outputs, controlnet_conditioning_scale, border, qrcode_background)
+    for uri in result_uris:
+        st.image(uri)
+
+st.image(example_image, caption='Example Image', use_column_width=True)
+st.markdown("powered with ❤️ by Aiconvert.online")