Remove Gradio path; run Streamlit UI only

app.py

@@ -4,7 +4,6 @@
 import numpy as np
 import pandas as pd
 import streamlit as st
-import gradio as gr
 import os
 from datetime import datetime
 from PIL import Image
@@ -42,6 +41,7 @@ if "color_to_label" not in st.session_state:
 
 if 'reuse_image' not in st.session_state:
     st.session_state.reuse_image = None
+
 def set_image(img):
     st.session_state.reuse_image = img
 
@@ -120,14 +120,12 @@ def run_streamlit_ui():
         im[drawing]=[0,0,0,0] # RGBA
         
         if st.button('Submit'):
-            
             with st.spinner("AI is doing the magic!"):
-                output = process_inpaint(np.array(img_input), np.array(im)) #TODO Put button here
+                output = process_inpaint(np.array(img_input), np.array(im))
                 img_output = Image.fromarray(output).convert("RGB")
             
             st.write("AI has finished the job!")
             st.image(img_output)
-            # reuse = st.button('Edit again (Re-use this image)', on_click=set_image, args=(inpainted_img, ))
             
             uploaded_name = os.path.splitext(uploaded_file.name)[0]
             image_download_button(
@@ -141,49 +139,7 @@ def run_streamlit_ui():
                     "upload then remove the artifacts.")
 
 
-def _prepare_mask_rgba(image: Image.Image, mask: np.ndarray) -> np.ndarray:
-    if mask is None:
-        rgba = np.zeros((image.height, image.width, 4), dtype=np.uint8)
-        rgba[:, :, 3] = 255
-        return rgba
-    mask_img = Image.fromarray(mask).convert("L").resize(image.size)
-    mask_np = np.array(mask_img)
-    rgba = np.zeros((image.height, image.width, 4), dtype=np.uint8)
-    rgba[:, :, :3] = 0
-    rgba[:, :, 3] = 255
-    rgba[mask_np > 0, 3] = 0
-    return rgba
-
-
-def gradio_inpaint(data):
-    if data is None:
-        return None
-    img = data.get("image") if isinstance(data, dict) else data
-    mask = data.get("mask") if isinstance(data, dict) else None
-    if img is None:
-        return None
-    if not isinstance(img, Image.Image):
-        img = Image.fromarray(img)
-    img_rgba = img.convert("RGBA")
-    rgba_mask = _prepare_mask_rgba(img_rgba, mask)
-    output = process_inpaint(np.array(img_rgba), rgba_mask)
-    return Image.fromarray(output).convert("RGB")
-
-
-with gr.Blocks() as demo:
-    gr.Markdown("# AI Photo Object Removal")
-    gr.Markdown("Draw on the image to remove objects. Use the Sketch tool to paint the mask.")
-    with gr.Row():
-        input_image = gr.Image(label="Image", type="pil", tool="sketch", image_mode="RGBA", sources=["upload"]) 
-    run_btn = gr.Button("Remove Object")
-    output_image = gr.Image(label="Result", type="pil")
-    run_btn.click(gradio_inpaint, inputs=input_image, outputs=output_image)
-
-
 if __name__ == "__main__":
-    # Default to Gradio for HF Spaces
-    use_gradio = True
-    if use_gradio:
-        demo.queue().launch()
-    else:
-        run_streamlit_ui()
+    # Streamlit Spaces run the file with `streamlit run app.py`
+    # So keep a safe guard for direct execution as well
+    run_streamlit_ui()