Delete app.py

app.py

@@ -1,58 +0,0 @@
-import gradio as gr
-import numpy as np
-from PIL import Image
-
-APP_TITLE = "DeepFaceLab Clone"
-APP_DESCRIPTION = (
-    "Ultra-high-fidelity face swap system inspired by DeepFaceLab.\n\n"
-    "This interface is the foundation for identity-preserving face transformation."
-)
-
-def validate_image(img):
-    if img is None:
-        return False
-    if not isinstance(img, Image.Image):
-        return False
-    return True
-
-def placeholder_face_swap(source_img, target_img):
-    """
-    Placeholder logic.
-    This function will later be replaced by:
-    - Face detection
-    - Alignment
-    - Encoder-decoder inference
-    - Blending & post-processing
-    """
-    if not validate_image(source_img) or not validate_image(target_img):
-        return "Please upload both source and target images.", None
-
-    # Temporary visual confirmation (side-by-side)
-    src = source_img.resize((512, 512))
-    tgt = target_img.resize((512, 512))
-    combined = Image.new("RGB", (1024, 512))
-    combined.paste(src, (0, 0))
-    combined.paste(tgt, (512, 0))
-
-    return "Pipeline initialized successfully.", combined
-
-with gr.Blocks(title=APP_TITLE) as demo:
-    gr.Markdown(f"# {APP_TITLE}")
-    gr.Markdown(APP_DESCRIPTION)
-
-    with gr.Row():
-        source_image = gr.Image(label="Source Face", type="pil")
-        target_image = gr.Image(label="Target Face", type="pil")
-
-    run_button = gr.Button("Run Face Swap")
-
-    status_output = gr.Textbox(label="Status", interactive=False)
-    image_output = gr.Image(label="Output Preview")
-
-    run_button.click(
-        fn=placeholder_face_swap,
-        inputs=[source_image, target_image],
-        outputs=[status_output, image_output],
-    )
-
-demo.launch()