Add Gradio app (app.py), requirements for Space, and README

README_gradio.md

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+Run locally
+
+1) Install core requirements from the repo (CUDA-compatible torch recommended).
+2) Install UI deps:
+
+   python3 -m pip install -r requirements-gradio.txt
+
+3) Ensure pretrained weights are available at `pretrained_models/` (or symlink).
+4) Launch:
+
+   python3 app.py
+
+Hugging Face Space
+
+- Add `app.py` as the entry point.
+- Add `requirements.txt` and `requirements-gradio.txt` to the Space (merge if desired).
+- Make sure all large weights are present in `pretrained_models/` (LFS) or fetched at build time.
+

app.py

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+import os
+import tempfile
+import logging
+from typing import Tuple, Dict
+
+import gradio as gr
+from PIL import Image
+
+from runners.simple_runner import SimpleRunner
+
+
+# -----------------------------------------------------------------------------
+# Logging (use lazy % formatting as requested)
+# -----------------------------------------------------------------------------
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger("sfe-app")
+
+
+# -----------------------------------------------------------------------------
+# Model bootstrap (load once and reuse)
+# -----------------------------------------------------------------------------
+RUNNER: SimpleRunner | None = None
+
+
+def get_runner() -> SimpleRunner:
+    global RUNNER
+    if RUNNER is None:
+        logger.info("Initializing SimpleRunner with %s", "pretrained_models/sfe_editor_light.pt")
+        RUNNER = SimpleRunner(
+            editor_ckpt_pth="pretrained_models/sfe_editor_light.pt",
+        )
+    return RUNNER
+
+
+# -----------------------------------------------------------------------------
+# Attribute catalog and recommended ranges
+# -----------------------------------------------------------------------------
+# Each entry maps a friendly attribute name to the internal editing name and a
+# recommended power range for the slider.
+ATTRIBUTE_MAP: Dict[str, Tuple[str, Tuple[float, float]]] = {
+    # Face semantics
+    "Smile": ("fs_smiling", (-10.0, 10.0)),
+    "Age": ("age", (-10.0, 10.0)),  # interfacegan_directions
+    "Female features": ("gender", (-10.0, 7.0)),  # stylespace_directions (positive adds femininity)
+
+    # Facial hair
+    # trimmed_beard removes beard for positive power; use negative to add
+    "Beard": ("trimmed_beard", (-30.0, 30.0)),
+    # goatee removes goatee for positive; negative tends to add
+    "Mustache/Goatee": ("goatee", (-7.0, 7.0)),
+
+    # Accessories & cosmetics
+    "Glasses": ("fs_glasses", (-20.0, 30.0)),
+    "Makeup": ("fs_makeup", (-10.0, 15.0)),
+
+    # Hair style (pretrained mappers)
+    "Curly hair": ("curly_hair", (0.0, 0.12)),  # styleclip_directions
+    "Afro": ("afro", (0.0, 0.14)),
+
+    # Hair color via global text mapper
+    # You can also type custom prompts below
+    "Orange hair (text)": ("styleclip_global_a face_a face with orange hair_0.18", (0.0, 0.2)),
+    "Blonde hair (text)": ("styleclip_global_a face_a face with blonde hair_0.18", (0.0, 0.2)),
+}
+
+
+def recommended_range(attr_name: str) -> Tuple[float, float]:
+    edit_name, rng = ATTRIBUTE_MAP[attr_name]
+    return rng
+
+
+def run_edit(
+    image: Image.Image,
+    attribute: str,
+    strength: float,
+    align_face: bool,
+    use_bg_mask: bool,
+    custom_text_edit: str,
+) -> Image.Image:
+    """Run a single attribute edit and return the edited image."""
+    runner = get_runner()
+
+    # Determine editing name and clip strength into the suggested range
+    edit_name, (lo, hi) = ATTRIBUTE_MAP[attribute]
+    if custom_text_edit and attribute.endswith("(text)"):
+        # Allow overriding the default text prompt
+        if custom_text_edit.strip():
+            edit_name = custom_text_edit.strip()
+
+    clipped_strength = max(lo, min(hi, strength))
+    if clipped_strength != strength:
+        logger.info("Clipped strength from %s to %s for %s", strength, clipped_strength, attribute)
+
+    # Persist input to a temp file for the runner
+    with tempfile.TemporaryDirectory() as tmpdir:
+        inp_path = os.path.join(tmpdir, "input.jpg")
+        out_path = os.path.join(tmpdir, "edited.jpg")
+        image.convert("RGB").save(inp_path)
+
+        logger.info("Editing %s with power %s", edit_name, clipped_strength)
+        _ = runner.edit(
+            orig_img_pth=inp_path,
+            editing_name=edit_name,
+            edited_power=clipped_strength,
+            save_pth=out_path,
+            align=align_face,
+            use_mask=use_bg_mask,
+        )
+
+        return Image.open(out_path).convert("RGB")
+
+
+def build_ui() -> gr.Blocks:
+    with gr.Blocks(css="footer {visibility: hidden}") as demo:
+        gr.Markdown("""
+        **StyleFeatureEditor – Facial Attribute Editing**  
+        Upload a face and apply edits like smile, age, beard, hair style/color, glasses, and makeup.  
+        Tip: For Beard/Goatee, negative strength tends to add facial hair.
+        """)
+
+        with gr.Row():
+            with gr.Column():
+                inp = gr.Image(type="pil", label="Input face", sources=["upload", "clipboard"])
+                attr = gr.Dropdown(
+                    choices=list(ATTRIBUTE_MAP.keys()),
+                    value="Smile",
+                    label="Attribute",
+                )
+                strength = gr.Slider(-15, 15, value=5, step=0.01, label="Strength (p)")
+                align_face = gr.Checkbox(value=False, label="Align face before editing")
+                use_bg_mask = gr.Checkbox(value=False, label="Use background mask (reduce artifacts)")
+                custom_text = gr.Textbox(
+                    value="",
+                    label="Custom text edit (StyleCLIP Global Mapper)",
+                    placeholder="styleclip_global_a face_a face with black hair_0.18",
+                )
+                run_btn = gr.Button("Run edit")
+
+            with gr.Column():
+                out = gr.Image(type="pil", label="Edited output")
+
+        # Update slider range based on attribute selection
+        def _on_attr_change(name: str):
+            lo, hi = recommended_range(name)
+            # Keep current value within new bounds
+            new_val = max(lo, min(hi, strength.value if hasattr(strength, "value") else 0))
+            return gr.Slider.update(minimum=lo, maximum=hi, value=new_val)
+
+        attr.change(_on_attr_change, inputs=attr, outputs=strength)
+
+        run_btn.click(
+            fn=run_edit,
+            inputs=[inp, attr, strength, align_face, use_bg_mask, custom_text],
+            outputs=out,
+        )
+
+    return demo
+
+
+if __name__ == "__main__":
+    app = build_ui()
+    # On Spaces, the port/host are managed by the platform; run local defaults otherwise
+    app.launch()
+
+

requirements-gradio.txt

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+gradio==4.44.0
+numpy>=1.23
+Pillow>=9.5
+torch
+torchvision
+omegaconf==2.1.2
+

requirements.txt

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+gradio==4.44.0
+numpy>=1.23
+Pillow>=9.5
+torch
+torchvision
+omegaconf==2.1.2
+