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@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+examples/man_laughing.mp4 filter=lfs diff=lfs merge=lfs -text
+examples/man_sad.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,13 +1,20 @@
 ---
-title: Ltx 2.3 Beard Removal
-emoji: 🏆
-colorFrom: yellow
+title: LTX-2.3 Beard Removal
+emoji: 🪒
+colorFrom: blue
 colorTo: gray
 sdk: gradio
-sdk_version: 6.18.0
-python_version: '3.12'
+sdk_version: 6.13.0
+python_version: "3.12"
 app_file: app.py
 pinned: false
+hardware: zero-a10g
+short_description: Remove beards from video with an LTX-2.3 IC-LoRA
+models:
+  - diffusers/LTX-2.3-Diffusers
+  - linoyts/LTX-2.3-loras
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🪒 LTX-2.3 Beard Removal (Instant Shave)
+Removes beard, mustache and stubble from a person in a video while preserving identity, expression and motion.
+IC-LoRA on LTX-2.3 (`LTX2InContextPipeline`, 30 steps, guidance 4.0, STG, 25fps, `REMOVEBEARD` trigger).

app.py

@@ -0,0 +1,171 @@
+import os
+
+os.environ.setdefault("TORCH_COMPILE_DISABLE", "1")
+os.environ.setdefault("TORCHDYNAMO_DISABLE", "1")
+
+import random
+import tempfile
+
+import numpy as np
+import imageio.v3 as iio
+import spaces
+import torch
+import gradio as gr
+from PIL import Image, ImageOps
+from huggingface_hub import hf_hub_download
+from safetensors.torch import load_file
+
+from diffusers import LTX2InContextPipeline
+from diffusers.pipelines.ltx2.pipeline_ltx2_ic_lora import LTX2ReferenceCondition
+from diffusers.utils import load_video, encode_video
+
+# --- Config -----------------------------------------------------------------
+# Beard-removal IC-LoRA — non-distilled recipe: 30 steps, guidance 4.0, STG, 25 fps.
+BASE_MODEL = "diffusers/LTX-2.3-Diffusers"
+LORA_REPO = "linoyts/LTX-2.3-loras"
+LORA_FILE = "ltx-2.3-22b-ic-lora-instant-shave-0.9.safetensors"
+LORA_SCALE = 1.0
+FPS = 25  # the card recommends 25 fps
+NUM_STEPS = 30
+GUIDANCE = 4.0
+STG_BLOCKS = [29]
+NEGATIVE = ("beard, mustache, facial hair, stubble, worst quality, "
+            "inconsistent motion, blurry, jittery, distorted")
+MAX_SEED = np.iinfo(np.int32).max
+HF_TOKEN = os.environ.get("HF_TOKEN")
+
+RES_PRESETS = {"Fast (768×448)": (768, 448), "Quality (960×544)": (960, 544)}
+FRAME_CHOICES = [33, 49, 73, 97, 121]
+
+pipe = LTX2InContextPipeline.from_pretrained(BASE_MODEL, torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+pipe.vae.enable_tiling()
+_lora_path = hf_hub_download(LORA_REPO, LORA_FILE, token=HF_TOKEN)
+pipe.load_lora_weights(load_file(_lora_path), adapter_name="shave")
+pipe.set_adapters("shave", LORA_SCALE)
+
+
+def _src_fps(path, default=FPS):
+    try:
+        return float(iio.immeta(path, plugin="pyav").get("fps", default)) or default
+    except Exception:
+        return default
+
+
+def _load_frames(path, num_frames, width, height):
+    frames = load_video(path)
+    if not frames:
+        return []
+    fps = _src_fps(path)
+    out = []
+    for i in range(num_frames):
+        idx = min(int(round(i / FPS * fps)), len(frames) - 1)
+        out.append(ImageOps.fit(frames[idx].convert("RGB"), (width, height), Image.LANCZOS))
+    return out
+
+
+def _pick_resolution(first_frame, preset):
+    w, h = RES_PRESETS[preset]
+    if first_frame.height > first_frame.width:
+        w, h = h, w
+    return w, h
+
+
+def _build_prompt(prompt):
+    desc = prompt.strip() or "the same person, completely clean-shaven"
+    return (f"REMOVEBEARD {desc}, completely smooth and clean-shaven face, bare skin, "
+            f"no beard, no stubble, no facial hair; identity, expression, motion, lighting and scene unchanged.")
+
+
+def _export(video_np, audio, path):
+    kw = {}
+    if audio is not None:
+        kw = dict(audio=audio[0].float().cpu(), audio_sample_rate=pipe.vocoder.config.output_sampling_rate)
+    encode_video(video_np, fps=FPS, output_path=path, **kw)
+
+
+def _duration(*args, **kwargs):
+    preset = next((a for a in args if isinstance(a, str) and a in RES_PRESETS), "Fast")
+    num_frames = next((a for a in args if isinstance(a, int) and a in FRAME_CHOICES), 49)
+    per_frame = 4.2 if "Quality" in str(preset) else 3.0  # 30 steps + CFG + STG
+    return int(120 + int(num_frames) * per_frame)
+
+
+@spaces.GPU(duration=_duration)
+def shave(video, prompt, preset, num_frames, seed, randomize,
+          progress=gr.Progress(track_tqdm=True)):
+    if video is None:
+        raise gr.Error("Please upload a video of a bearded subject.")
+    if randomize:
+        seed = random.randint(0, MAX_SEED)
+    seed = int(seed)
+    num_frames = int(num_frames)
+
+    probe = load_video(video)
+    if not probe:
+        raise gr.Error("Could not read any frames from that video.")
+    width, height = _pick_resolution(probe[0], preset)
+    ref = _load_frames(video, num_frames, width, height)
+    full_prompt = _build_prompt(prompt)
+
+    def _cb(p, i, t, kw):
+        progress((i + 1) / NUM_STEPS, desc=f"Removing beard — step {i + 1}/{NUM_STEPS}")
+        return {}
+
+    video_out, audio_out = pipe(
+        prompt=full_prompt, negative_prompt=NEGATIVE,
+        reference_conditions=[LTX2ReferenceCondition(frames=ref, strength=1.0)],
+        reference_downscale_factor=1,
+        width=width, height=height, num_frames=num_frames, frame_rate=FPS,
+        num_inference_steps=NUM_STEPS, guidance_scale=GUIDANCE,
+        spatio_temporal_guidance_blocks=STG_BLOCKS,
+        generator=torch.Generator(device="cuda").manual_seed(seed),
+        output_type="np", return_dict=False, callback_on_step_end=_cb,
+    )
+    out_path = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name
+    _export(video_out[0], audio_out, out_path)
+    return out_path, seed
+
+
+with gr.Blocks(title="LTX-2.3 Beard Removal") as demo:
+    gr.Markdown(
+        "# 🪒 LTX-2.3 Beard Removal (Instant Shave)\n"
+        "Removes beard, mustache, and stubble from a person in a video while preserving identity, expression, "
+        "motion, lighting, and scene. Optionally describe the clean-shaven look and any sounds in one prompt. "
+        "IC-LoRA: [`linoyts/LTX-2.3-loras`](https://huggingface.co/linoyts/LTX-2.3-loras) · base: LTX-2.3."
+    )
+    with gr.Row():
+        with gr.Column():
+            video_in = gr.Video(label="Video of a bearded subject")
+            prompt = gr.Textbox(
+                label="Prompt — describe the clean-shaven subject/scene and any sounds (optional)", lines=3,
+                placeholder="a man with a completely smooth clean-shaven face, warm indoor light, laughing; warm hearty laughter and quiet room tone",
+            )
+            with gr.Accordion("Settings", open=False):
+                preset = gr.Dropdown(list(RES_PRESETS), value="Fast (768×448)", label="Resolution")
+                num_frames = gr.Dropdown(FRAME_CHOICES, value=49, label="Frames (25fps)")
+                randomize = gr.Checkbox(True, label="Randomize seed")
+                seed = gr.Slider(0, MAX_SEED, value=42, step=1, label="Seed")
+            run = gr.Button("Remove beard", variant="primary")
+        with gr.Column():
+            video_out = gr.Video(label="Clean-shaven result")
+            used_seed = gr.Number(label="Seed used", interactive=False)
+
+    run.click(shave, inputs=[video_in, prompt, preset, num_frames, seed, randomize],
+              outputs=[video_out, used_seed])
+
+    gr.Examples(
+        examples=[
+            ["examples/man_laughing.mp4",
+             "a man with a completely smooth clean-shaven face, no beard or stubble, laughing warmly in soft indoor light; warm hearty laughter and a quiet room tone",
+             "Fast (768×448)", 49, 42, False],
+            ["examples/man_sad.mp4",
+             "a young man with a completely smooth clean-shaven face, no stubble, neutral expression, soft daylight; quiet ambient room tone",
+             "Fast (768×448)", 49, 42, False],
+        ],
+        inputs=[video_in, prompt, preset, num_frames, seed, randomize],
+        outputs=[video_out, used_seed], fn=shave, cache_examples=True, cache_mode="lazy",
+    )
+
+if __name__ == "__main__":
+    demo.launch(show_error=True)

examples/man_laughing.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d6ae85ecf6f52e2a196102b81fb1b0f9f05eb47e817b85c7c51f783aaad891cc
+size 216129

examples/man_sad.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d3858d2f9e01d7a426e64f8c129752e67cb0897d92141f79eb0b1b32b4e6fa89
+size 230152

requirements.txt

@@ -0,0 +1,9 @@
+git+https://github.com/huggingface/diffusers
+transformers
+accelerate
+peft
+safetensors
+sentencepiece
+imageio
+imageio-ffmpeg
+av