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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/landscape_dry.mp4 filter=lfs diff=lfs merge=lfs -text
+examples/man_dancing_dry.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,13 +1,20 @@
 ---
-title: Ltx 2.3 Water Simulation
-emoji: 🦀
-colorFrom: red
-colorTo: yellow
+title: LTX-2.3 Water Simulation
+emoji: 🌊
+colorFrom: blue
+colorTo: green
 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: Add water VFX to video with an LTX-2.3 IC-LoRA
+models:
+  - diffusers/LTX-2.3-Distilled-Diffusers
+  - ltx-community/LTX-2.3-loras
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🌊 LTX-2.3 Water Simulation
+Adds naturally-moving water (rivers, surf, rain, floods, splashes) to a dry clip while preserving subject,
+framing and camera. IC-LoRA on distilled LTX-2.3 (`LTX2InContextPipeline`, 8-step, `ADD WATER` trigger, strength ~1.2).

app.py

@@ -0,0 +1,176 @@
+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.pipelines.ltx2.utils import DISTILLED_SIGMA_VALUES
+from diffusers.utils import load_video, encode_video
+
+# --- Config -----------------------------------------------------------------
+# Water-simulation IC-LoRA — distilled recipe (8 sigmas, CFG off), strength sweet-spot ~1.2.
+BASE_MODEL = "diffusers/LTX-2.3-Distilled-Diffusers"
+LORA_REPO = "ltx-community/LTX-2.3-loras"
+LORA_FILE = "ltx-2.3-22b-ic-lora-water-simulation-0.9.safetensors"
+LORA_SCALE = 1.2
+FPS = 24
+NUM_STEPS = len(DISTILLED_SIGMA_VALUES)
+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 = [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="water")
+pipe.set_adapters("water", 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 "a flowing stream of clear water"
+    return (
+        "Reference shows the dry scene. Edited shows the same scene with water added. "
+        f"ADD WATER {desc}. "
+        "Subject identity, clothing, framing, and background geometry are identical to the reference; "
+        "only water-related elements differ between reference and edited."
+    )
+
+
+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), 73)
+    per_frame = 1.6 if "Quality" in str(preset) else 1.0
+    return int(70 + int(num_frames) * per_frame)
+
+
+@spaces.GPU(duration=_duration)
+def add_water(video, prompt, strength, preset, num_frames, seed, randomize,
+              progress=gr.Progress(track_tqdm=True)):
+    if video is None:
+        raise gr.Error("Please upload a 'dry' video to add water to.")
+    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)
+    pipe.set_adapters("water", float(strength))
+    full_prompt = _build_prompt(prompt)
+
+    def _cb(p, i, t, kw):
+        progress((i + 1) / NUM_STEPS, desc=f"Adding water — step {i + 1}/{NUM_STEPS}")
+        return {}
+
+    video_out, audio_out = pipe(
+        prompt=full_prompt, negative_prompt="",
+        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, sigmas=DISTILLED_SIGMA_VALUES,
+        guidance_scale=1.0, stg_scale=0.0, audio_guidance_scale=1.0, audio_stg_scale=0.0,
+        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 Water Simulation") as demo:
+    gr.Markdown(
+        "# 🌊 LTX-2.3 Water Simulation\n"
+        "Add believable, naturally-moving water to a dry clip — rivers, surf, rain, waterfalls, floods, "
+        "splashes — that interacts with the moving scene, while subject, clothing, framing and camera stay "
+        "exactly as shot. Describe the water (and any sounds) in one prompt; the trigger `ADD WATER` is added for you. "
+        "IC-LoRA: [`ltx-community/LTX-2.3-loras`](https://huggingface.co/ltx-community/LTX-2.3-loras) · base: distilled LTX-2.3."
+    )
+    with gr.Row():
+        with gr.Column():
+            video_in = gr.Video(label="Dry input video")
+            prompt = gr.Textbox(
+                label="Describe the water — type, motion, how it interacts, plus any sounds", lines=3,
+                placeholder="a clear shallow stream braiding around their legs with white foam crests and glistening wet ground; rushing water, gentle splashing",
+            )
+            with gr.Accordion("Settings", open=False):
+                strength = gr.Slider(1.0, 1.6, value=1.2, step=0.05,
+                                     label="Water strength (1.2–1.3 natural · 1.35+ hard surface→sea · ≥1.5 max drama)")
+                preset = gr.Dropdown(list(RES_PRESETS), value="Fast (768×448)", label="Resolution")
+                num_frames = gr.Dropdown(FRAME_CHOICES, value=73, label="Frames (24fps)")
+                randomize = gr.Checkbox(True, label="Randomize seed")
+                seed = gr.Slider(0, MAX_SEED, value=42, step=1, label="Seed")
+            run = gr.Button("Add water", variant="primary")
+        with gr.Column():
+            video_out = gr.Video(label="Result with water")
+            used_seed = gr.Number(label="Seed used", interactive=False)
+
+    run.click(add_water, inputs=[video_in, prompt, strength, preset, num_frames, seed, randomize],
+              outputs=[video_out, used_seed])
+
+    gr.Examples(
+        examples=[
+            ["examples/man_dancing_dry.mp4",
+             "a clear shallow stream rushing and braiding around their legs with white foam crests and glistening wet floor, splashing with each step; rushing water and rhythmic splashes",
+             1.3, "Fast (768×448)", 73, 42, False],
+            ["examples/landscape_dry.mp4",
+             "a wide river flooding across the valley with rippling reflections and drifting foam, mist rising off the surface; flowing water and a distant waterfall",
+             1.25, "Fast (768×448)", 73, 42, False],
+        ],
+        inputs=[video_in, prompt, strength, preset, num_frames, seed, randomize],
+        outputs=[video_out, used_seed], fn=add_water, cache_examples=True, cache_mode="lazy",
+    )
+
+if __name__ == "__main__":
+    demo.launch(show_error=True)

examples/landscape_dry.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:52054b0a9af57517bbca8341a924a4cd941e9da07b2e4ee8287c808271a9d74d
+size 349543

examples/man_dancing_dry.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a52822c2ebe58ed8e882fe7a80c29f8a3759d61f65ddb8da35062dedcf0b9387
+size 292547

requirements.txt

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