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README.md

@@ -1,13 +1,27 @@
 ---
-title: Smart Character Swap Flux2 Klein
-emoji: 📊
-colorFrom: pink
-colorTo: purple
+title: Smart Character Swap - FLUX.2 Klein
+emoji: 🎭
+colorFrom: purple
+colorTo: pink
 sdk: gradio
-sdk_version: 6.18.0
-python_version: '3.12'
+sdk_version: 6.11.0
 app_file: app.py
 pinned: false
+short_description: Occlusion-aware character & face swap with FLUX.2 [klein]
+models:
+  - black-forest-labs/FLUX.2-klein-9B
+  - nhathoangfoto/Flux.2-Klein-9B-SmartCharacterSwap
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🎭 Smart Character Swap · FLUX.2 [klein]
+
+Swap an **identity** into a **target scene** while preserving the scene's pose,
+lighting, color grading, and occlusions (hands, veils, foreground objects).
+
+Upload the identity source (the face/character to bring in) and the target scene,
+then hit **Swap**. The before/after slider shows the original scene against the result.
+
+- **LoRA:** [`nhathoangfoto/Flux.2-Klein-9B-SmartCharacterSwap`](https://huggingface.co/nhathoangfoto/Flux.2-Klein-9B-SmartCharacterSwap)
+- **Base model:** [`black-forest-labs/FLUX.2-klein-9B`](https://huggingface.co/black-forest-labs/FLUX.2-klein-9B)
+
+Trigger word `jhuangswap` is added automatically.

app.py

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+import os
+import random
+
+import gradio as gr
+import numpy as np
+import spaces
+import torch
+from diffusers import Flux2KleinPipeline
+from PIL import Image
+
+# ──────────────────────────────────────────────────────────────────────────────
+# Smart Character Swap — FLUX.2 [klein]
+#
+#   Identity source → the face / character to bring in
+#   Target scene    → the photo whose pose, lighting, occlusions and color grade
+#                     should be kept while the identity is swapped in
+#
+# Occlusion-aware, lighting-matched character / face swap, trained on FLUX.2 [klein].
+# ──────────────────────────────────────────────────────────────────────────────
+
+MAX_SEED = np.iinfo(np.int32).max
+dtype = torch.bfloat16
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+BASE_MODEL = "black-forest-labs/FLUX.2-klein-9B"
+LORA_REPO = "nhathoangfoto/Flux.2-Klein-9B-SmartCharacterSwap"
+LORA_WEIGHTS = "Klein2-9B-SmartCharacterSwap.safetensors"
+TRIGGER = "jhuangswap"
+
+DEFAULT_PROMPT = (
+    "jhuangswap, masterpiece, high-end photography, realistic portrait, "
+    "matching target lighting, highly detailed skin texture, 8k resolution"
+)
+
+print("Loading FLUX.2 [klein] 9B...")
+pipe = Flux2KleinPipeline.from_pretrained(BASE_MODEL, torch_dtype=dtype)
+pipe.to("cuda")
+pipe.load_lora_weights(LORA_REPO, weight_name=LORA_WEIGHTS, adapter_name="swap")
+print("Pipeline ready.")
+
+
+def _fit(img, target=1024, mult=16):
+    """Resize so the longest side ~= target, snapped to a multiple of `mult`."""
+    img = img.convert("RGB")
+    w, h = img.size
+    scale = target / max(w, h)
+    nw = max(mult, int(round(w * scale / mult)) * mult)
+    nh = max(mult, int(round(h * scale / mult)) * mult)
+    return img.resize((nw, nh), Image.LANCZOS)
+
+
+@spaces.GPU(duration=120)
+def swap(identity, scene, prompt, lora_scale, steps, guidance,
+         seed, randomize_seed, progress=gr.Progress(track_tqdm=True)):
+    if identity is None:
+        raise gr.Error("Please upload an identity source (the face/character to bring in).")
+    if scene is None:
+        raise gr.Error("Please upload a target scene (the photo to swap the identity into).")
+
+    pipe.set_adapters(["swap"], adapter_weights=[lora_scale])
+
+    scene_f = _fit(scene, target=1024)
+    identity_f = _fit(identity, target=1024)
+
+    full_prompt = prompt.strip() if prompt and prompt.strip() else DEFAULT_PROMPT
+    if TRIGGER not in full_prompt:
+        full_prompt = f"{TRIGGER}, {full_prompt}"
+
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    generator = torch.Generator(device=device).manual_seed(int(seed))
+
+    # Output keeps the target scene's composition; identity is the reference.
+    result = pipe(
+        image=[scene_f, identity_f],
+        prompt=full_prompt,
+        height=scene_f.height,
+        width=scene_f.width,
+        num_inference_steps=int(steps),
+        guidance_scale=guidance,
+        generator=generator,
+    ).images[0]
+
+    return (scene_f, result), seed
+
+
+css = """
+#col { max-width: 1200px; margin: 0 auto; }
+.header { text-align:center; padding: 8px 0 4px; }
+.header h1 { font-size: 1.7rem; margin: 0; font-weight: 700; }
+.header p  { color: var(--body-text-color-subdued); margin: 4px 0 0; font-size: 0.95rem; }
+.header a  { color: #6366f1; text-decoration: none; font-weight: 600; }
+"""
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_id="col"):
+        gr.HTML(
+            """
+            <div class="header">
+              <h1>🎭 Smart Character Swap · FLUX.2 [klein]</h1>
+              <p>Swap an <b>identity</b> into a <b>target scene</b> — occlusion-aware, with the scene's
+              own lighting and color grade preserved.
+              &nbsp;·&nbsp;
+              <a href="https://huggingface.co/nhathoangfoto/Flux.2-Klein-9B-SmartCharacterSwap" target="_blank">Model card</a></p>
+            </div>
+            """
+        )
+
+        with gr.Row(equal_height=False):
+            with gr.Column():
+                with gr.Row():
+                    identity = gr.Image(label="Identity source (face to bring in)", type="pil", height=300)
+                    scene = gr.Image(label="Target scene (pose / lighting to keep)", type="pil", height=300)
+
+                prompt = gr.Textbox(
+                    label="Prompt",
+                    value=DEFAULT_PROMPT,
+                    lines=2,
+                    info="Trigger 'jhuangswap' is added automatically if you remove it.",
+                )
+
+                with gr.Accordion("Advanced", open=False):
+                    lora_scale = gr.Slider(0.5, 1.2, value=0.9, step=0.05, label="LoRA strength")
+                    steps = gr.Slider(4, 30, value=8, step=1, label="Steps")
+                    guidance = gr.Slider(1.0, 10.0, value=4.0, step=0.1, label="Guidance scale")
+                    with gr.Row():
+                        seed = gr.Slider(0, MAX_SEED, value=0, step=1, label="Seed")
+                        randomize_seed = gr.Checkbox(value=True, label="Randomize")
+
+                run_btn = gr.Button("Swap", variant="primary", size="lg")
+
+            with gr.Column():
+                result = gr.ImageSlider(label="Target scene → Swapped result", type="pil", height=480)
+
+        gr.Examples(
+            examples=[
+                ["examples/identity_B.jpg", "examples/scene_B.jpg"],
+                ["examples/identity_A.jpg", "examples/scene_A.jpg"],
+            ],
+            inputs=[identity, scene],
+            outputs=[result, seed],
+            fn=lambda i, s: swap(i, s, DEFAULT_PROMPT, 0.9, 8, 4.0, 0, True),
+            cache_examples=True,
+            cache_mode="lazy",
+            label="Identity + scene examples",
+        )
+
+    swap_inputs = [identity, scene, prompt, lora_scale, steps, guidance, seed, randomize_seed]
+    run_btn.click(fn=swap, inputs=swap_inputs, outputs=[result, seed])
+    prompt.submit(fn=swap, inputs=swap_inputs, outputs=[result, seed])
+
+if __name__ == "__main__":
+    demo.launch(theme=gr.themes.Citrus(), show_error=True, ssr_mode=False)

requirements.txt

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+git+https://github.com/huggingface/diffusers.git
+transformers
+accelerate
+safetensors
+bitsandbytes
+torchao
+kernels
+peft