Upload folder using huggingface_hub

.gitattributes

@@ -33,3 +33,6 @@ 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
+anime_1.jpg filter=lfs diff=lfs merge=lfs -text
+example_ref_2.jpg filter=lfs diff=lfs merge=lfs -text
+example_ref_3.jpg filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,13 +1,18 @@
 ---
-title: Charactersheet Lora Demo
-emoji: 🦀
-colorFrom: blue
-colorTo: yellow
+title: CharacterSheet LoRA Demo
+emoji: 🧑‍🎨
+colorFrom: indigo
+colorTo: pink
 sdk: gradio
 sdk_version: 6.22.0
-python_version: '3.12'
 app_file: app.py
-pinned: false
+short_description: Multi-view character sheet from one image (FLUX.2 LoRA)
+python_version: "3.12"
+startup_duration_timeout: 1h
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# CharacterSheet LoRA Demo
+
+This Space demonstrates the [CharacterSheet](https://huggingface.co/Alissonerdx/CharacterSheet) QuadView LoRA applied on top of [FLUX.2 Klein 9B](https://huggingface.co/black-forest-labs/FLUX.2-klein-9B).
+
+Upload a clear, well-framed image of a character and the model produces a multi-view character sheet: a face close-up plus front, side, and back full-body views on a single 1536×1024 sheet.

app.py

@@ -0,0 +1,177 @@
+import os
+
+os.environ.setdefault("PYTORCH_CUDA_ALLOC_CONF", "expandable_segments:True")
+
+import spaces  # MUST come before torch / diffusers / transformers
+import torch
+import gradio as gr
+import numpy as np
+import random
+from PIL import Image
+from diffusers import Flux2KleinPipeline
+
+# ---------------------------------------------------------------------------
+# Model setup
+# ---------------------------------------------------------------------------
+MODEL_ID = "black-forest-labs/FLUX.2-klein-9B"  # distilled, 4-step base
+LORA_REPO = "Alissonerdx/CharacterSheet"
+LORA_WEIGHT = "QuadView_klein9b_v1.safetensors"  # FLUX.2 Klein 9B QuadView LoRA
+
+TRIGGER_PROMPT = (
+    "Convert the character in the image to a Character Sheet showing a face "
+    "close-up, front, side and back full body views"
+)
+
+dtype = torch.bfloat16
+device = "cuda"
+
+print("Loading FLUX.2 Klein 9B pipeline...")
+pipe = Flux2KleinPipeline.from_pretrained(MODEL_ID, torch_dtype=dtype).to("cuda")
+print("Loading CharacterSheet QuadView LoRA...")
+pipe.load_lora_weights(LORA_REPO, weight_name=LORA_WEIGHT)
+print("LoRA loaded. Ready.")
+
+MAX_SEED = np.iinfo(np.int32).max
+
+
+@spaces.GPU(duration=120)
+def generate(
+    reference_image,
+    prompt=TRIGGER_PROMPT,
+    num_inference_steps=8,
+    guidance_scale=1.0,
+    lora_strength=1.0,
+    seed=42,
+    randomize_seed=True,
+    width=1536,
+    height=1024,
+    progress=gr.Progress(track_tqdm=True),
+):
+    """Generate a multi-view character sheet from a single reference image.
+
+    Uses the CharacterSheet QuadView LoRA on FLUX.2 Klein 9B to turn one
+    character photo into a face close-up plus front, side, and back full-body
+    views arranged on a single sheet.
+
+    Args:
+        reference_image: A clear, well-framed image of the character.
+        prompt: Instruction caption; defaults to the QuadView trigger.
+        num_inference_steps: Sampling steps (8 is the recommended starting point).
+        guidance_scale: CFG scale (1.0 for distilled Klein 9B).
+        lora_strength: LoRA scale (1.0 = full strength).
+        seed: RNG seed for reproducibility.
+        randomize_seed: Use a random seed instead of the provided one.
+        width: Output width in pixels.
+        height: Output height in pixels.
+    """
+    if reference_image is None:
+        raise gr.Error("Please upload a reference character image.")
+
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    seed = int(seed)
+
+    # Apply / adjust LoRA strength
+    pipe.set_adapters(["default"], adapter_weights=[float(lora_strength)])
+
+    generator = torch.Generator(device=device).manual_seed(seed)
+
+    img = pipe(
+        image=reference_image,
+        prompt=prompt,
+        width=int(width),
+        height=int(height),
+        num_inference_steps=int(num_inference_steps),
+        guidance_scale=float(guidance_scale),
+        generator=generator,
+    ).images[0]
+
+    return img, seed
+
+
+# ---------------------------------------------------------------------------
+# UI
+# ---------------------------------------------------------------------------
+CSS = """
+#col-container { max-width: 1100px; margin: 0 auto; }
+.dark .gradio-container { color: var(--body-text-color); }
+"""
+
+with gr.Blocks(theme=gr.themes.Citrus(), css=CSS) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown(
+            """# CharacterSheet LoRA — QuadView on FLUX.2 Klein 9B
+Turn a single character photo into a multi-view reference sheet (face close-up + front, side, and back full-body views) using the [CharacterSheet LoRA](https://huggingface.co/Alissonerdx/CharacterSheet) on [FLUX.2 Klein 9B](https://huggingface.co/black-forest-labs/FLUX.2-klein-9B)."""
+        )
+
+        with gr.Row():
+            with gr.Column():
+                reference_image = gr.Image(
+                    label="Reference character image",
+                    type="pil",
+                    sources=["upload", "clipboard"],
+                )
+                run_button = gr.Button("Generate character sheet", variant="primary")
+
+                with gr.Accordion("Advanced settings", open=False):
+                    prompt = gr.Textbox(
+                        label="Instruction prompt",
+                        value=TRIGGER_PROMPT,
+                        lines=3,
+                        info="The trigger caption for the QuadView LoRA. Edit only if you know what you're doing.",
+                    )
+                    with gr.Row():
+                        num_inference_steps = gr.Slider(
+                            label="Steps", minimum=1, maximum=20, step=1, value=8,
+                            info="8 is the recommended starting point for Klein 9B QuadView.",
+                        )
+                        guidance_scale = gr.Slider(
+                            label="CFG scale", minimum=0.0, maximum=10.0, step=0.1, value=1.0,
+                        )
+                    lora_strength = gr.Slider(
+                        label="LoRA strength", minimum=0.0, maximum=2.0, step=0.05, value=1.0,
+                    )
+                    with gr.Row():
+                        seed = gr.Slider(
+                            label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=42,
+                        )
+                        randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+                    with gr.Row():
+                        width = gr.Slider(
+                            label="Width", minimum=512, maximum=2048, step=16, value=1536,
+                        )
+                        height = gr.Slider(
+                            label="Height", minimum=512, maximum=2048, step=16, value=1024,
+                        )
+
+            with gr.Column():
+                result = gr.Image(label="Character sheet", show_label=True)
+
+        gr.Examples(
+            examples=[
+                ["example_ref.jpg", TRIGGER_PROMPT, 8, 1.0, 1.0, 42, True, 1536, 1024],
+                ["example_ref_2.jpg", TRIGGER_PROMPT, 8, 1.0, 1.0, 42, True, 1536, 1024],
+                ["example_ref_3.jpg", TRIGGER_PROMPT, 8, 1.0, 1.0, 42, True, 1536, 1024],
+            ],
+            inputs=[
+                reference_image, prompt, num_inference_steps, guidance_scale,
+                lora_strength, seed, randomize_seed, width, height,
+            ],
+            outputs=[result, seed],
+            fn=generate,
+            cache_examples=True,
+            cache_mode="lazy",
+        )
+
+    gr.on(
+        triggers=[run_button.click],
+        fn=generate,
+        inputs=[
+            reference_image, prompt, num_inference_steps, guidance_scale,
+            lora_strength, seed, randomize_seed, width, height,
+        ],
+        outputs=[result, seed],
+        api_name="generate",
+    )
+
+demo.launch(mcp_server=True)

requirements.txt

@@ -0,0 +1,5 @@
+git+https://github.com/huggingface/diffusers.git
+transformers
+accelerate
+safetensors
+sentencepiece