Initial commit

README.md

@@ -0,0 +1,47 @@
+---
+title: Character View Generator
+emoji: 🎭
+colorFrom: purple
+colorTo: blue
+sdk: gradio
+sdk_version: 4.44.0
+app_file: app.py
+pinned: false
+license: mit
+---
+
+# Character View Generator
+
+Generate consistent character views from a reference face image using IP-Adapter FaceID Plus.
+
+## API Usage
+
+```python
+from gradio_client import Client
+
+client = Client("ghost-logic/character-view-generator")
+
+result = client.predict(
+    face_image="path/to/face.png",
+    view_angle="3/4-right",
+    prompt="anime character, blue skin, orange eyes",
+    negative_prompt="realistic, photo",
+    strength=0.8,
+    guidance_scale=5.0,
+    num_steps=30,
+    seed=42,
+    api_name="/generate_view"
+)
+```
+
+## View Angles
+
+- `front` - Direct front view
+- `3/4-left` - Three-quarter view facing left
+- `3/4-right` - Three-quarter view facing right
+- `profile-left` - Full side profile facing left
+- `profile-right` - Full side profile facing right
+
+## For Daggr Integration
+
+This space is designed to be called from a daggr pipeline for character sheet generation.

app.py

@@ -0,0 +1,180 @@
+import gradio as gr
+import torch
+from PIL import Image
+from diffusers import StableDiffusionXLPipeline, ControlNetModel, AutoencoderKL
+from transformers import CLIPVisionModelWithProjection
+import spaces
+import os
+import numpy as np
+
+# Pre-defined head rotation angles (pitch, yaw in degrees)
+VIEW_ANGLES = {
+    "front": (0, 0),
+    "3/4-left": (0, -35),
+    "3/4-right": (0, 35),
+    "profile-left": (0, -90),
+    "profile-right": (0, 90),
+}
+
+# Global pipeline (loaded once)
+pipe = None
+ip_adapter = None
+
+def load_pipeline():
+    """Load the IP-Adapter FaceID Plus pipeline"""
+    global pipe
+
+    if pipe is not None:
+        return pipe
+
+    # Load IP-Adapter FaceID Plus with SDXL
+    from diffusers import StableDiffusionXLPipeline
+    from diffusers.utils import load_image
+
+    # Base model - using a good anime-capable SDXL model
+    model_id = "stabilityai/stable-diffusion-xl-base-1.0"
+
+    pipe = StableDiffusionXLPipeline.from_pretrained(
+        model_id,
+        torch_dtype=torch.float16,
+        variant="fp16",
+    )
+
+    # Load IP-Adapter FaceID Plus
+    pipe.load_ip_adapter(
+        "h94/IP-Adapter-FaceID",
+        subfolder=None,
+        weight_name="ip-adapter-faceid-plusv2_sdxl.bin",
+        image_encoder_folder="models/image_encoder",
+    )
+
+    pipe.set_ip_adapter_scale(0.7)
+    pipe.enable_model_cpu_offload()
+
+    return pipe
+
+
+@spaces.GPU
+def generate_view(
+    face_image: Image.Image,
+    view_angle: str,
+    prompt: str,
+    negative_prompt: str = "",
+    strength: float = 0.8,
+    guidance_scale: float = 5.0,
+    num_steps: int = 30,
+    seed: int = 42,
+) -> Image.Image:
+    """
+    Generate a character view from a reference face.
+
+    Args:
+        face_image: Reference face image (front view ideally)
+        view_angle: One of 'front', '3/4-left', '3/4-right', 'profile-left', 'profile-right'
+        prompt: Description of the character/style
+        negative_prompt: What to avoid
+        strength: IP-Adapter strength (0.0-1.0)
+        guidance_scale: CFG scale
+        num_steps: Number of inference steps
+        seed: Random seed for reproducibility
+
+    Returns:
+        Generated image at the specified angle
+    """
+
+    pipe = load_pipeline()
+
+    # Add view-specific prompt additions
+    angle_prompts = {
+        "front": "front view, facing camera, symmetrical",
+        "3/4-left": "3/4 view, turned slightly left, three quarter view",
+        "3/4-right": "3/4 view, turned slightly right, three quarter view",
+        "profile-left": "side profile, facing left, profile view",
+        "profile-right": "side profile, facing right, profile view",
+    }
+
+    view_prompt = angle_prompts.get(view_angle, "")
+    full_prompt = f"{prompt}, {view_prompt}, portrait, character art, consistent character"
+
+    default_negative = "deformed, ugly, bad anatomy, blurry, low quality, worst quality, text, watermark"
+    full_negative = f"{negative_prompt}, {default_negative}" if negative_prompt else default_negative
+
+    # Set seed for reproducibility
+    generator = torch.Generator(device="cpu").manual_seed(seed)
+
+    # Generate with IP-Adapter face reference
+    result = pipe(
+        prompt=full_prompt,
+        negative_prompt=full_negative,
+        ip_adapter_image=face_image,
+        num_inference_steps=num_steps,
+        guidance_scale=guidance_scale,
+        generator=generator,
+        width=1024,
+        height=1024,
+    )
+
+    return result.images[0]
+
+
+# Gradio Interface
+with gr.Blocks(title="Character View Generator") as demo:
+    gr.Markdown("""
+    # Character View Generator
+
+    Generate consistent character views from a reference face image.
+    Designed for character sheet pipelines.
+    """)
+
+    with gr.Row():
+        with gr.Column():
+            face_input = gr.Image(label="Reference Face", type="pil")
+            view_dropdown = gr.Dropdown(
+                choices=list(VIEW_ANGLES.keys()),
+                value="front",
+                label="Target View Angle"
+            )
+            prompt_input = gr.Textbox(
+                label="Prompt",
+                placeholder="anime character, blue skin, orange eyes...",
+                lines=2
+            )
+            negative_input = gr.Textbox(
+                label="Negative Prompt (optional)",
+                placeholder="realistic, photo...",
+                lines=2
+            )
+
+            with gr.Row():
+                strength_slider = gr.Slider(0.0, 1.0, value=0.8, label="Identity Strength")
+                guidance_slider = gr.Slider(1.0, 20.0, value=5.0, label="Guidance Scale")
+
+            with gr.Row():
+                steps_slider = gr.Slider(10, 50, value=30, step=1, label="Steps")
+                seed_input = gr.Number(value=42, label="Seed", precision=0)
+
+            generate_btn = gr.Button("Generate View", variant="primary")
+
+        with gr.Column():
+            output_image = gr.Image(label="Generated View")
+
+    generate_btn.click(
+        fn=generate_view,
+        inputs=[
+            face_input,
+            view_dropdown,
+            prompt_input,
+            negative_input,
+            strength_slider,
+            guidance_slider,
+            steps_slider,
+            seed_input,
+        ],
+        outputs=output_image,
+        api_name="generate_view"  # Enables API access
+    )
+
+
+if __name__ == "__main__":
+    demo.queue(api_open=True)
+    demo.launch()

requirements.txt

@@ -0,0 +1,11 @@
+torch
+diffusers>=0.25.0
+transformers
+accelerate
+safetensors
+gradio
+Pillow
+numpy
+spaces
+insightface
+onnxruntime-gpu