app.py

import gradio as gr
from PIL import Image
import numpy as np
import cv2
import os
import tempfile
import time
from gradio_client import Client, handle_file

# --- CONFIGURATION: FALLBACK LIST ---
# We try these 4 distinct spaces. If one is down, we jump to the next.
MODELS = [
    # 1. LGM (ashawkey/LGM) - Very fast, usually online.
    {"id": "ashawkey/LGM", "api": "/process", "type": "lgm"},
    
    # 2. InstantMesh (TencentARC) - High quality, try again.
    {"id": "TencentARC/InstantMesh", "api": "/generate", "type": "instantmesh"},

    # 3. Zero123++ (sudo-ai) - Good alternative architecture.
    {"id": "sudo-ai/zero123plus-v1.2", "api": "/generate", "type": "zero123"},
    
    # 4. Shap-E (OpenAI) - The reliable backup.
    {"id": "hysts/Shap-E", "api": "/image-to-3d", "type": "shape"}
]

def photo_to_sketch(image):
    """Instant local sketch"""
    if image is None: return None
    if isinstance(image, np.ndarray):
        image = Image.fromarray(image.astype('uint8'))
    
    # Resize to safe dimensions (512x512) to prevent downstream API crashes
    image = image.resize((512, 512))
    
    gray = image.convert("L")
    img_array = np.array(gray)
    blurred = cv2.GaussianBlur(img_array, (5, 5), 0)
    edges = cv2.Canny(blurred, 60, 150)
    sketch_np = 255 - edges
    return Image.fromarray(sketch_np).convert("RGB")

def generate_3d_avatar(sketch_image, height, weight, muscle, gender, breast):
    """Try multiple remote models until one succeeds"""
    print(f"-> Starting 3D Generation Process...")
    
    if sketch_image is None:
        raise gr.Error("Please upload an image first!")

    # --- CRITICAL FIX: Sanitize Image ---
    # Many 3D APIs crash if the image is not 256x256 or 512x512 RGB.
    if isinstance(sketch_image, np.ndarray):
        sketch_image = Image.fromarray(sketch_image.astype('uint8'))
    
    sketch_image = sketch_image.convert("RGB").resize((512, 512))
    
    temp_dir = tempfile.gettempdir()
    sketch_path = os.path.join(temp_dir, f"sketch_{int(time.time())}.png")
    sketch_image.save(sketch_path)
    print(f"-> Saved clean input to {sketch_path}")

    last_error = ""

    # --- RETRY LOOP ---
    for model in MODELS:
        try:
            model_id = model["id"]
            print(f"------------------------------------------")
            print(f"-> Attempting Connection to: {model_id}...")
            
            client = Client(model_id)
            
            if model["type"] == "lgm":
                # LGM Parameters: [Image, Scale, Steps, Seed]
                print("-> Sending request (LGM format)...")
                result = client.predict(
                    handle_file(sketch_path), 
                    api_name=model["api"]
                )

            elif model["type"] == "instantmesh":
                print("-> Sending request (InstantMesh format)...")
                result = client.predict(
                    handle_file(sketch_path), # Image
                    True,                     # Remove Background
                    30,                       # Steps
                    42,                       # Seed
                    api_name=model["api"]
                )
                
            elif model["type"] == "zero123":
                print("-> Sending request (Zero123 format)...")
                result = client.predict(
                    handle_file(sketch_path), # Image
                    True,                     # Remove Background
                    api_name=model["api"]
                )
                
            elif model["type"] == "shape":
                print("-> Sending request (Shap-E format)...")
                # Shap-E is strictly: Image, Prompt, Seed, Guidance, Steps
                result = client.predict(
                    handle_file(sketch_path), 
                    "",  # Prompt must be string (empty is fine)
                    0,   # Seed
                    15,  # Guidance
                    64,  # Steps
                    api_name=model["api"]
                )

            # If we get here, it worked!
            print(f"-> SUCCESS! Model generated by {model_id}")
            
            # Handle return types (list of files vs single path)
            if isinstance(result, (list, tuple)):
                # Find the first .glb or .obj
                final_model = next((item for item in result if isinstance(item, str) and item.endswith(('.glb', '.obj', '.gltf', '.ply'))), result[0])
            else:
                final_model = result
                
            return final_model, final_model

        except Exception as e:
            print(f"-> FAILED: {model_id} | Error: {e}")
            last_error = str(e)
            continue # Try next model

    # If all fail
    raise gr.Error(f"CRITICAL OUTAGE: All 4 backup models failed. The Hugging Face inference cloud is severely degraded right now. Last Error: {last_error}")

# =============== UI ===============
with gr.Blocks(title="SketchToLife") as demo:
    gr.Markdown("# SketchToLife – Emergency Backup Mode")
    gr.Markdown("**Status:** Trying LGM → InstantMesh → Zero123 → Shap-E")

    with gr.Row():
        with gr.Column():
            inp = gr.Image(label="Upload Photo", type="pil", height=420)
            btn1 = gr.Button("Generate Clean Sketch", variant="secondary", size="lg")
            out_sketch = gr.Image(label="Your Sketch", height=420, type="pil")

        with gr.Column():
            gr.Markdown("### Customize Body")
            h = gr.Dropdown(["short", "average", "tall", "giant"], value="average", label="Height")
            w = gr.Dropdown(["slim", "average", "curvy", "heavy"], value="average", label="Weight")
            m = gr.Dropdown(["slim", "fit", "muscular", "bodybuilder"], value="fit", label="Muscle")
            g = gr.Radio(["male", "female", "neutral"], value="neutral", label="Gender")
            b = gr.Dropdown(["small", "medium", "large"], value="medium", label="Breast/Form")
            
            btn2 = gr.Button("Generate 3D Model", variant="primary", size="lg")

    with gr.Row():
        view3d = gr.Model3D(label="3D Result", height=520, interactive=True)
        download = gr.File(label="Download .GLB")

    btn1.click(photo_to_sketch, inputs=inp, outputs=out_sketch)
    btn2.click(generate_3d_avatar, inputs=[out_sketch, h, w, m, g, b], outputs=[view3d, download])

if __name__ == "__main__":
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        ssr_mode=False
    )