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import uuid
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
import gradio as gr
import torch
from diffusers import ShapEPipeline
from PIL import Image
MODEL_ID = "openai/shap-e"
pipe = None
DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
DTYPE = torch.float16 if DEVICE == "cuda" else torch.float32
ROOT_DIR = Path(__file__).resolve().parent
DATA_DIR = ROOT_DIR / "data"
ASSETS_DIR = DATA_DIR / "assets"
ASSETS_DIR.mkdir(parents=True, exist_ok=True)
EXAMPLES = [
"A cute stylized robot with a round head",
"A fantasy treasure chest with gold trim",
"A small dragon figurine, toy-like, colorful",
"A low-poly medieval house",
"A ceramic teapot shaped like an owl",
"A cartoon submarine with tiny windows",
]
def get_pipeline():
global pipe
if pipe is None:
kwargs = {"torch_dtype": DTYPE}
if DEVICE == "cuda":
kwargs["variant"] = "fp16"
pipe = ShapEPipeline.from_pretrained(MODEL_ID, **kwargs)
pipe = pipe.to(DEVICE)
return pipe
def make_white_background_transparent(frame: Image.Image, threshold: int = 245) -> Image.Image:
"""
Делает почти-белый фон прозрачным.
Если R, G и B все >= threshold, пиксель считаем фоном.
"""
img = frame.convert("RGBA")
data = img.getdata()
new_data = []
for r, g, b, a in data:
if r >= threshold and g >= threshold and b >= threshold:
new_data.append((255, 255, 255, 0))
else:
new_data.append((r, g, b, a))
img.putdata(new_data)
return img
def crop_to_nontransparent_content(img: Image.Image, padding: int = 8) -> Image.Image:
"""
Обрезает лишние прозрачные поля вокруг объекта.
"""
alpha = img.getchannel("A")
bbox = alpha.getbbox()
if bbox is None:
return img
left, top, right, bottom = bbox
left = max(0, left - padding)
top = max(0, top - padding)
right = min(img.width, right + padding)
bottom = min(img.height, bottom + padding)
return img.crop((left, top, right, bottom))
def save_frames_to_files(frames, prompt: str) -> List[str]:
asset_id = f"asset_{uuid.uuid4().hex[:8]}"
asset_dir = ASSETS_DIR / asset_id
asset_dir.mkdir(parents=True, exist_ok=True)
frame_paths = []
for i, frame in enumerate(frames):
img = frame.convert("RGBA")
img = make_white_background_transparent(img, threshold=245)
img = crop_to_nontransparent_content(img, padding=8)
frame_path = asset_dir / f"view_{i:03d}.png"
img.save(frame_path)
frame_paths.append(str(frame_path))
return frame_paths
def make_asset(prompt: str, frame_paths: List[str]) -> Dict[str, Any]:
return {
"prompt": prompt,
"frame_paths": frame_paths,
"selected_index": 0,
}
def gallery_items_from_assets(saved_assets: List[Dict[str, Any]]) -> List[Tuple[str, str]]:
items = []
for i, asset in enumerate(saved_assets):
frame_paths = asset.get("frame_paths", [])
if not frame_paths:
continue
idx = int(asset.get("selected_index", 0))
idx = max(0, min(idx, len(frame_paths) - 1))
caption = f"{i + 1}. {asset.get('prompt', '')}"
items.append((frame_paths[idx], caption))
return items
def current_view_from_selected(
saved_assets: List[Dict[str, Any]],
selected_asset_index: Optional[int],
):
if selected_asset_index is None:
return None, "No asset selected.", gr.update(interactive=False), gr.update(interactive=False)
if selected_asset_index < 0 or selected_asset_index >= len(saved_assets):
return None, "No asset selected.", gr.update(interactive=False), gr.update(interactive=False)
asset = saved_assets[selected_asset_index]
frame_paths = asset.get("frame_paths", [])
if not frame_paths:
return None, "No asset selected.", gr.update(interactive=False), gr.update(interactive=False)
idx = int(asset.get("selected_index", 0))
idx = max(0, min(idx, len(frame_paths) - 1))
label = f"Asset {selected_asset_index + 1} · View {idx + 1} / {len(frame_paths)}"
return frame_paths[idx], label, gr.update(interactive=True), gr.update(interactive=True)
def selected_view_path(
saved_assets: List[Dict[str, Any]],
selected_asset_index: Optional[int],
):
if selected_asset_index is None:
return None
if selected_asset_index < 0 or selected_asset_index >= len(saved_assets):
return None
asset = saved_assets[selected_asset_index]
frame_paths = asset.get("frame_paths", [])
if not frame_paths:
return None
idx = int(asset.get("selected_index", 0))
idx = max(0, min(idx, len(frame_paths) - 1))
return frame_paths[idx]
def generate_and_add_asset(
prompt: str,
steps: int,
guidance_scale: float,
frame_size: int,
seed: int,
saved_assets: List[Dict[str, Any]],
):
prompt = (prompt or "").strip()
if not prompt:
raise gr.Error("Prompt is empty.")
saved_assets = saved_assets or []
pipeline = get_pipeline()
generator = torch.Generator(device=DEVICE).manual_seed(int(seed))
result = pipeline(
prompt,
guidance_scale=float(guidance_scale),
num_inference_steps=int(steps),
frame_size=int(frame_size),
generator=generator,
)
frames = result.images[0]
frame_paths = save_frames_to_files(frames, prompt)
new_asset = make_asset(prompt, frame_paths)
saved_assets = saved_assets + [new_asset]
selected_asset_index = len(saved_assets) - 1
gallery_items = gallery_items_from_assets(saved_assets)
current_view, view_text, prev_btn, next_btn = current_view_from_selected(
saved_assets, selected_asset_index
)
gc.collect()
if DEVICE == "cuda":
torch.cuda.empty_cache()
return saved_assets, selected_asset_index, gallery_items, current_view, view_text, prev_btn, next_btn
def select_asset(
saved_assets: List[Dict[str, Any]],
evt: gr.SelectData,
):
if not saved_assets:
return None, [], None, "No asset selected.", gr.update(interactive=False), gr.update(interactive=False)
if evt is None or evt.index is None:
return None, gallery_items_from_assets(saved_assets), None, "No asset selected.", gr.update(interactive=False), gr.update(interactive=False)
idx = evt.index
if isinstance(idx, (list, tuple)):
idx = idx[0]
idx = int(idx)
current_view, view_text, prev_btn, next_btn = current_view_from_selected(saved_assets, idx)
gallery_items = gallery_items_from_assets(saved_assets)
return idx, gallery_items, current_view, view_text, prev_btn, next_btn
def prev_view(
saved_assets: List[Dict[str, Any]],
selected_asset_index: Optional[int],
):
if selected_asset_index is None:
raise gr.Error("Select an asset in the gallery first.")
if selected_asset_index < 0 or selected_asset_index >= len(saved_assets):
raise gr.Error("Select an asset in the gallery first.")
asset = saved_assets[selected_asset_index]
frame_paths = asset.get("frame_paths", [])
if not frame_paths:
raise gr.Error("Selected asset has no frames.")
idx = int(asset.get("selected_index", 0))
idx = (idx - 1) % len(frame_paths)
asset["selected_index"] = idx
gallery_items = gallery_items_from_assets(saved_assets)
current_view, view_text, prev_btn, next_btn = current_view_from_selected(
saved_assets, selected_asset_index
)
return saved_assets, gallery_items, current_view, view_text, prev_btn, next_btn
def next_view(
saved_assets: List[Dict[str, Any]],
selected_asset_index: Optional[int],
):
if selected_asset_index is None:
raise gr.Error("Select an asset in the gallery first.")
if selected_asset_index < 0 or selected_asset_index >= len(saved_assets):
raise gr.Error("Select an asset in the gallery first.")
asset = saved_assets[selected_asset_index]
frame_paths = asset.get("frame_paths", [])
if not frame_paths:
raise gr.Error("Selected asset has no frames.")
idx = int(asset.get("selected_index", 0))
idx = (idx + 1) % len(frame_paths)
asset["selected_index"] = idx
gallery_items = gallery_items_from_assets(saved_assets)
current_view, view_text, prev_btn, next_btn = current_view_from_selected(
saved_assets, selected_asset_index
)
return saved_assets, gallery_items, current_view, view_text, prev_btn, next_btn
def clear_saved_assets():
return [], None, [], None, "No asset selected.", gr.update(interactive=False), gr.update(interactive=False)
def set_prompt(value: str):
return value |