Use full gpu for now

app.py

@@ -4,8 +4,8 @@ from typing import Optional
 
 import gradio as gr
 import numpy as np
-import spaces
 import torch
+from gradio.themes import Soft
 from PIL import Image, ImageDraw
 
 # Prefer local transformers in the workspace
@@ -171,7 +171,6 @@ def _model_repo_from_key(key: str) -> str:
     return mapping.get(key, mapping["base_plus"])
 
 
-@spaces.GPU()
 def load_model_if_needed() -> tuple[Sam2VideoModel, Sam2VideoProcessor, str, torch.dtype]:
     desired_repo = _model_repo_from_key(GLOBAL_STATE.model_repo_key)
     if GLOBAL_STATE.model is not None and GLOBAL_STATE.processor is not None:
@@ -238,7 +237,6 @@ def ensure_session_for_current_model() -> None:
             GLOBAL_STATE.session_repo_id = desired_repo
 
 
-@spaces.GPU()
 def init_video_session(video: str | dict) -> tuple[AppState, int, int, Image.Image, str]:
     """Gradio handler: load video, init session, return state, slider bounds, and first frame."""
     # Reset ONLY video-related fields, keep model loaded
@@ -353,7 +351,6 @@ def _ensure_color_for_obj(obj_id: int):
         GLOBAL_STATE.color_by_obj[obj_id] = pastel_color_for_object(obj_id)
 
 
-@spaces.GPU()
 def on_image_click(
     img: Image.Image | np.ndarray,
     state: AppState,
@@ -485,7 +482,6 @@ def on_image_click(
     return update_frame_display(GLOBAL_STATE, int(frame_idx))
 
 
-@spaces.GPU()
 def propagate_masks(state: AppState, progress=gr.Progress()):
     if state is None or state.inference_session is None:
         yield "Load a video first."
@@ -567,7 +563,9 @@ def reset_session() -> tuple[AppState, Image.Image, int, int, str]:
     return GLOBAL_STATE, preview_img, slider_minmax, slider_value, status
 
 
-with gr.Blocks(title="SAM2 Video (Transformers) - Interactive Segmentation") as demo:
+theme = Soft(primary_hue="indigo", secondary_hue="rose", neutral_hue="slate")
+
+with gr.Blocks(title="SAM2 Video (Transformers) - Interactive Segmentation", theme=theme) as demo:
     state = gr.State(GLOBAL_STATE)
 
     gr.Markdown("""