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Dockerfile

@@ -1,6 +1,6 @@
 FROM nvidia/cuda:12.1.1-cudnn8-runtime-ubuntu22.04
 
-ENV DEBIAN_FRONTEND=noninteractive     PYTHONUNBUFFERED=1     PIP_NO_CACHE_DIR=1     HOME=/home/user     PATH=/home/user/.local/bin:$PATH
+ENV DEBIAN_FRONTEND=noninteractive     PYTHONUNBUFFERED=1     PIP_NO_CACHE_DIR=1     HOME=/home/user     PATH=/home/user/.local/bin:$PATH     FORCE_CPU=0
 
 RUN apt-get update && apt-get install -y     python3     python3-pip     ffmpeg     libgl1     libglib2.0-0     && rm -rf /var/lib/apt/lists/*
 

app.py

@@ -24,7 +24,6 @@ HF_TOKEN = os.environ.get("HF_TOKEN") or os.environ.get("HUGGINGFACEHUB_API_TOKE
 FACE_MODEL_NAME = os.environ.get("FACE_MODEL_NAME", "buffalo_l")
 DETECTION_SIZE = int(os.environ.get("DETECTION_SIZE", "640"))
 MAX_FRAMES = int(os.environ.get("MAX_FRAMES", "0"))
-FORCE_CPU = os.environ.get("FORCE_CPU") == "1"
 
 face_analyzer = None
 face_swapper = None
@@ -36,17 +35,21 @@ def ensure_ffmpeg():
         raise RuntimeError("ffmpeg is required but not available in PATH.")
 
 
-def get_execution_providers():
-    providers = []
-    if not FORCE_CPU:
-        providers.append("CUDAExecutionProvider")
-    providers.append("CPUExecutionProvider")
-    return providers
+def available_providers():
+    return ort.get_available_providers()
 
 
-def provider_status():
-    available = ort.get_available_providers()
-    return available, ("CUDAExecutionProvider" in available)
+def gpu_ready():
+    return "CUDAExecutionProvider" in available_providers()
+
+
+def gpu_guard():
+    providers = available_providers()
+    if "CUDAExecutionProvider" not in providers:
+        raise RuntimeError(
+            "GPU-only mode: CUDAExecutionProvider is missing. "
+            f"Available providers: {providers}"
+        )
 
 
 def ensure_swap_model() -> str:
@@ -57,25 +60,26 @@ def ensure_swap_model() -> str:
     if local_target.exists():
         model_path = str(local_target)
         return model_path
-    downloaded = hf_hub_download(
+    model_path = hf_hub_download(
         repo_id=MODEL_REPO_ID,
         filename=MODEL_FILENAME,
         revision=MODEL_REVISION,
         token=HF_TOKEN,
         local_dir=str(MODELS_DIR),
     )
-    model_path = downloaded
     return model_path
 
 
 def load_models():
     global face_analyzer, face_swapper
+    gpu_guard()
     if face_analyzer is not None and face_swapper is not None:
         return face_analyzer, face_swapper
     swap_model_path = ensure_swap_model()
-    face_analyzer = FaceAnalysis(name=FACE_MODEL_NAME, providers=get_execution_providers())
+    providers = ["CUDAExecutionProvider"]
+    face_analyzer = FaceAnalysis(name=FACE_MODEL_NAME, providers=providers)
     face_analyzer.prepare(ctx_id=0, det_size=(DETECTION_SIZE, DETECTION_SIZE))
-    face_swapper = get_model(swap_model_path, providers=get_execution_providers())
+    face_swapper = get_model(swap_model_path, providers=providers)
     return face_analyzer, face_swapper
 
 
@@ -107,15 +111,16 @@ def swap_frame(frame_bgr, source_face, analyzer, swapper):
     return result
 
 
-def process_video(face_image_path, video_path, progress=gr.Progress(track_tqdm=False)):
-    available_providers, cuda_available = provider_status()
-    if FORCE_CPU:
-        raise RuntimeError(f"FORCE_CPU=1 is set. Available providers: {available_providers}")
-    if not cuda_available:
-        raise RuntimeError(f"CUDAExecutionProvider is not available. Available providers: {available_providers}")
+def startup_status():
+    providers = available_providers()
+    return f"Available providers: {providers} | GPU ready: {gpu_ready()}"
+
 
+def process_video(face_image_path, video_path, progress=gr.Progress(track_tqdm=False)):
+    gpu_guard()
     ensure_ffmpeg()
     analyzer, swapper = load_models()
+
     src = cv2.imread(face_image_path)
     if src is None:
         raise ValueError("Could not read the source face image.")
@@ -153,18 +158,13 @@ def process_video(face_image_path, video_path, progress=gr.Progress(track_tqdm=F
     cap.release()
     writer.release()
     mux_audio(silent_video, audio_file, final_video)
-    return final_video, f"Done. Processed {idx} frame(s). Providers: {available_providers}"
-
-
-def startup_message():
-    available, cuda_ok = provider_status()
-    return f"ONNX Runtime providers: {available} | CUDA available: {cuda_ok}"
+    return final_video, f"Done. Processed {idx} frame(s)."
 
 
-with gr.Blocks(title="Video FaceSwap GPU") as demo:
-    gr.Markdown("""# Video FaceSwap GPU
-Upload a source face image and a target video. The app downloads the swap model from the Hugging Face Hub at runtime, then swaps the main source face onto detected faces in the video.""")
-    status_banner = gr.Textbox(label="Startup status", value=startup_message(), interactive=False)
+with gr.Blocks(title="Video FaceSwap GPU Only") as demo:
+    gr.Markdown("""# Video FaceSwap GPU Only
+This Space will only run when ONNX Runtime exposes CUDAExecutionProvider. If not, it refuses to process video.""")
+    gr.Textbox(label="GPU status", value=startup_status(), interactive=False)
     with gr.Row():
         face_image = gr.Image(type="filepath", label="Source face image")
         target_video = gr.Video(label="Target video")

readme.md

@@ -0,0 +1,31 @@
+---
+title: Video FaceSwap GPU Only
+emoji: 🎭
+colorFrom: blue
+colorTo: purple
+sdk: docker
+app_port: 7860
+suggested_hardware: a10g-small
+startup_duration_timeout: 1h
+---
+
+# Video FaceSwap GPU Only
+
+This Space is strict GPU-only. It refuses to process video unless ONNX Runtime exposes CUDAExecutionProvider.
+
+## Environment variables
+
+- `MODEL_REPO_ID`: default `ezioruan/inswapper_128.onnx`
+- `MODEL_FILENAME`: default `inswapper_128.onnx`
+- `MODEL_REVISION`: optional branch, tag, or commit hash
+- `HF_TOKEN`: recommended for gated/private repos and better Hub rate limits
+- `FACE_MODEL_NAME`: default `buffalo_l`
+- `DETECTION_SIZE`: default `640`
+- `MAX_FRAMES`: optional frame cap for testing, default `0`
+
+## Deploy
+
+1. Create a Docker Space.
+2. Select a paid GPU hardware tier such as A10G small.
+3. Add these files.
+4. Add `HF_TOKEN` if needed.