feat: add ROCm (AMD GPU) and Intel GPU support (v0.2.12)

New image variants:
- :rocm  — InsightFace via ROCmExecutionProvider, SigLIP via PyTorch ROCm 6.3
- :intel — InsightFace via OpenVINOExecutionProvider (onnxruntime-openvino);
           Intel GPU compute runtime auto-installed from Intel graphics repo;
           OPENVINO_DEVICE=GPU opts into Arc/iGPU inference (default: CPU)

Also adds:
- pyproject-rocm.toml + uv-rocm.lock, pyproject-intel.toml + uv-intel.lock
- compose.yml device passthrough snippets for AMD and Intel
- CI: build-rocm and build-intel jobs in docker-publish.yml; all four
  variants built and tagged in release.yml
- README reworked: cleaner structure, GPU variant quick-start examples,
  OPENVINO_DEVICE env var documented
- CHANGELOG entry and version bump to 0.2.12

Fix: IntPrompt in dict literal was eagerly evaluated in the no-embedding
fallback path of _get_strategy_choice, prompting users for a custom count
regardless of which strategy they picked.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

winnow/image_processing.py

@@ -144,7 +144,14 @@ def process_object_mode(
     try:
         model = get_yolo_model()
         target_class = config.get("object_class", "dog")
-        device = "cpu" if os.getenv("FORCE_CPU", "").lower() in ("true", "1", "yes") else None
+        import torch
+
+        if os.getenv("FORCE_CPU", "").lower() in ("true", "1", "yes"):
+            device = "cpu"
+        elif hasattr(torch, "xpu") and torch.xpu.is_available():
+            device = "xpu"
+        else:
+            device = None  # YOLO auto-selects (CUDA/ROCm/CPU)
 
         results = model(img, verbose=False, device=device)