Adds hardware detection that queries TensorFlow to determine exactly
which device will be used for training:
- New Python script detect_hardware.py queries TensorFlow for available
devices (GPU/Metal/CPU)
- New API endpoint GET /api/vision-training/hardware runs the script
and caches results for 1 hour
- Training page shows hardware prominently before the "Start Training"
button with GPU/CPU badge, TensorFlow version, and system memory
On Apple Silicon Macs, shows chip type (e.g., "Apple M3 Pro GPU (Metal)")
On NVIDIA systems, shows GPU name from CUDA
Falls back to CPU with processor info if no GPU available
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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