[FEATURE] Optimization of Image Embedding & Clustering Inference

### Describe the feature

While exploring the codebase, I noticed that the current face clustering and image embedding generation could be optimized for multi-core systems.

I recently completed a research internship at IIT Palakkad specifically focusing on matrix multiplication optimization in multi-core systems. I'd like to propose a project for GSoC 2026 to implement high-performance inference pipelines for PictoPy, ensuring it handles large libraries smoothly on modern hardware (like Apple Silicon/M-series chips).

I am already familiar with the Python ML stack and would love to discuss how I can integrate these optimizations into the core logic.

### Add ScreenShots

Validated the PictoPy backend on macOS 15 (M5 ARM64). Successfully resolved dependency conflicts and confirmed native execution via the Apple Silicon process 'Python' (PID 2822). The server is active and listening on port 52123.

### Record

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