| """PCB Analyzer Orchestrator Entry Point for Collector Lite & Recycler Portal.""" |
| from __future__ import annotations |
|
|
| from typing import Any |
| from .model_client import BaseModelClient, MockModelClient, Detection |
| from .purity_assay import assay_pcb, assess_bis_discrepancy, AssayedBoard |
| from .vernacular_voice import generate_vernacular_voice_alert, VoiceAlert |
|
|
|
|
| class PCBAnalyzer: |
| """Single unified orchestrator for PCB micro-component purity assaying.""" |
|
|
| def __init__(self, model_client: BaseModelClient | None = None): |
| self.model_client = model_client or MockModelClient() |
|
|
| def analyze_board( |
| self, |
| front_image: Any, |
| back_image: Any | None = None, |
| base_price: float = 100.0, |
| form_factor: str = "desktop_atx", |
| lang: str = "hi", |
| ) -> dict[str, Any]: |
| """Perform 2-photo workflow PCB component purity assaying.""" |
|
|
| |
| detections_front = self.model_client.predict(front_image) |
|
|
| |
| detections_back = [] |
| if back_image is not None: |
| detections_back = self.model_client.predict(back_image) |
|
|
| all_detections = detections_front + detections_back |
|
|
| |
| assayed: AssayedBoard = assay_pcb( |
| detections=all_detections, |
| base_price=base_price, |
| form_factor=form_factor, |
| ) |
|
|
| |
| voice_alert: VoiceAlert = generate_vernacular_voice_alert( |
| bis_band=assayed.status_band, |
| adjusted_price=assayed.adjusted_price, |
| lang=lang, |
| ) |
|
|
| return { |
| "form_factor": assayed.form_factor, |
| "board_integrity_score": assayed.board_integrity_score, |
| "base_price": assayed.base_price, |
| "adjusted_price": assayed.adjusted_price, |
| "price_floor": assayed.price_floor, |
| "status_band": assayed.status_band, |
| "detected_counts": assayed.detected_counts, |
| "expected_counts": assayed.expected_counts, |
| "fraud_desoldered_pads": assayed.fraud_desoldered_pads, |
| "factory_unpopulated_pads": assayed.factory_unpopulated_pads, |
| "occluded_regions": assayed.occluded_regions, |
| "voice_alert": { |
| "lang": voice_alert.lang, |
| "transcript": voice_alert.transcript, |
| "audio_fallback_path": voice_alert.audio_fallback_path, |
| }, |
| } |
|
|
| def verify_intake_discrepancy( |
| self, |
| collector_bis: float, |
| recycler_front_image: Any, |
| recycler_back_image: Any | None = None, |
| form_factor: str = "desktop_atx", |
| ) -> dict[str, Any]: |
| """Verify intake lot discrepancy at Recycler Portal against collector BIS.""" |
| recycler_analysis = self.analyze_board( |
| front_image=recycler_front_image, |
| back_image=recycler_back_image, |
| form_factor=form_factor, |
| ) |
| recycler_bis = recycler_analysis["board_integrity_score"] |
| status = assess_bis_discrepancy(collector_bis, recycler_bis) |
|
|
| return { |
| "collector_bis": collector_bis, |
| "recycler_bis": recycler_bis, |
| "bis_delta": round(collector_bis - recycler_bis, 1), |
| "discrepancy_status": status, |
| "recycler_assay": recycler_analysis, |
| } |
|
|
