"""
Unit and Integration Test Suite
Validates InventoryManager, ShelfProductDetector, ProductFeatureMatcher, and Pipeline.
"""

import os
import sys
import cv2

current_dir = os.path.dirname(os.path.abspath(__file__))
if current_dir not in sys.path:
    sys.path.insert(0, current_dir)

from inventory import InventoryManager
from feature_matcher import ProductFeatureMatcher
from detector import ShelfProductDetector
from pipeline import ShelfRecognitionPipeline


def test_inventory():
    print("[TEST] Testing InventoryManager...")
    inv = InventoryManager("stock")
    assert len(inv.products) >= 10, f"Expected products >= 10 in stock.csv, found {len(inv.products)}"
    p1 = inv.get_product("sku_001")
    assert p1 is not None, "sku_001 not found"
    assert p1["product_name"] == "明治 おいしい牛乳"
    assert p1["price"] == 258.0
    assert p1["number_on"] == 73
    print("  -> InventoryManager test: PASSED")


def test_feature_matcher():
    print("[TEST] Testing ProductFeatureMatcher...")
    matcher = ProductFeatureMatcher("stock")
    assert len(matcher.db.templates) >= 7, f"Expected templates >= 7, got {len(matcher.db.templates)}"

    for method in ["hybrid", "orb", "brisk"]:
        tmpl_img = matcher.db.templates["sku_001"]["image"]
        res = matcher.classify_crop(tmpl_img, method=method)
        assert res["status"] == "success", f"Method {method} failed"
        assert res["best_sku"] == "sku_001", f"Expected sku_001 with {method}, got {res['best_sku']}"
        print(f"  -> {method.upper()} classification test: PASSED (Score: {res['score']}, Conf: {res['confidence']})")


def test_detector():
    print("[TEST] Testing ShelfProductDetector...")
    detector = ShelfProductDetector("runs/detect/train/weights/best.pt")
    sample_shelf = "runs/detect/train/train_batch0.jpg"
    res = detector.detect(sample_shelf)
    assert res["status"] == "success", "Detection failed"
    assert res["total_detected"] > 0, "No boxes detected"
    print(f"  -> Detector test: PASSED ({res['total_detected']} items localized)")

    first_box = res["boxes"][0]
    cx, cy = first_box["center"]
    hit = detector.find_box_at_point(cx, cy, res["boxes"])
    assert hit is not None, "Hit test failed on center coordinate"
    assert hit["id"] == first_box["id"], "Hit test returned incorrect box"
    print("  -> Spatial hit-test: PASSED")


def test_pipeline():
    print("[TEST] Testing End-to-End Pipeline...")
    pipeline = ShelfRecognitionPipeline(
        weights_path="runs/detect/train/weights/best.pt",
        stock_dir="stock"
    )
    init_res = pipeline.set_active_shelf_image("runs/detect/train/train_batch0.jpg")
    assert init_res["status"] == "success"
    assert len(init_res["boxes"]) > 0

    first_box = init_res["boxes"][0]
    cx, cy = first_box["center"]
    click_res = pipeline.process_click(cx, cy, method="hybrid")
    assert click_res["status"] == "success", f"Click processing failed: {click_res.get('message')}"
    assert "inventory" in click_res
    assert click_res["inventory"] is not None
    print(f"  -> End-to-End Pipeline test: PASSED (Matched: {click_res['classification']['matched_sku']} - {click_res['inventory']['product_name']})")


if __name__ == "__main__":
    print("=" * 60)
    print("STARTING TEST SUITE")
    print("=" * 60)
    test_inventory()
    test_feature_matcher()
    test_detector()
    test_pipeline()
    print("=" * 60)
    print("ALL TESTS PASSED SUCCESSFULLY!")
    print("=" * 60)