Initial commit for push folder

recognization/code/test_suite.py

@@ -0,0 +1,91 @@
+"""
+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)