feat: update Python processors and add utility scripts

- Update ASR, face, OCR, pose processors
- Add release pre-flight check script
- Add synonym generation, chunk processing scripts
- Add face recognition, stamp search utilities

scripts/find_magnifying_glass.py

@@ -0,0 +1,86 @@
+#!/opt/homebrew/bin/python3.11
+"""
+Search for magnifying glass in key stamp scenes using OWL-ViT
+"""
+
+import os
+import cv2
+import json
+from PIL import Image
+import torch
+from transformers import OwlViTProcessor, OwlViTForObjectDetection
+
+BASE_DIR = "output/384b0ff44aaaa1f1/magnifying_glass"
+RESULTS_DIR = "output/384b0ff44aaaa1f1/magnifying_glass_results"
+os.makedirs(RESULTS_DIR, exist_ok=True)
+
+print("🔬 Loading OWL-ViT...")
+processor = OwlViTProcessor.from_pretrained("google/owlvit-base-patch32")
+model = OwlViTForObjectDetection.from_pretrained("google/owlvit-base-patch32")
+model.eval()
+
+SEARCH_TERMS = [
+    "magnifying glass",
+    "magnifier",
+    "loupe",
+    "lens",
+    "looking glass",
+    "glass",
+    "round glass",
+]
+
+import glob
+
+frames = sorted(glob.glob(os.path.join(BASE_DIR, "mag_*.jpg")))
+print(f"🔍 Searching {len(frames)} frames for magnifying glass...")
+
+found = False
+for frame_path in frames:
+    frame_name = os.path.basename(frame_path)
+    sec = frame_name.replace("mag_", "").replace("s.jpg", "")
+
+    image = Image.open(frame_path).convert("RGB")
+
+    for term in SEARCH_TERMS:
+        inputs = processor(text=[[term]], images=image, return_tensors="pt")
+
+        with torch.no_grad():
+            outputs = model(**inputs)
+
+        target_sizes = torch.Tensor([image.size[::-1]])
+        results = processor.post_process_object_detection(
+            outputs=outputs, target_sizes=target_sizes, threshold=0.05
+        )
+
+        for score, label, box in zip(
+            results[0]["scores"], results[0]["labels"], results[0]["boxes"]
+        ):
+            s = float(score)
+            if s > 0.05:
+                x1, y1, x2, y2 = map(int, box.tolist())
+                img = cv2.imread(frame_path)
+                crop = img[y1:y2, x1:x2]
+                if crop.size > 0:
+                    crop_name = f"mag_{sec}s_{term.replace(' ', '_')}_{s:.2f}.jpg"
+                    cv2.imwrite(os.path.join(RESULTS_DIR, crop_name), crop)
+
+                    cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 3)
+                    cv2.putText(
+                        img,
+                        f"{term} {s:.2f}",
+                        (x1, y1 - 10),
+                        cv2.FONT_HERSHEY_SIMPLEX,
+                        0.7,
+                        (0, 255, 0),
+                        2,
+                    )
+                    ann_name = f"annotated_mag_{sec}s.jpg"
+                    cv2.imwrite(os.path.join(RESULTS_DIR, ann_name), img)
+
+                print(f"  📍 {sec}s | {term} | {s:.2f}")
+                found = True
+
+if not found:
+    print("❌ No magnifying glass detected in these frames.")
+else:
+    print(f"\n✅ Found magnifying glass detections. Check {RESULTS_DIR}")