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/scan_keyframes_opencv.py

@@ -0,0 +1,96 @@
+#!/opt/homebrew/bin/python3.11
+"""
+Batch Scan Keyframes for SMALL red stamps
+"""
+
+import cv2
+import numpy as np
+import os
+import json
+
+UUID = "384b0ff44aaaa1f1"
+BASE_DIR = f"output/{UUID}/florence2_results"
+
+# The keyframes we extracted
+FRAMES = [
+    "scan_6751.jpg",  # 112:31
+    "scan_6755.jpg",  # 112:35
+    "scan_6759.jpg",  # 112:39
+]
+
+
+def find_small_stamps_in_frame(img_path):
+    if not os.path.exists(img_path):
+        return []
+
+    img = cv2.imread(img_path)
+    if img is None:
+        return []
+
+    h, w, _ = img.shape
+    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+
+    # Red Mask
+    mask1 = cv2.inRange(hsv, np.array([0, 70, 50]), np.array([10, 255, 255]))
+    mask2 = cv2.inRange(hsv, np.array([170, 70, 50]), np.array([180, 255, 255]))
+    mask = mask1 + mask2
+
+    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    found = []
+    # Constraint: Stamp must be small.
+    # If the image is 1080p, a stamp held in hand is likely < 200x200 pixels?
+    # Let's say Area < 30,000 pixels (approx 5% of width * 5% of height).
+    MAX_STAMP_AREA = 30000
+
+    for cnt in contours:
+        area = cv2.contourArea(cnt)
+
+        if area > MAX_STAMP_AREA:
+            continue
+
+        # Shape Constraint: Triangle or Rectangle
+        peri = cv2.arcLength(cnt, True)
+        approx = cv2.approxPolyDP(cnt, 0.04 * peri, True)
+        vertices = len(approx)
+
+        # Check for Triangle (3) or Rectangle (4)
+        if vertices in [3, 4]:
+            x, y, w_box, h_box = cv2.boundingRect(approx)
+
+            # Aspect ratio check? Stamps are usually rectangular or square.
+            # Triangles are rare for stamps unless folded.
+            # Let's just return everything small and triangular/rectangular for now.
+
+            found.append((x, y, w_box, h_box, area, approx))
+
+    return found, img
+
+
+print("🔍 Scanning Keyframes for Small Stamps...")
+
+for frame_name in FRAMES:
+    frame_path = os.path.join(BASE_DIR, frame_name)
+    result, img = find_small_stamps_in_frame(frame_path)
+
+    print(f"\n🎞️ Analyzing {frame_name}...")
+
+    if result:
+        print(f"   ✅ Found {len(result)} potential small stamps!")
+
+        # Draw them
+        for x, y, w_box, h_box, area, approx in result:
+            print(f"      📍 Box: ({x},{y}), Size: {w_box}x{h_box}, Area: {area}")
+            cv2.rectangle(img, (x, y), (x + w_box, y + h_box), (0, 255, 0), 2)
+
+            # Save crop
+            crop_name = f"crop_{frame_name}_{x}_{y}.jpg"
+            crop_path = os.path.join(BASE_DIR, crop_name)
+            crop = img[y : y + h_box, x : x + w_box]
+            cv2.imwrite(crop_path, crop)
+
+        # Save result image
+        res_name = f"result_opencv_{frame_name}"
+        cv2.imwrite(os.path.join(BASE_DIR, res_name), img)
+    else:
+        print(f"   ❌ No small stamps found.")