#!/opt/homebrew/bin/python3.11
"""
Find BLUE stamps (Inverted Jenny) or Envelopes
Filter: Blue Color + Small/Medium Size
"""

import cv2
import numpy as np
import os

UUID = "384b0ff44aaaa1f1"
BASE_DIR = f"output/{UUID}/florence2_results"

# Keyframes to check
FRAMES = [
    "scan_6751.jpg",  # 112:31
    "scan_6755.jpg",  # 112:35
    "scan_6756.jpg",  # 112:36 (Dialogue: "Give me the stamp")
    "scan_6759.jpg",  # 112:39
]

print("🔍 Analyzing Keyframes for BLUE Stamps...")

for frame_name in FRAMES:
    img_path = os.path.join(BASE_DIR, frame_name)
    if not os.path.exists(img_path):
        continue

    img = cv2.imread(img_path)
    h, w, _ = img.shape

    # Convert to HSV
    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

    # Blue Mask (Hue ~100-130)
    # Adjusting for various shades of blue
    mask1 = cv2.inRange(hsv, np.array([90, 50, 50]), np.array([130, 255, 255]))

    # Optional: Also look for White/Paper (Envelope)
    # mask2 = cv2.inRange(hsv, np.array([0, 0, 200]), np.array([180, 30, 255]))
    # mask = mask1 + mask2
    mask = mask1

    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    print(f"\n🎞️ Scanning {frame_name} for Blue objects...")

    found_count = 0
    for cnt in contours:
        area = cv2.contourArea(cnt)

        # FILTER 1: Area Size
        # We want something stamp-sized or envelope-sized
        # Stamp: ~100 - 5000 px
        # Envelope: ~1000 - 20000 px
        if area < 100 or area > 20000:
            continue

        # FILTER 2: Aspect Ratio (Rectangular)
        x, y, w_box, h_box = cv2.boundingRect(cnt)
        aspect_ratio = float(w_box) / h_box

        # Check if it looks like a rectangle (0.5 to 2.0 ratio roughly)
        # But stamps can be small. Let's just check area mostly.

        # Filter out very long thin lines (likely text)
        if w_box < 5 or h_box < 5:
            continue

        # Filter out very large backgrounds
        if w_box > 300 and h_box > 300:
            continue

        print(
            f"   ✅ Found Blue Candidate: Area={int(area)}, Size={w_box}x{h_box}, Pos=({x},{y})"
        )

        # Draw
        cv2.rectangle(img, (x, y), (x + w_box, y + h_box), (0, 255, 0), 2)
        cv2.putText(
            img,
            f"BLUE? ({int(area)})",
            (x, y - 10),
            cv2.FONT_HERSHEY_SIMPLEX,
            0.5,
            (0, 255, 0),
            1,
        )

        # Crop
        crop = img[y : y + h_box, x : x + w_box]
        crop_path = os.path.join(BASE_DIR, f"crop_blue_{frame_name}_{x}_{y}.jpg")
        cv2.imwrite(crop_path, crop)

        found_count += 1

    if found_count > 0:
        res_path = os.path.join(BASE_DIR, f"result_blue_{frame_name}")
        cv2.imwrite(res_path, img)
    else:
        print("   ❌ No blue candidates found.")