Files
momentry_core/scripts/find_stamp_opencv.py
Warren 8f05a7c188 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
2026-04-30 15:07:49 +08:00

87 lines
2.6 KiB
Python

#!/opt/homebrew/bin/python3.11
"""
Find the Red Inverted Triangle Stamp using OpenCV Color & Shape Detection
"""
import cv2
import numpy as np
import os
UUID = "384b0ff44aaaa1f1"
BASE_DIR = f"output/{UUID}/florence2_results"
IMG_NAME = "frame_6756.jpg" # Frame at 112:36
IMG_PATH = os.path.join(BASE_DIR, IMG_NAME)
OUT_PATH = os.path.join(BASE_DIR, "found_stamp_opencv.jpg")
print(f"📷 Loading image: {IMG_PATH}")
if not os.path.exists(IMG_PATH):
print("❌ Image not found.")
exit()
img = cv2.imread(IMG_PATH)
h, w, _ = img.shape
print(f"📐 Image Size: {w}x{h}")
# 1. Convert to HSV Color Space
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# 2. Define Red Color Range in HSV
# Red wraps around 180, so we need two ranges
# Lower Red: Hue 0-10
lower_red1 = np.array([0, 70, 50])
upper_red1 = np.array([10, 255, 255])
mask1 = cv2.inRange(hsv, lower_red1, upper_red1)
# Upper Red: Hue 170-180
lower_red2 = np.array([170, 70, 50])
upper_red2 = np.array([180, 255, 255])
mask2 = cv2.inRange(hsv, lower_red2, upper_red2)
# Combine Masks
mask = mask1 + mask2
# 3. Find Contours in the Mask
contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
print(f"🔍 Found {len(contours)} red regions.")
# 4. Filter for Triangles (Stamp Shape)
found_stamps = []
for i, cnt in enumerate(contours):
# Calculate perimeter for approximation accuracy
peri = cv2.arcLength(cnt, True)
approx = cv2.approxPolyDP(cnt, 0.04 * peri, True)
# Check for triangle (3 vertices)
if len(approx) == 3:
area = cv2.contourArea(approx)
# Filter by size (ignore noise, ignore huge red walls)
# A stamp would likely be between 500 and 20000 pixels depending on zoom
if 200 < area < 50000:
# Get bounding box
x, y, w_box, h_box = cv2.boundingRect(approx)
found_stamps.append((x, y, w_box, h_box, approx))
print(
f"✅ Potential Stamp #{len(found_stamps)}: Area={area}, Box=({x},{y})"
)
# 5. Draw Results
result_img = img.copy()
for x, y, w_box, h_box, approx in found_stamps:
# Draw Box
cv2.rectangle(result_img, (x, y), (x + w_box, y + h_box), (0, 255, 0), 3)
# Draw Contour
cv2.drawContours(result_img, [approx], 0, (255, 0, 0), 2)
# Label
cv2.putText(
result_img, "STAMP?", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2
)
if found_stamps:
cv2.imwrite(OUT_PATH, result_img)
print(f"🎨 Result saved to: {OUT_PATH}")
else:
print(
"❌ No red triangles found. The stamp might not be visible or red in this frame."
)