8f05a7c188
- Update ASR, face, OCR, pose processors - Add release pre-flight check script - Add synonym generation, chunk processing scripts - Add face recognition, stamp search utilities
84 lines
2.4 KiB
Python
84 lines
2.4 KiB
Python
#!/opt/homebrew/bin/python3.11
|
|
"""
|
|
Find SMALL red triangles (Stamps) using OpenCV
|
|
Filter: Triangle Shape + Small Area (Physical Constraint)
|
|
"""
|
|
|
|
import cv2
|
|
import numpy as np
|
|
import os
|
|
|
|
UUID = "384b0ff44aaaa1f1"
|
|
BASE_DIR = f"output/{UUID}/florence2_results"
|
|
# Check the original frame
|
|
IMG_NAME = "frame_6756.jpg"
|
|
IMG_PATH = os.path.join(BASE_DIR, IMG_NAME)
|
|
OUT_PATH = os.path.join(BASE_DIR, "found_small_stamp_opencv.jpg")
|
|
|
|
print(f"🔍 Analyzing {IMG_NAME} for SMALL stamps...")
|
|
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
|
|
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
|
|
|
|
# 2. 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
|
|
|
|
# 3. Find Contours
|
|
contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
|
|
print(f"🔍 Found {len(contours)} red regions.")
|
|
|
|
found_stamps = []
|
|
# Screen area approx 2 million pixels. Stamp should be tiny (< 1% or < 15,000 pixels)
|
|
MAX_STAMP_AREA = 15000
|
|
|
|
for cnt in contours:
|
|
area = cv2.contourArea(cnt)
|
|
|
|
# Physical Constraint: Must be small
|
|
if area > MAX_STAMP_AREA:
|
|
continue
|
|
|
|
# Shape Constraint: Must be triangle-like (approx 3 vertices)
|
|
peri = cv2.arcLength(cnt, True)
|
|
approx = cv2.approxPolyDP(cnt, 0.04 * peri, True)
|
|
|
|
if len(approx) == 3:
|
|
x, y, w_box, h_box = cv2.boundingRect(approx)
|
|
found_stamps.append((x, y, w_box, h_box, approx, area))
|
|
print(f"✅ Potential Stamp: Area={area}, Box=({x},{y})")
|
|
|
|
# 4. Draw Results
|
|
result_img = img.copy()
|
|
for x, y, w_box, h_box, approx, area in found_stamps:
|
|
cv2.rectangle(result_img, (x, y), (x + w_box, y + h_box), (0, 255, 0), 2)
|
|
cv2.drawContours(result_img, [approx], 0, (255, 0, 0), 2)
|
|
cv2.putText(
|
|
result_img,
|
|
f"STAMP ({area})",
|
|
(x, y - 10),
|
|
cv2.FONT_HERSHEY_SIMPLEX,
|
|
0.5,
|
|
(0, 255, 0),
|
|
1,
|
|
)
|
|
|
|
if found_stamps:
|
|
cv2.imwrite(OUT_PATH, result_img)
|
|
print(f"🎨 Result saved to: {OUT_PATH}")
|
|
# Crop the first one
|
|
x, y, w_box, h_box, _, _ = found_stamps[0]
|
|
crop = img[y : y + h_box, x : x + w_box]
|
|
cv2.imwrite(os.path.join(BASE_DIR, "crop_small_stamp.jpg"), crop)
|
|
else:
|
|
print("❌ No small stamps found in this frame.")
|