import cv2
import numpy as np
import glob

def get_number_sprite(m_img):
    gray = np.max(m_img, axis=2)
    _, thresh = cv2.threshold(gray, 200, 255, cv2.THRESH_BINARY)
    row_sums = np.sum(thresh, axis=1) / 255
    staff_lines = np.where(row_sums > m_img.shape[1] * 0.5)[0]
    y_staff = staff_lines[0] if len(staff_lines) > 0 else 50
    crop_y1 = max(0, y_staff - 60)
    crop_y2 = max(0, y_staff - 5)
    crop_x1 = 0
    crop_x2 = min(60, m_img.shape[1])
    if crop_y2 <= crop_y1 or crop_x2 <= crop_x1: return None
    sprite = thresh[crop_y1:crop_y2, crop_x1:crop_x2]
    if np.count_nonzero(sprite > 127) < 8: return None
    return sprite

img_path = r"C:\Users\Certes\.gemini\antigravity\brain\975cea00-dd68-4689-9ee3-f1a2408b4ee6\final_check_100_sec.png"
img = cv2.imread(img_path)

h, w = img.shape[:2]
gray = np.max(img, axis=2)
col_sums = np.sum(gray < 100, axis=0) # white padding is 255, black measures are <100
# ACTUALLY, final image has white padding for rows. And black background for music.
# Let's just crop based on the stitched widths.
# Better yet, just use a sliding window template match on the number sprite!
# Even simpler: just visually save the sprites of the FIRST measure of every ROW!

rows = []
for y in range(0, h, 320): # assuming chunk height is around 320
    chunk = img[y:y+320, :]
    if np.max(chunk) > 200:
        rows.append(chunk)

print(f"Detected {len(rows)} A4 rows in final image.")

for i, row in enumerate(rows):
    gray_row = np.max(row, axis=2)
    _, binary = cv2.threshold(gray_row, 200, 255, cv2.THRESH_BINARY)
    
    # Just save the first 100x100 box of the row where the number sprite usually is
    row_sums = np.sum(binary, axis=1) / 255
    staff_lines = np.where(row_sums > w * 0.4)[0]
    if len(staff_lines) > 0:
        y_staff = staff_lines[0]
        crop_y1 = max(0, y_staff - 60)
        crop_y2 = max(0, y_staff - 5)
        sprite = binary[crop_y1:crop_y2, 10:80]
        
        cv2.imwrite(f"C:/Users/Certes/Desktop/guitar_score/debug_ocr_measure_{i}.png", sprite)
        pixels = np.count_nonzero(sprite > 127)
        print(f"Row {i} parsed. Sprite white pixels: {pixels}")