import cv2
import numpy as np
import sys
import glob

# Test matching between two chunks to see what the score was!
# Wait, the chunks are the output of the slicing!
# The tracker works on the original FRAMES!
# Let's test the tracker on the original frames!
# I will supply the exact logic used in the tracker.

def test_tracker():
    video_file = r"C:\Users\Certes\Desktop\guitar_score\output\サカナクション／新宝島(エレキギターTAB) 難易度★★★ sakanaction shintakarajima.mp4"
    cap = cv2.VideoCapture(video_file)
    
    panorama = None
    last_clean_frame = None
    in_transition = False
    last_conf = 1.0
    
    count = 0
    saved_matches = []
    
    while True:
        ret, frame = cap.read()
        if not ret: break
        
        count += 1
        if count % 15 != 0: # fps=2
            continue
            
        frame = cv2.resize(frame, (1280, 720))
        
        if panorama is None:
            panorama = frame.copy()
            last_clean_frame = frame.copy()
            continue
            
        # calculate shift
        prev_chan = last_clean_frame[:, :, 0]
        curr_chan = frame[:, :, 0]
        w = 1280
        template_w = int(w * 0.3)
        start_x = int(w * 0.6)
        template = prev_chan[:, start_x:start_x + template_w]
        
        res = cv2.matchTemplate(curr_chan, template, cv2.TM_CCOEFF_NORMED)
        _, conf, _, max_loc = cv2.minMaxLoc(res)
        dx = start_x - max_loc[0]
        if conf < 0.15 or dx <= 0:
            dx = 0
        if dx > w * 0.15:
            dx = 0
            
        if (conf < 0.45) or (last_conf - conf > 0.3):
            in_transition = True
        elif in_transition and conf > 0.85 and dx == 0:
            in_transition = False
            
            # overlap logic
            h = panorama.shape[0]
            new_page = frame.copy()
            search_w = min(1500, panorama.shape[1])
            search_region = panorama[:, -search_w:, 0]
            
            head_w = min(400, new_page.shape[1])
            head = new_page[:, 50:50+head_w, 0]
            
            res2 = cv2.matchTemplate(search_region, head, cv2.TM_CCOEFF_NORMED)
            _, max_val, _, matched_loc = cv2.minMaxLoc(res2)
            
            saved_matches.append(max_val)
            print(f"Page turn detected! Overlap match score: {max_val:.4f} at {matched_loc}")
            
            if max_val > 0.65:
                overlap_px = search_w - matched_loc[0] + 50
                if overlap_px < new_page.shape[1] - 50:
                    panorama = np.hstack([panorama, new_page[:, overlap_px:]])
                else:
                    pass
            else:
                panorama = np.hstack([panorama, new_page])
                
        elif dx > 0 and dx < w and not in_transition:
            new_strip = frame[:, w - dx:, :]
            panorama = np.hstack([panorama, new_strip])

        last_conf = conf
        last_clean_frame = frame.copy()
        
        if len(saved_matches) >= 3:
            break
            
    cap.release()
    print("Test complete.")

if __name__ == "__main__":
    test_tracker()