"""
TelecomKz Pixel-Perfect OpenCV Long Screenshot Stitcher
Uses Template Matching to find exact subpixel scroll offsets and preserves fixed top & bottom navigation bars.
"""

import sys
import subprocess
import time
import io
import json
from pathlib import Path
import numpy as np
import cv2
from PIL import Image

ADB_PATHS = [
    r"C:\Users\user\AppData\Local\Android\Sdk\platform-tools\adb.exe",
    "adb"
]

def find_adb():
    for p in ADB_PATHS:
        try:
            res = subprocess.run([p, "version"], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
            if res.returncode == 0:
                return p
        except Exception:
            continue
    return "adb"

ADB_BIN = find_adb()

def get_device():
    res = subprocess.run([ADB_BIN, "devices"], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
    lines = res.stdout.strip().split("\n")[1:]
    for line in lines:
        parts = line.strip().split("\t")
        if len(parts) >= 2 and parts[1] == "device":
            return parts[0]
    return None

def capture_frame(dev):
    cmd = [ADB_BIN]
    if dev:
        cmd.extend(["-s", dev])
    cmd.extend(["exec-out", "screencap", "-p"])
    res = subprocess.run(cmd, stdout=subprocess.PIPE)
    if res.returncode == 0 and len(res.stdout) > 1000:
        arr = np.frombuffer(res.stdout, dtype=np.uint8)
        return cv2.imdecode(arr, cv2.IMREAD_UNCHANGED)
    return None

def stitch_perfect_long_screen(screen_id: str = "main_dashboard", scroll_steps: int = 3):
    dev = get_device()
    if not dev:
        print(json.dumps({"success": False, "error": "No Android device connected."}))
        return False
        
    print(f"Connecting to Android device {dev} for pixel-perfect stitching...")
    
    # 1. Capture Frame 1 (at top of page)
    f1 = capture_frame(dev)
    if f1 is None:
        print("Failed to capture Frame 1")
        return False
        
    h, w = f1.shape[:2] # 2340 x 1080
    top_bar_h = 255
    bottom_nav_y = 2140
    bottom_nav_h = h - bottom_nav_y # 200px
    
    top_bar = f1[0:top_bar_h, 0:w]
    bottom_nav = f1[bottom_nav_y:h, 0:w]
    
    # Current stitched scrollable canvas starts with Frame 1 middle content
    scrollable_canvas = f1[top_bar_h:bottom_nav_y, 0:w]
    
    # Frames capture loop with template matching
    swipes_done = 0
    for step in range(scroll_steps):
        # Swipe inside the scrollable window
        subprocess.run([ADB_BIN, "-s", dev, "shell", "input", "swipe", "540", "1700", "540", "900", "350"])
        time.sleep(1.0)
        swipes_done += 1
        
        f_next = capture_frame(dev)
        if f_next is None:
            break
            
        f_next_scroll = f_next[top_bar_h:bottom_nav_y, 0:w]
        
        # Take a 150px template strip from the bottom of current canvas (excluding right edge scrollbar)
        template_h = 150
        template_w = w - 80 # ignore right scrollbar zone
        template = scrollable_canvas[-template_h:, 20:template_w]
        
        # Match template in f_next_scroll
        res = cv2.matchTemplate(f_next_scroll[:, 20:template_w], template, cv2.TM_CCOEFF_NORMED)
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
        
        print(f"Step {step+1}: Match confidence = {max_val:.3f}, matched_y = {max_loc[1]}")
        
        if max_val > 0.70:
            match_y = max_loc[1]
            # New unique content is from match_y + template_h to bottom
            append_y = match_y + template_h
            if append_y < f_next_scroll.shape[0]:
                new_slice = f_next_scroll[append_y:, 0:w]
                scrollable_canvas = np.vstack([scrollable_canvas, new_slice])
        else:
            print(f"Low match confidence ({max_val:.2f}), using fixed fallback slice")
            new_slice = f_next_scroll[800:, 0:w]
            scrollable_canvas = np.vstack([scrollable_canvas, new_slice])
            
    # Assemble master image: [Top Bar] + [Continuous Scrollable Canvas] + [Bottom Navigation Bar]
    master_image = np.vstack([top_bar, scrollable_canvas, bottom_nav])
    
    # Save image
    screens_dir = Path("public/assets/screens")
    screens_dir.mkdir(parents=True, exist_ok=True)
    out_path = screens_dir / f"{screen_id}_long.png"
    
    cv2.imwrite(str(out_path), master_image)
    print(f"Flawless Stitched Image saved to: {out_path} (Resolution: {master_image.shape[1]}x{master_image.shape[0]})")
    
    # Scroll back up to initial position
    for _ in range(swipes_done):
        subprocess.run([ADB_BIN, "-s", dev, "shell", "input", "swipe", "540", "900", "540", "1700", "250"])
        time.sleep(0.3)
        
    return master_image.shape[1], master_image.shape[0]

if __name__ == "__main__":
    stitch_perfect_long_screen("main_dashboard", scroll_steps=2)