#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
测试 image-match：用模板图生成合成截图（模拟手机屏中缩略图），再跑匹配并校验中心点。
用法: python test_img_match.py <template_path> [screenshot_path]
  - 仅 template_path: 用模板生成合成截图再匹配（用于验证流程与 RoMa 参数）
  - template_path + screenshot_path: 用真实截图与模板匹配（用于实机调试）
输出: 打印 JSON 结果及期望中心点（合成时），成功时退出码 0。
"""
import os
import sys
import json
import tempfile
import subprocess

# 项目根目录
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
PROJECT_ROOT = os.path.dirname(os.path.dirname(SCRIPT_DIR))
IMAGE_MATCH = os.path.join(SCRIPT_DIR, "image-match.py")


def load_image_cv(path):
    import cv2
    import numpy as np
    with open(path, "rb") as f:
        data = np.frombuffer(f.read(), dtype=np.uint8)
    img = cv2.imdecode(data, cv2.IMREAD_COLOR)
    if img is not None:
        return img
    return cv2.imread(path)


def make_synthetic_screenshot(template_path, scale=0.45, offset_x=100, offset_y=350, screen_w=1080, screen_h=2340):
    """用模板图生成一张合成截图：黑色背景，模板缩放后贴在 (offset_x, offset_y)。"""
    import cv2
    import numpy as np
    tpl = load_image_cv(template_path)
    if tpl is None:
        raise FileNotFoundError(f"无法读取模板: {template_path}")
    h, w = tpl.shape[:2]
    new_w = int(round(w * scale))
    new_h = int(round(h * scale))
    small = cv2.resize(tpl, (new_w, new_h), interpolation=cv2.INTER_AREA)
    screen = np.zeros((screen_h, screen_w, 3), dtype=np.uint8)
    screen[:] = (30, 30, 30)  # 深灰模拟界面
    x1, y1 = offset_x, offset_y
    x2, y2 = min(offset_x + new_w, screen_w), min(offset_y + new_h, screen_h)
    sx2 = x2 - x1
    sy2 = y2 - y1
    screen[y1:y1 + sy2, x1:x1 + sx2] = small[:sy2, :sx2]
    expect_cx = offset_x + new_w // 2
    expect_cy = offset_y + new_h // 2
    return screen, (expect_cx, expect_cy, offset_x, offset_y, new_w, new_h)


def run_match(screenshot_path, template_path, method="feature"):
    py = os.environ.get("PYTHON", "python")
    cmd = [py, IMAGE_MATCH, screenshot_path, template_path, "0.8", method]
    r = subprocess.run(cmd, capture_output=True, text=True, timeout=60, cwd=PROJECT_ROOT)
    out = (r.stdout or "").strip()
    err = (r.stderr or "").strip()
    if r.returncode != 0 and out:
        try:
            return json.loads(out)
        except json.JSONDecodeError:
            pass
    if out:
        try:
            return json.loads(out)
        except json.JSONDecodeError:
            pass
    return {"success": False, "error": err or out or "unknown error", "returncode": r.returncode}


def main():
    if len(sys.argv) < 2:
        print("用法: python test_img_match.py <template_path> [screenshot_path]")
        sys.exit(2)
    template_path = os.path.abspath(sys.argv[1])
    if not os.path.exists(template_path):
        print(json.dumps({"success": False, "error": f"模板不存在: {template_path}"}))
        sys.exit(1)
    screenshot_path = sys.argv[2] if len(sys.argv) > 2 else None
    expect_center = None

    if screenshot_path is None:
        # 合成截图
        screenshot_path = os.path.join(tempfile.gettempdir(), "ef_test_screenshot.png")
        screen, (expect_cx, expect_cy, ox, oy, nw, nh) = make_synthetic_screenshot(
            template_path, scale=0.45, offset_x=100, offset_y=350
        )
        import cv2
        cv2.imwrite(screenshot_path, screen)
        expect_center = (expect_cx, expect_cy)
        print("合成截图已生成:", screenshot_path, "期望中心:", expect_center, file=sys.stderr)

    result = run_match(screenshot_path, template_path)
    print(json.dumps(result, ensure_ascii=False, indent=2))
    if expect_center and result.get("success"):
        cx, cy = result.get("center_x"), result.get("center_y")
        ex, ey = expect_center
        tol = 25
        if abs(cx - ex) <= tol and abs(cy - ey) <= tol:
            print("中心点与期望一致 (容差 %d px)" % tol, file=sys.stderr)
        else:
            print("中心点与期望偏差: 得到 (%d,%d) 期望 (%d,%d)" % (cx, cy, ex, ey), file=sys.stderr)
    if not result.get("success"):
        sys.exit(1)
    sys.exit(0)


if __name__ == "__main__":
    main()