"""干净标定 + 精确求解 + 落点 ground-truth(中途截图)。 标定(慢 swipe 114->900, 6s; 中途 c1@2s c2@4s c3@5.5s): - diff(c1,c2): 拼图块位移 / handle位移(262px) = ratio - diff(ref,c1): home 簇(左) => home_center - c3 近 max-reach: 看 piece 最远能到哪(验证轨道是否够长) 刷新后重测缺口 => 按 ratio 求 handle 目标 => swipe; 中途截图验证落点。 """ from __future__ import annotations import subprocess import time from io import BytesIO import numpy as np from PIL import Image PHOTO_LEFT, PHOTO_RIGHT = 66, 1013 PHOTO_TOP, PHOTO_BOT = 267, 819 HANDLE_HOME_X = 114 TRACK_Y = 950 def adb_text(*a): r = subprocess.run(["adb", *a], capture_output=True, text=True, encoding="utf-8", errors="replace", timeout=60) return r.stdout def cap(): d = subprocess.run(["adb", "exec-out", "screencap", "-p"], capture_output=True, timeout=30).stdout return np.asarray(Image.open(BytesIO(d)).convert("L")) def photo(img): return img[PHOTO_TOP:PHOTO_BOT, PHOTO_LEFT:PHOTO_RIGHT] def detect_notch(img, x_min_local=230, col_thr=25): reg = photo(img) col = (reg < 90).sum(axis=0) col_r = col[x_min_local:] hot = np.where(col_r > col_thr)[0] if len(hot) == 0: return None br = np.where(np.diff(hot) > 12)[0] segs = [s for s in np.split(hot, br + 1) if len(s) > 10] seg = max(segs, key=lambda s: col_r[s].sum()) segL = x_min_local + int(seg[0]) segR = x_min_local + int(seg[-1]) block = (reg[:, segL:segR + 1] < 95) ys, xs = np.where(block) if len(xs) == 0: return None cx = PHOTO_LEFT + int(round(np.average(xs + segL))) return cx def detect_handle(img): band = img[925:980, :] col = (band < 235).sum(axis=0) hot = np.where(col > 20)[0] if len(hot) == 0: return HANDLE_HOME_X br = np.where(np.diff(hot) > 8)[0] segs = [s for s in np.split(hot, br + 1) if s[0] < 320] if not segs: segs = np.split(hot, br + 1) seg = max(segs, key=lambda s: col[s].sum()) return int(round(np.average(seg, weights=col[seg]))) def diff_centroids(a, b, thr=45): """帧差 -> 拼图块足迹簇的局部 cx 列表(按 x 排序)。""" d = np.abs(b.astype(np.int16) - a.astype(np.int16)) mask = d > thr col = mask.sum(axis=0) hot = np.where(col > 6)[0] if len(hot) == 0: return [] w = np.where(col > 6, col, 0) br = np.where(np.diff(hot) > 12)[0] out = [] for s in np.split(hot, br + 1): if len(s) > 12: out.append(int(round(np.average(s, weights=w[s])))) return sorted(out) def main(): ref = cap() hh = detect_handle(ref) print(f"[init] handle_home={hh} notchA={detect_notch(ref)}", flush=True) DH = 900 - hh p = subprocess.Popen(["adb", "shell", "input", "swipe", str(hh), str(TRACK_Y), "900", str(TRACK_Y), "6000"]) time.sleep(2.0); c1 = cap() time.sleep(2.0); c2 = cap() time.sleep(1.5); c3 = cap() p.wait() time.sleep(2.2) # 释放 => refresh # ratio: c1->c2 (handle disp = DH*2/6) dh_c1c2 = DH * 2.0 / 6.0 b12 = diff_centroids(photo(c1), photo(c2)) ratio = None if len(b12) >= 2: shift = b12[-1] - b12[0] ratio = shift / dh_c1c2 print(f"[cal] c1->c2 blobs_local={b12} shift={shift} handle_disp={dh_c1c2:.0f} " f"=> ratio={ratio:.3f}", flush=True) # home: ref->c1 (handle disp = DH*2/6) b01 = diff_centroids(photo(ref), photo(c1)) home_center = None if len(b01) >= 2: home_center = PHOTO_LEFT + b01[0] if ratio is None: ratio = (b01[-1] - b01[0]) / dh_c1c2 print(f"[cal] ref->c1 blobs_local={b01} home_center={home_center} " f"(cross-ratio={(b01[-1]-b01[0])/dh_c1c2:.3f})", flush=True) # max-reach: where is piece in c3? diff(ref,c3) rightmost blob b03 = diff_centroids(photo(ref), photo(c3)) if b03: maxreach = PHOTO_LEFT + b03[-1] print(f"[cal] c3(ref->c3) blobs_local={b03} piece_rightmost@screen={maxreach} " f"(handle disp~{DH*5.5/6:.0f})", flush=True) print(f"[cal] => home_center={home_center} ratio={ratio}", flush=True) if home_center is None or ratio is None or ratio <= 0: print("[!] 标定失败", flush=True); return 2 fresh = cap() notch_cx = detect_notch(fresh) print(f"[fresh] notchB={notch_cx}", flush=True) if notch_cx is None: print("[!] 刷新后无缺口", flush=True); return 2 delta_piece = notch_cx - home_center delta_handle = delta_piece / ratio handle_target = int(round(hh + delta_handle)) print(f"[plan] notch_cx={notch_cx} home={home_center} ratio={ratio:.3f} " f"=> Δpiece={delta_piece:.0f} Δhandle={delta_handle:.0f} " f"swipe {hh}->{handle_target}", flush=True) adb_text("logcat", "-c") p2 = subprocess.Popen(["adb", "shell", "input", "swipe", str(hh), str(TRACK_Y), str(handle_target), str(TRACK_Y), "1600"]) time.sleep(0.9) mid = cap() # 落点 ground truth p2.wait() time.sleep(3.5) aft = cap() top = adb_text("shell", "dumpsys", "activity", "activities") after_top = next((l.strip() for l in top.splitlines() if "topResumedActivity" in l), "(none)") closed = "KwaiWebViewActivity" not in after_top photo_changed = not np.array_equal(photo(fresh), photo(aft)) # 落点: mid 时 piece 位置 (diff fresh,mid 右簇) landing = None bm = diff_centroids(photo(fresh), photo(mid)) if bm: landing = PHOTO_LEFT + bm[-1] print(f"[post] top={after_top[:72]}", flush=True) print(f"[post] closed={closed} photo_changed={photo_changed} " f"piece_landing@screen={landing} (notch={notch_cx}, Δ={landing-notch_cx if landing else '?'})", flush=True) if closed: print(">>> VERDICT: 活动关闭 => result=1, 真机指纹过 350014! 路径=真机 WebView/模拟器。", flush=True) elif photo_changed and landing is not None and abs(landing - notch_cx) <= 20: print(">>> VERDICT: 落点命中缺口(±20)却刷新 => 350014(号码被永久标记, 真机也过不去)。", flush=True) elif photo_changed: print(f">>> VERDICT: 刷新但落点偏 {landing-notch_cx:+.0f}px => 缺口错(350002), 调整再试。", flush=True) else: print(">>> VERDICT: 未刷新 => 滑动未生效。", flush=True) print("\n===== LOGCAT =====", flush=True) for ln in adb_text("logcat", "-d").splitlines(): low = ln.lower() if any(k in low for k in ("captcha", "verify", "3500", "ksecret", "result\"", "hardetect")): print(ln[:190], flush=True) return 0 if __name__ == "__main__": raise SystemExit(main())