diff --git a/bb_chart_2026_03_02.html b/bb_chart_2026_03_02.html new file mode 100644 index 0000000..2533fdb --- /dev/null +++ b/bb_chart_2026_03_02.html @@ -0,0 +1,145 @@ + + + + + ETHUSDT 2026-03-02 K线 + 布林带 + + + + +
+ + + + diff --git a/bb_trade_log_20260301.txt b/bb_trade_log_20260301.txt deleted file mode 100644 index 342ab27..0000000 --- a/bb_trade_log_20260301.txt +++ /dev/null @@ -1,368 +0,0 @@ - -============================================================ -时间: 2026-03-01 03:34:26 -操作: 加仓空#1 -价格: 1945.80 -BB上轨: 1942.91 | 中轨: 1928.45 | 下轨: 1913.99 -原因: 价格最高1945.80触及上轨1942.91，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 03:35:28 -操作: 加仓空#2 -价格: 1946.06 -BB上轨: 1947.60 | 中轨: 1930.12 | 下轨: 1912.64 -原因: 价格最高1948.81触及上轨1947.60，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-01 04:20:55 -操作: 加仓空#3 -价格: 1956.54 -BB上轨: 1958.72 | 中轨: 1947.07 | 下轨: 1935.42 -原因: 价格最高1963.78触及上轨1958.72，BB(10,2.5) (加仓#3/3) -============================================================ - -============================================================ -时间: 2026-03-01 06:37:04 -操作: 开空 -价格: 1981.98 -BB上轨: 1971.65 | 中轨: 1961.60 | 下轨: 1951.55 -原因: 价格最高1982.00触及上轨1971.65，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 08:04:15 -操作: 加仓空#1 -价格: 1968.36 -BB上轨: 1967.65 | 中轨: 1961.56 | 下轨: 1955.46 -原因: 价格最高1968.37触及上轨1967.65，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 09:11:15 -操作: 翻转: 平空→开多 -价格: 1948.38 -BB上轨: 1965.27 | 中轨: 1957.74 | 下轨: 1950.20 -原因: 价格最低1948.07触及下轨1950.20，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 09:15:44 -操作: 加仓多#1 -价格: 1946.42 -BB上轨: 1966.34 | 中轨: 1956.43 | 下轨: 1946.53 -原因: 价格最低1946.20触及下轨1946.53，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 09:37:21 -操作: 翻转: 平多→开空 -价格: 1966.51 -BB上轨: 1967.60 | 中轨: 1955.23 | 下轨: 1942.85 -原因: 价格最高1967.64触及上轨1967.60，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 09:47:41 -操作: 加仓空#1 -价格: 1974.91 -BB上轨: 1973.88 | 中轨: 1956.84 | 下轨: 1939.80 -原因: 价格最高1974.91触及上轨1973.88，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 09:50:10 -操作: 加仓空#2 -价格: 1990.01 -BB上轨: 1988.73 | 中轨: 1959.52 | 下轨: 1930.30 -原因: 价格最高1991.56触及上轨1988.73，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-01 09:59:41 -操作: 开空 -价格: 2009.09 -BB上轨: 2008.95 | 中轨: 1964.55 | 下轨: 1920.15 -原因: 价格最高2009.20触及上轨2008.95，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 10:02:15 -操作: 加仓空#1 -价格: 2023.05 -BB上轨: 2025.72 | 中轨: 1970.39 | 下轨: 1915.07 -原因: 价格最高2026.00触及上轨2025.72，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 11:22:14 -操作: 开多 -价格: 2028.59 -BB上轨: 2042.05 | 中轨: 2035.46 | 下轨: 2028.87 -原因: 价格最低2028.58触及下轨2028.87，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 11:54:08 -操作: 加仓多#1 -价格: 2023.39 -BB上轨: 2039.59 | 中轨: 2032.27 | 下轨: 2024.96 -原因: 价格最低2021.86触及下轨2024.96，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 11:55:14 -操作: 加仓多#2 -价格: 2020.39 -BB上轨: 2042.34 | 中轨: 2030.59 | 下轨: 2018.84 -原因: 价格最低2018.50触及下轨2018.84，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-01 12:15:00 -操作: 加仓多#3 -价格: 2012.23 -BB上轨: 2039.99 | 中轨: 2026.95 | 下轨: 2013.91 -原因: 价格最低2008.07触及下轨2013.91，BB(10,2.5) (加仓#3/3) -============================================================ - -============================================================ -时间: 2026-03-01 13:20:34 -操作: 翻转: 平多→开空 -价格: 2017.26 -BB上轨: 2017.21 | 中轨: 2014.22 | 下轨: 2011.24 -原因: 价格最高2017.47触及上轨2017.21，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 13:25:07 -操作: 加仓空#1 -价格: 2021.89 -BB上轨: 2021.00 | 中轨: 2015.09 | 下轨: 2009.17 -原因: 价格最高2021.58触及上轨2021.00，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 13:55:06 -操作: 翻转: 平空→开多 -价格: 2009.30 -BB上轨: 2023.23 | 中轨: 2016.18 | 下轨: 2009.13 -原因: 价格最低2008.73触及下轨2009.13，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 14:04:49 -操作: 加仓多#1 -价格: 2005.00 -BB上轨: 2024.71 | 中轨: 2015.13 | 下轨: 2005.56 -原因: 价格最低2005.00触及下轨2005.56，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 14:05:27 -操作: 加仓多#2 -价格: 2001.68 -BB上轨: 2026.45 | 中轨: 2014.43 | 下轨: 2002.41 -原因: 价格最低2001.68触及下轨2002.41，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-01 14:10:46 -操作: 加仓多#3 -价格: 1993.93 -BB上轨: 2029.77 | 中轨: 2012.76 | 下轨: 1995.76 -原因: 价格最低1993.62触及下轨1995.76，BB(10,2.5) (加仓#3/3) -============================================================ - -============================================================ -时间: 2026-03-01 15:12:06 -操作: 翻转: 平多→开空 -价格: 2003.74 -BB上轨: 2003.48 | 中轨: 1996.50 | 下轨: 1989.52 -原因: 价格最高2003.74触及上轨2003.48，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 15:22:02 -操作: 加仓空#1 -价格: 2004.51 -BB上轨: 2004.32 | 中轨: 1996.69 | 下轨: 1989.06 -原因: 价格最高2004.51触及上轨2004.32，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 15:39:37 -操作: 加仓空#2 -价格: 2006.49 -BB上轨: 2005.89 | 中轨: 1998.49 | 下轨: 1991.09 -原因: 价格最高2007.16触及上轨2005.89，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-01 15:40:18 -操作: 加仓空#3 -价格: 2005.95 -BB上轨: 2008.50 | 中轨: 1999.85 | 下轨: 1991.20 -原因: 价格最高2008.89触及上轨2008.50，BB(10,2.5) (加仓#3/3) -============================================================ - -============================================================ -时间: 2026-03-01 16:47:20 -操作: 翻转: 平空→开多 -价格: 1997.54 -BB上轨: 2011.42 | 中轨: 2004.66 | 下轨: 1997.89 -原因: 价格最低1997.54触及下轨1997.89，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 16:50:39 -操作: 加仓多#1 -价格: 1994.11 -BB上轨: 2012.88 | 中轨: 2003.62 | 下轨: 1994.36 -原因: 价格最低1994.00触及下轨1994.36，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 16:55:10 -操作: 加仓多#2 -价格: 1984.53 -BB上轨: 2019.59 | 中轨: 2002.06 | 下轨: 1984.53 -原因: 价格最低1984.04触及下轨1984.53，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-01 17:02:18 -操作: 加仓多#3 -价格: 1977.78 -BB上轨: 2021.30 | 中轨: 2000.09 | 下轨: 1978.87 -原因: 价格最低1977.34触及下轨1978.87，BB(10,2.5) (加仓#3/3) -============================================================ - -============================================================ -时间: 2026-03-01 18:26:31 -操作: 翻转: 平多→开空 -价格: 1981.80 -BB上轨: 1982.79 | 中轨: 1979.44 | 下轨: 1976.08 -原因: 价格最高1982.80触及上轨1982.79，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 18:30:23 -操作: 加仓空#1 -价格: 1985.00 -BB上轨: 1984.64 | 中轨: 1979.89 | 下轨: 1975.13 -原因: 价格最高1985.00触及上轨1984.64，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 18:35:09 -操作: 加仓空#2 -价格: 1986.68 -BB上轨: 1986.58 | 中轨: 1980.49 | 下轨: 1974.40 -原因: 价格最高1986.68触及上轨1986.58，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-01 19:16:32 -操作: 加仓空#3 -价格: 1987.27 -BB上轨: 1987.94 | 中轨: 1983.79 | 下轨: 1979.63 -原因: 价格最高1987.96触及上轨1987.94，BB(10,2.5) (加仓#3/3) -============================================================ - -============================================================ -时间: 2026-03-01 20:28:43 -操作: 翻转: 平空→开多 -价格: 1979.84 -BB上轨: 1987.42 | 中轨: 1983.66 | 下轨: 1979.90 -原因: 价格最低1979.64触及下轨1979.90，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 20:34:05 -操作: 加仓多#1 -价格: 1978.24 -BB上轨: 1987.88 | 中轨: 1983.22 | 下轨: 1978.55 -原因: 价格最低1978.24触及下轨1978.55，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 21:20:40 -操作: 加仓多#2 -价格: 1973.00 -BB上轨: 1982.99 | 中轨: 1978.04 | 下轨: 1973.10 -原因: 价格最低1973.00触及下轨1973.10，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-01 21:51:21 -操作: 翻转: 平多→开空 -价格: 1981.17 -BB上轨: 1980.40 | 中轨: 1976.08 | 下轨: 1971.77 -原因: 价格最高1981.82触及上轨1980.40，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 21:55:09 -操作: 开空 -价格: 2019.50 -BB上轨: 2011.12 | 中轨: 1980.16 | 下轨: 1949.21 -原因: 价格最高2019.50触及上轨2011.12，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 22:42:31 -操作: 翻转: 平空→开多 -价格: 1998.46 -BB上轨: 2021.45 | 中轨: 2010.61 | 下轨: 1999.77 -原因: 价格最低1997.98触及下轨1999.77，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 22:45:18 -操作: 加仓多#1 -价格: 1995.73 -BB上轨: 2021.76 | 中轨: 2008.71 | 下轨: 1995.66 -原因: 价格最低1995.55触及下轨1995.66，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 23:17:24 -操作: 翻转: 平多→开空 -价格: 2011.33 -BB上轨: 2011.41 | 中轨: 2003.47 | 下轨: 1995.52 -原因: 价格最高2011.70触及上轨2011.41，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-01 23:20:33 -操作: 加仓空#1 -价格: 2013.00 -BB上轨: 2012.52 | 中轨: 2003.72 | 下轨: 1994.92 -原因: 价格最高2013.00触及上轨2012.52，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-01 23:28:46 -操作: 加仓空#2 -价格: 2012.26 -BB上轨: 2012.18 | 中轨: 2003.62 | 下轨: 1995.05 -原因: 价格最高2012.30触及上轨2012.18，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-01 23:34:42 -操作: 加仓空#3 -价格: 2012.90 -BB上轨: 2013.39 | 中轨: 2003.97 | 下轨: 1994.56 -原因: 价格最高2013.42触及上轨2013.39，BB(10,2.5) (加仓#3/3) -============================================================ - -============================================================ -时间: 2026-03-01 23:57:04 -操作: 翻转: 平空→开多 -价格: 2000.60 -BB上轨: 2017.24 | 中轨: 2008.93 | 下轨: 2000.62 -原因: 价格最低2000.38触及下轨2000.62，BB(10,2.5) -============================================================ diff --git a/bb_trade_log_20260302.txt b/bb_trade_log_20260302.txt deleted file mode 100644 index 6947ebf..0000000 --- a/bb_trade_log_20260302.txt +++ /dev/null @@ -1,160 +0,0 @@ - -============================================================ -时间: 2026-03-02 00:00:12 -操作: 加仓多#1 -价格: 1993.03 -BB上轨: 2022.56 | 中轨: 2007.82 | 下轨: 1993.08 -原因: 价格最低1992.31触及下轨1993.08，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-02 00:47:35 -操作: 加仓多#2 -价格: 1991.52 -BB上轨: 2009.23 | 中轨: 2000.42 | 下轨: 1991.62 -原因: 价格最低1991.22触及下轨1991.62，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-02 00:50:07 -操作: 加仓多#3 -价格: 1972.92 -BB上轨: 2020.78 | 中轨: 1998.46 | 下轨: 1976.14 -原因: 价格最低1972.33触及下轨1976.14，BB(10,2.5) (加仓#3/3) -============================================================ - -============================================================ -时间: 2026-03-02 02:54:45 -操作: 翻转: 平空→开多 -价格: 1975.78 -BB上轨: 1987.69 | 中轨: 1981.61 | 下轨: 1975.53 -原因: 价格最低1974.35触及下轨1975.53，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-02 02:55:32 -操作: 加仓多#1 -价格: 1972.67 -BB上轨: 1988.35 | 中轨: 1980.89 | 下轨: 1973.42 -原因: 价格最低1972.66触及下轨1973.42，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-02 03:01:38 -操作: 加仓多#2 -价格: 1973.37 -BB上轨: 1985.83 | 中轨: 1979.58 | 下轨: 1973.32 -原因: 价格最低1972.87触及下轨1973.32，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-02 03:06:27 -操作: 加仓多#3 -价格: 1969.61 -BB上轨: 1986.78 | 中轨: 1978.35 | 下轨: 1969.93 -原因: 价格最低1968.00触及下轨1969.93，BB(10,2.5) (加仓#3/3) -============================================================ - -============================================================ -时间: 2026-03-02 04:10:24 -操作: 开多 -价格: 1938.14 -BB上轨: 1968.16 | 中轨: 1954.01 | 下轨: 1939.86 -原因: 价格最低1932.00触及下轨1939.86，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-02 04:15:20 -操作: 加仓多#1 -价格: 1931.04 -BB上轨: 1971.27 | 中轨: 1951.22 | 下轨: 1931.16 -原因: 价格最低1931.04触及下轨1931.16，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-02 05:21:09 -操作: 翻转: 平多→开空 -价格: 1925.01 -BB上轨: 1925.19 | 中轨: 1914.61 | 下轨: 1904.03 -原因: 价格最高1926.00触及上轨1925.19，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-02 06:03:53 -操作: 加仓空#1 -价格: 1930.73 -BB上轨: 1930.55 | 中轨: 1925.10 | 下轨: 1919.65 -原因: 价格最高1930.73触及上轨1930.55，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-02 06:13:08 -操作: 加仓空#2 -价格: 1933.10 -BB上轨: 1930.98 | 中轨: 1926.37 | 下轨: 1921.75 -原因: 价格最高1933.10触及上轨1930.98，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-02 06:15:10 -操作: 开空 -价格: 1944.64 -BB上轨: 1942.77 | 中轨: 1928.24 | 下轨: 1913.72 -原因: 价格最高1945.94触及上轨1942.77，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-02 08:07:31 -操作: 加仓空#1 -价格: 1943.79 -BB上轨: 1945.86 | 中轨: 1937.82 | 下轨: 1929.77 -原因: 价格最高1945.97触及上轨1945.86，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-02 08:10:09 -操作: 加仓空#2 -价格: 1950.40 -BB上轨: 1948.66 | 中轨: 1938.79 | 下轨: 1928.92 -原因: 价格最高1950.40触及上轨1948.66，BB(10,2.5) (加仓#2/3) -============================================================ - -============================================================ -时间: 2026-03-02 08:32:48 -操作: 加仓空#3 -价格: 1950.23 -BB上轨: 1950.72 | 中轨: 1942.27 | 下轨: 1933.83 -原因: 价格最高1950.89触及上轨1950.72，BB(10,2.5) (加仓#3/3) -============================================================ - -============================================================ -时间: 2026-03-02 09:10:45 -操作: 开空 -价格: 1980.63 -BB上轨: 1979.30 | 中轨: 1956.47 | 下轨: 1933.64 -原因: 价格最高1982.52触及上轨1979.30，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-02 10:06:29 -操作: 翻转: 平空→开多 -价格: 1956.56 -BB上轨: 1977.03 | 中轨: 1966.90 | 下轨: 1956.77 -原因: 价格最低1956.32触及下轨1956.77，BB(10,2.5) -============================================================ - -============================================================ -时间: 2026-03-02 10:10:10 -操作: 加仓多#1 -价格: 1948.99 -BB上轨: 1978.42 | 中轨: 1964.20 | 下轨: 1949.99 -原因: 价格最低1948.98触及下轨1949.99，BB(10,2.5) (加仓#1/3) -============================================================ - -============================================================ -时间: 2026-03-02 10:19:45 -操作: 加仓多#2 -价格: 1941.70 -BB上轨: 1981.96 | 中轨: 1961.75 | 下轨: 1941.53 -原因: 价格最低1941.34触及下轨1941.53，BB(10,2.5) (加仓#2/3) -============================================================ diff --git a/captcha_clip.py b/captcha_clip.py deleted file mode 100644 index 19f6811..0000000 --- a/captcha_clip.py +++ /dev/null @@ -1,113 +0,0 @@ -""" -用 CLIP 做图块相似度匹配，在大图中找模板图标位置 -原理：把大图切成滑动窗口小块，用 CLIP 计算每块和模板的视觉相似度，取最高分的块 -""" -import cv2 -import numpy as np -from PIL import Image -import torch -from transformers import CLIPProcessor, CLIPModel -from pathlib import Path - -BASE = Path(__file__).parent / "images" -MODEL_NAME = "openai/clip-vit-base-patch32" # 约600MB，小模型 - - -def load_clip(): - print("加载 CLIP 模型（约600MB，首次自动下载）...") - model = CLIPModel.from_pretrained(MODEL_NAME).to("cuda") - processor = CLIPProcessor.from_pretrained(MODEL_NAME) - print("CLIP 加载完成") - return model, processor - - -def find_by_clip(model, processor, main_img: np.ndarray, template_img: np.ndarray, - step=10, win_sizes=None): - """ - 滑动窗口 + CLIP 相似度，找模板在大图中的最佳位置 - """ - if win_sizes is None: - th, tw = template_img.shape[:2] - # 尝试原始尺寸及上下浮动 - win_sizes = [(int(tw * s), int(th * s)) for s in [0.8, 0.9, 1.0, 1.1, 1.2]] - - # 预处理模板 - tmpl_pil = Image.fromarray(cv2.cvtColor(template_img, cv2.COLOR_BGR2RGB)) - tmpl_inputs = processor(images=tmpl_pil, return_tensors="pt").to("cuda") - with torch.no_grad(): - tmpl_out = model.vision_model(**tmpl_inputs) - tmpl_feat = model.visual_projection(tmpl_out.pooler_output).float() - tmpl_feat = tmpl_feat / tmpl_feat.norm(dim=-1, keepdim=True) - - mh, mw = main_img.shape[:2] - best_score = -1 - best_box = None - - for (ww, wh) in win_sizes: - if ww > mw or wh > mh: - continue - for y in range(0, mh - wh + 1, step): - for x in range(0, mw - ww + 1, step): - crop = main_img[y:y+wh, x:x+ww] - crop_pil = Image.fromarray(cv2.cvtColor(crop, cv2.COLOR_BGR2RGB)) - crop_inputs = processor(images=crop_pil, return_tensors="pt").to("cuda") - with torch.no_grad(): - crop_out = model.vision_model(**crop_inputs) - crop_feat = model.visual_projection(crop_out.pooler_output).float() - crop_feat = crop_feat / crop_feat.norm(dim=-1, keepdim=True) - score = (tmpl_feat * crop_feat).sum().item() - if score > best_score: - best_score = score - best_box = (x, y, ww, wh) - - return best_box, best_score - - -def main(): - main_img = cv2.imread(str(BASE / "1.jpg")) - templates = { - "2.png": cv2.imread(str(BASE / "2.png")), - "3.png": cv2.imread(str(BASE / "3.png")), - "4.png": cv2.imread(str(BASE / "4.png")), - } - - # 模板是 BGRA，转 BGR - for name in templates: - img = cv2.imread(str(BASE / name), cv2.IMREAD_UNCHANGED) - if img.shape[2] == 4: - # alpha 通道合成白底 - alpha = img[:, :, 3:4] / 255.0 - rgb = img[:, :, :3].astype(float) - white = np.ones_like(rgb) * 255 - merged = (rgb * alpha + white * (1 - alpha)).astype(np.uint8) - templates[name] = merged - else: - templates[name] = img - - model, processor = load_clip() - - vis = main_img.copy() - colors = {"2.png": (0, 0, 255), "3.png": (0, 255, 0), "4.png": (255, 0, 0)} - - print() - for name, tmpl in templates.items(): - print(f"正在匹配 {name} ...") - box, score = find_by_clip(model, processor, main_img, tmpl, step=8) - if box: - x, y, w, h = box - cx, cy = x + w // 2, y + h // 2 - color = colors[name] - cv2.rectangle(vis, (x, y), (x+w, y+h), color, 2) - cv2.circle(vis, (cx, cy), 5, color, -1) - cv2.putText(vis, name, (x, y-5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 1) - print(f" {name}: 中心点 ({cx}, {cy}) 相似度={score:.4f}") - else: - print(f" {name}: 未找到") - - out = BASE / "result_clip.jpg" - cv2.imwrite(str(out), vis) - print(f"\n结果保存到: {out}") - - -if __name__ == "__main__": - main() diff --git a/captcha_vl.py b/captcha_vl.py deleted file mode 100644 index d60605d..0000000 --- a/captcha_vl.py +++ /dev/null @@ -1,131 +0,0 @@ -""" -用 Qwen2-VL 本地模型识别验证码图片位置 -首次运行会自动下载模型（约 4GB） -""" -import base64 -from pathlib import Path -from transformers import Qwen2VLForConditionalGeneration, AutoProcessor -from qwen_vl_utils import process_vision_info -import torch - -MODEL_NAME = "Qwen/Qwen2-VL-7B-Instruct" -BASE = Path(__file__).parent / "images" - -def img_to_base64(path): - with open(path, "rb") as f: - return base64.b64encode(f.read()).decode() - -def load_model(): - print("加载模型中（首次运行会下载约15GB）...") - from transformers import BitsAndBytesConfig - bnb_config = BitsAndBytesConfig( - load_in_4bit=True, - bnb_4bit_compute_dtype=torch.float16, - bnb_4bit_use_double_quant=True, - bnb_4bit_quant_type="nf4", - ) - model = Qwen2VLForConditionalGeneration.from_pretrained( - MODEL_NAME, - quantization_config=bnb_config, - device_map="cuda", - ) - processor = AutoProcessor.from_pretrained(MODEL_NAME) - print("模型加载完成") - return model, processor - -def ask_one(model, processor, main_img_path, template_path): - """让模型找出单个模板图在主图中的位置，返回原始回答""" - messages = [ - { - "role": "user", - "content": [ - { - "type": "text", - "text": ( - "下面是一张背景大图（300x200像素），" - "以及一个需要在大图中找到的小图标轮廓。\n" - "大图：" - ) - }, - {"type": "image", "image": str(main_img_path)}, - { - "type": "text", - "text": "\n小图标轮廓（这个图标出现在大图中某个物体上）：" - }, - {"type": "image", "image": str(template_path)}, - { - "type": "text", - "text": ( - "\n请仔细观察小图标的形状，在大图中找到形状最相似的物体，" - "给出该物体中心点的像素坐标。" - "坐标原点在左上角，x向右，y向下。" - "只需回答坐标，格式：(x, y)" - ) - } - ] - } - ] - - text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) - image_inputs, video_inputs = process_vision_info(messages) - inputs = processor( - text=[text], - images=image_inputs, - videos=video_inputs, - padding=True, - return_tensors="pt", - ).to("cuda") - - with torch.no_grad(): - generated_ids = model.generate(**inputs, max_new_tokens=50) - - generated_ids_trimmed = [ - out_ids[len(in_ids):] for in_ids, out_ids in zip(inputs.input_ids, generated_ids) - ] - output = processor.batch_decode( - generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False - ) - return output[0].strip() - - -def main(): - main_img = BASE / "1.jpg" - templates = [BASE / "2.png", BASE / "3.png", BASE / "4.png"] - - model, processor = load_model() - - import re - import cv2 - - img = cv2.imread(str(main_img)) - colors = {"2.png": (0, 0, 255), "3.png": (0, 255, 0), "4.png": (255, 0, 0)} - results = {} - - for tmpl_path in templates: - name = tmpl_path.name - print(f"\n正在识别 {name} ...") - answer = ask_one(model, processor, main_img, tmpl_path) - print(f"{name} 模型回答: {answer}") - - match = re.search(r"\((\d+)[,，\s]+(\d+)\)", answer) - if match: - x, y = int(match.group(1)), int(match.group(2)) - results[name] = (x, y) - color = colors[name] - cv2.circle(img, (x, y), 8, color, -1) - cv2.circle(img, (x, y), 12, color, 2) - cv2.putText(img, name, (x + 14, y + 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 1) - else: - print(f"{name}: 未能解析坐标，原始回答: {answer}") - - print("\n=== 点击坐标汇总 ===") - for name, (x, y) in results.items(): - print(f"{name}: ({x}, {y})") - - out = BASE / "result_vl.jpg" - cv2.imwrite(str(out), img) - print(f"\n可视化结果保存到: {out}") - - -if __name__ == "__main__": - main() diff --git a/credentials.json b/credentials.json deleted file mode 100644 index 08d7b9d..0000000 --- a/credentials.json +++ /dev/null @@ -1 +0,0 @@ -{"installed":{"client_id":"823839778551-mgovppr13aoil1r69upj7uiv84ej0sih.apps.googleusercontent.com","project_id":"gen-lang-client-0535910705","auth_uri":"https://accounts.google.com/o/oauth2/auth","token_uri":"https://oauth2.googleapis.com/token","auth_provider_x509_cert_url":"https://www.googleapis.com/oauth2/v1/certs","client_secret":"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","redirect_uris":["http://localhost"]}} \ No newline at end of file diff --git a/find_captcha.py b/find_captcha.py deleted file mode 100644 index 59a053e..0000000 --- a/find_captcha.py +++ /dev/null @@ -1,127 +0,0 @@ -""" -验证码图片匹配脚本 -在 1.jpg 中找到 2.png、3.png、4.png 的位置 -""" -import cv2 -import numpy as np -import os - -def find_template_in_image(main_img_path, template_path, threshold=0.5): - """ - 在主图中查找模板图片的位置（原始尺寸 + 多尺度） - 支持 PNG alpha 通道作为模板轮廓 - 返回置信度最高的匹配结果 - """ - main_img = cv2.imread(main_img_path) - template = cv2.imread(template_path, cv2.IMREAD_UNCHANGED) - - if main_img is None: - print(f"无法读取主图: {main_img_path}") - return [] - if template is None: - print(f"无法读取模板: {template_path}") - return [] - - h, w = template.shape[:2] - main_gray = cv2.cvtColor(main_img, cv2.COLOR_BGR2GRAY) - - # 如果模板有 alpha 通道且 RGB 全黑，用 alpha 通道作为灰度图 - if template.shape[2] == 4: - alpha = template[:, :, 3] - rgb_sum = template[:, :, :3].sum() - if rgb_sum == 0: - tmpl_gray = alpha # 用 alpha 通道 - else: - tmpl_gray = cv2.cvtColor(template[:, :, :3], cv2.COLOR_BGR2GRAY) - else: - tmpl_gray = cv2.cvtColor(template, cv2.COLOR_BGR2GRAY) - - best = None - - # 先尝试原始尺寸 - scales = [1.0] + list(np.linspace(0.6, 1.4, 17)) - for scale in scales: - rw, rh = int(w * scale), int(h * scale) - if rh < 5 or rw < 5: - continue - if rh > main_gray.shape[0] or rw > main_gray.shape[1]: - continue - - resized_tmpl = cv2.resize(tmpl_gray, (rw, rh)) - res = cv2.matchTemplate(main_gray, resized_tmpl, cv2.TM_CCOEFF_NORMED) - _, max_val, _, max_loc = cv2.minMaxLoc(res) - - if best is None or max_val > best["confidence"]: - best = { - "x": max_loc[0], - "y": max_loc[1], - "w": rw, - "h": rh, - "confidence": max_val, - "scale": scale, - "center_x": max_loc[0] + rw // 2, - "center_y": max_loc[1] + rh // 2, - } - - if best is None or best["confidence"] < threshold: - return [] - return [best] - - -def main(): - base_dir = os.path.join(os.path.dirname(__file__), "images") - main_img_path = os.path.join(base_dir, "1.jpg") - templates = ["2.png", "3.png", "4.png"] - - print(f"主图: {main_img_path}\n") - - all_results = {} - for tmpl_name in templates: - tmpl_path = os.path.join(base_dir, tmpl_name) - matches = find_template_in_image(main_img_path, tmpl_path, threshold=0.5) - all_results[tmpl_name] = matches - - if matches: - m = matches[0] - print(f"[{tmpl_name}] 找到匹配:") - print(f" 位置: ({m['x']}, {m['y']})") - print(f" 中心点: ({m['center_x']}, {m['center_y']})") - print(f" 尺寸: {m['w']}x{m['h']}") - print(f" 置信度: {m['confidence']:.4f}") - print(f" 缩放比例: {m['scale']:.2f}") - else: - print(f"[{tmpl_name}] 未找到匹配（置信度不足）") - print() - - # 可视化结果，保存标注图 - main_img = cv2.imread(main_img_path) - colors = [(0, 0, 255), (0, 255, 0), (255, 0, 0)] # 红、绿、蓝 - for i, tmpl_name in enumerate(templates): - matches = all_results.get(tmpl_name, []) - for m in matches: - x, y, w, h = m["x"], m["y"], m["w"], m["h"] - color = colors[i % len(colors)] - cv2.rectangle(main_img, (x, y), (x + w, y + h), color, 2) - cv2.putText(main_img, tmpl_name, (x, y - 5), - cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2) - # 画中心点 - cx, cy = m["center_x"], m["center_y"] - cv2.circle(main_img, (cx, cy), 5, color, -1) - - output_path = os.path.join(base_dir, "result.jpg") - cv2.imwrite(output_path, main_img) - print(f"标注结果已保存到: {output_path}") - - # 打印点击坐标汇总（用于自动化点击） - print("\n=== 点击坐标汇总 ===") - for tmpl_name in templates: - matches = all_results.get(tmpl_name, []) - if matches: - m = matches[0] - print(f"{tmpl_name}: 点击 ({m['center_x']}, {m['center_y']})") - else: - print(f"{tmpl_name}: 未找到") - - -if __name__ == "__main__": - main() diff --git a/gmail_reader.py b/gmail_reader.py deleted file mode 100644 index e4eff0c..0000000 --- a/gmail_reader.py +++ /dev/null @@ -1,208 +0,0 @@ -""" -Gmail API 邮件读取工具 -使用前准备： -1. 访问 https://console.cloud.google.com/ 创建项目 -2. 启用 Gmail API -3. 创建 OAuth 2.0 凭据（桌面应用类型），下载 credentials.json 放到本目录 -4. 首次运行会弹出浏览器授权，授权后自动生成 token.json -""" - -import os -import base64 -import json -from datetime import datetime -from google.auth.transport.requests import Request -from google.oauth2.credentials import Credentials -from google_auth_oauthlib.flow import InstalledAppFlow -from googleapiclient.discovery import build -from email.utils import parsedate_to_datetime - -# 只读权限 -SCOPES = ['https://www.googleapis.com/auth/gmail.readonly'] - -# 凭据文件路径（和脚本同目录） -BASE_DIR = os.path.dirname(os.path.abspath(__file__)) -CREDENTIALS_FILE = os.path.join(BASE_DIR, 'credentials.json') -TOKEN_FILE = os.path.join(BASE_DIR, 'token.json') - - -def get_service(): - """获取 Gmail API 服务实例""" - creds = None - - # 尝试加载已有 token - if os.path.exists(TOKEN_FILE): - creds = Credentials.from_authorized_user_file(TOKEN_FILE, SCOPES) - - # token 无效或过期，重新授权 - if not creds or not creds.valid: - if creds and creds.expired and creds.refresh_token: - creds.refresh(Request()) - else: - if not os.path.exists(CREDENTIALS_FILE): - print(f"❌ 找不到 {CREDENTIALS_FILE}") - print("请从 Google Cloud Console 下载 OAuth 凭据文件，命名为 credentials.json 放到本目录") - return None - flow = InstalledAppFlow.from_client_secrets_file(CREDENTIALS_FILE, SCOPES) - creds = flow.run_local_server(port=0) - - # 保存 token 供下次使用 - with open(TOKEN_FILE, 'w') as f: - f.write(creds.to_json()) - - return build('gmail', 'v1', credentials=creds) - - -def decode_body(payload): - """递归解析邮件正文（优先纯文本）""" - # 直接有 body data - if 'body' in payload and payload['body'].get('data'): - return base64.urlsafe_b64decode(payload['body']['data']).decode('utf-8', errors='ignore') - - # 多部分邮件，递归查找 - if 'parts' in payload: - # 优先找 text/plain - for part in payload['parts']: - if part.get('mimeType') == 'text/plain': - data = part['body'].get('data', '') - if data: - return base64.urlsafe_b64decode(data).decode('utf-8', errors='ignore') - - # 没有纯文本，找 text/html - for part in payload['parts']: - if part.get('mimeType') == 'text/html': - data = part['body'].get('data', '') - if data: - return base64.urlsafe_b64decode(data).decode('utf-8', errors='ignore') - - # 递归子部分 - for part in payload['parts']: - result = decode_body(part) - if result: - return result - - return None - - -def get_header(headers, name): - """从 headers 列表中取指定字段""" - for h in headers: - if h['name'].lower() == name.lower(): - return h['value'] - return '' - - -def list_emails(service, query='', label_ids=None, max_results=10): - """ - 列出邮件 - :param query: Gmail 搜索语法，如 'from:xxx@gmail.com' 'subject:报告' 'is:unread' - :param label_ids: 标签过滤，如 ['INBOX'], ['UNREAD'] - :param max_results: 最多返回条数 - """ - params = {'userId': 'me', 'maxResults': max_results} - if query: - params['q'] = query - if label_ids: - params['labelIds'] = label_ids - - results = service.users().messages().list(**params).execute() - return results.get('messages', []) - - -def read_email(service, msg_id): - """读取单封邮件详情""" - msg = service.users().messages().get(userId='me', id=msg_id, format='full').execute() - headers = msg['payload']['headers'] - - subject = get_header(headers, 'Subject') or '(无主题)' - sender = get_header(headers, 'From') - to = get_header(headers, 'To') - date_str = get_header(headers, 'Date') - body = decode_body(msg['payload']) or '(无正文)' - - # 解析日期 - try: - date = parsedate_to_datetime(date_str) - date_str = date.strftime('%Y-%m-%d %H:%M:%S') - except Exception: - pass - - return { - 'id': msg_id, - 'subject': subject, - 'from': sender, - 'to': to, - 'date': date_str, - 'body': body, - 'labels': msg.get('labelIds', []), - 'snippet': msg.get('snippet', ''), - } - - -def get_attachments(service, msg_id, save_dir=None): - """下载邮件附件""" - msg = service.users().messages().get(userId='me', id=msg_id, format='full').execute() - attachments = [] - - if save_dir is None: - save_dir = os.path.join(BASE_DIR, 'attachments') - - def _find_attachments(payload): - if 'parts' in payload: - for part in payload['parts']: - filename = part.get('filename', '') - if filename and part['body'].get('attachmentId'): - att = service.users().messages().attachments().get( - userId='me', messageId=msg_id, id=part['body']['attachmentId'] - ).execute() - data = base64.urlsafe_b64decode(att['data']) - - os.makedirs(save_dir, exist_ok=True) - filepath = os.path.join(save_dir, filename) - with open(filepath, 'wb') as f: - f.write(data) - - attachments.append({'filename': filename, 'path': filepath, 'size': len(data)}) - print(f" 📎 已保存附件: {filename} ({len(data)} bytes)") - - # 递归 - _find_attachments(part) - - _find_attachments(msg['payload']) - return attachments - - -# ============ 使用示例 ============ - -if __name__ == '__main__': - service = get_service() - if not service: - exit(1) - - print("=" * 60) - print("📬 Gmail 邮件读取") - print("=" * 60) - - # --- 示例1: 读取收件箱最近 5 封邮件 --- - print("\n📥 收件箱最近 5 封邮件:\n") - messages = list_emails(service, label_ids=['INBOX'], max_results=5) - - for m in messages: - email_data = read_email(service, m['id']) - print(f"📧 主题: {email_data['subject']}") - print(f" 发件人: {email_data['from']}") - print(f" 日期: {email_data['date']}") - print(f" 摘要: {email_data['snippet'][:80]}...") - print() - - # --- 示例2: 搜索特定邮件（取消注释使用）--- - # messages = list_emails(service, query='subject:报告 is:unread', max_results=5) - - # --- 示例3: 读取完整正文 --- - # if messages: - # email_data = read_email(service, messages[0]['id']) - # print(f"\n完整正文:\n{email_data['body']}") - - # --- 示例4: 下载附件 --- - # if messages: - # get_attachments(service, messages[0]['id']) diff --git a/images/1.jpg b/images/1.jpg deleted file mode 100644 index b61bdcf..0000000 Binary files a/images/1.jpg and /dev/null differ diff --git a/images/2.png b/images/2.png deleted file mode 100644 index 055b62a..0000000 Binary files a/images/2.png and /dev/null differ diff --git a/images/3.png b/images/3.png deleted file mode 100644 index e4d079d..0000000 Binary files a/images/3.png and /dev/null differ diff --git a/images/4.png b/images/4.png deleted file mode 100644 index c7c9823..0000000 Binary files a/images/4.png and /dev/null differ diff --git a/images/result_clip.jpg b/images/result_clip.jpg deleted file mode 100644 index 88aef20..0000000 Binary files a/images/result_clip.jpg and /dev/null differ diff --git a/images/result_vl.jpg b/images/result_vl.jpg deleted file mode 100644 index 1b9b0a9..0000000 Binary files a/images/result_vl.jpg and /dev/null differ diff --git a/match_alpha.py b/match_alpha.py deleted file mode 100644 index 017f9f2..0000000 --- a/match_alpha.py +++ /dev/null @@ -1,65 +0,0 @@ -import cv2 -import numpy as np - -base = 'c:/Users/27942/Desktop/codes/codex_jxs_code/images/' -main_img = cv2.imread(base + '1.jpg') -main_gray = cv2.cvtColor(main_img, cv2.COLOR_BGR2GRAY) - -def match_template_alpha(main_gray, alpha, name): - h, w = alpha.shape[:2] - best = None - - # 策略1: 直接用alpha通道匹配灰度图 - # 策略2: 用alpha做mask，只比较非透明区域 - # 策略3: 对alpha二值化后匹配 - - _, alpha_bin = cv2.threshold(alpha, 10, 255, cv2.THRESH_BINARY) - - scales = [1.0] + list(np.linspace(0.65, 1.35, 29)) - for scale in scales: - rw, rh = int(w * scale), int(h * scale) - if rh < 10 or rw < 10: - continue - if rh > main_gray.shape[0] or rw > main_gray.shape[1]: - continue - - resized_alpha = cv2.resize(alpha, (rw, rh)) - resized_bin = cv2.resize(alpha_bin, (rw, rh)) - _, resized_mask = cv2.threshold(resized_bin, 10, 255, cv2.THRESH_BINARY) - - # 用mask匹配（只看非透明区域） - res = cv2.matchTemplate(main_gray, resized_alpha, cv2.TM_CCOEFF_NORMED, mask=resized_mask) - _, max_val, _, max_loc = cv2.minMaxLoc(res) - - if best is None or max_val > best['conf']: - best = { - 'x': max_loc[0], 'y': max_loc[1], - 'w': rw, 'h': rh, - 'conf': max_val, 'scale': scale, - 'cx': max_loc[0] + rw // 2, - 'cy': max_loc[1] + rh // 2, - } - - return best - -results = {} -for name in ['2.png', '3.png', '4.png']: - template = cv2.imread(base + name, cv2.IMREAD_UNCHANGED) - alpha = template[:, :, 3] - best = match_template_alpha(main_gray, alpha, name) - results[name] = best - x, y, cx, cy = best['x'], best['y'], best['cx'], best['cy'] - conf, scale = best['conf'], best['scale'] - print(name + ': pos=(' + str(x) + ',' + str(y) + ') center=(' + str(cx) + ',' + str(cy) + ') conf=' + str(round(conf, 4)) + ' scale=' + str(round(scale, 2))) - -# 可视化 -colors = [(0, 0, 255), (0, 255, 0), (255, 0, 0)] -vis = main_img.copy() -for i, name in enumerate(['2.png', '3.png', '4.png']): - m = results[name] - cv2.rectangle(vis, (m['x'], m['y']), (m['x'] + m['w'], m['y'] + m['h']), colors[i], 2) - cv2.putText(vis, name, (m['x'], m['y'] - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, colors[i], 1) - cv2.circle(vis, (m['cx'], m['cy']), 5, colors[i], -1) - -cv2.imwrite(base + 'result.jpg', vis) -print('result saved to images/result.jpg') diff --git a/models/database.db b/models/database.db index bdc38fb..4796fd1 100644 Binary files a/models/database.db and b/models/database.db differ