一些报错
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大佬大佬,我又遇到了一些问题,人脸注册之后再次进入系统,想要测试点名功能,但打开摄像头时会卡死退掉
get_known_faces_data 'gbk' codec can't decode byte 0xff in position 0: illegal multibyte sequence
open_face_bank: cannot unpack non-iterable NoneType object
还有一个,专注度分析的功能,测试本地视频时,视频也比较小,那些分析的曲线画不出来,会满屏的报错,说画的图片太多了
RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (matplotlib.pyplot.figure
) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam figure.max_open_warning
).
fig = plt.figure(figsize=(self.plot_base_h * aspect, self.plot_base_h))
大佬大佬,我又遇到了一些问题,人脸注册之后再次进入系统,想要测试点名功能,但打开摄像头时会卡死退掉
get_known_faces_data 'gbk' codec can't decode byte 0xff in position 0: illegal multibyte sequence
open_face_bank: cannot unpack non-iterable NoneType object还有一个,专注度分析的功能,测试本地视频时,视频也比较小,那些分析的曲线画不出来,会满屏的报错,说画的图片太多了
RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (matplotlib.pyplot.figure
) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParamfigure.max_open_warning
).
fig = plt.figure(figsize=(self.plot_base_h * aspect, self.plot_base_h))
大佬大佬,我又遇到了一些问题,人脸注册之后再次进入系统,想要测试点名功能,但打开摄像头时会卡死退掉
get_known_faces_data 'gbk' codec can't decode byte 0xff in position 0: illegal multibyte sequence
open_face_bank: cannot unpack non-iterable NoneType object
还有一个,专注度分析的功能,测试本地视频时,视频也比较小,那些分析的曲线画不出来,会满屏的报错,说画的图片太多了
RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (matplotlib.pyplot.figure
) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParamfigure.max_open_warning
).
fig = plt.figure(figsize=(self.plot_base_h * aspect, self.plot_base_h))
动态点名如何才可以签到成功?识别的准确率已经高于设置的阈值很久了,但还是一直不能签到上
大佬大佬,我又遇到了一些问题,人脸注册之后再次进入系统,想要测试点名功能,但打开摄像头时会卡死退掉
get_known_faces_data 'gbk' codec can't decode byte 0xff in position 0: illegal multibyte sequence
open_face_bank: cannot unpack non-iterable NoneType object
还有一个,专注度分析的功能,测试本地视频时,视频也比较小,那些分析的曲线画不出来,会满屏的报错,说画的图片太多了
RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (matplotlib.pyplot.figure
) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParamfigure.max_open_warning
).
fig = plt.figure(figsize=(self.plot_base_h * aspect, self.plot_base_h))动态点名如何才可以签到成功?识别的准确率已经高于设置的阈值很久了,但还是一直不能签到上
进入到已签到列表就算签到成功
大佬大佬,我又遇到了一些问题,人脸注册之后再次进入系统,想要测试点名功能,但打开摄像头时会卡死退掉
get_known_faces_data 'gbk' codec can't decode byte 0xff in position 0: illegal multibyte sequence
open_face_bank: cannot unpack non-iterable NoneType object
还有一个,专注度分析的功能,测试本地视频时,视频也比较小,那些分析的曲线画不出来,会满屏的报错,说画的图片太多了
RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (matplotlib.pyplot.figure
) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParamfigure.max_open_warning
).
fig = plt.figure(figsize=(self.plot_base_h * aspect, self.plot_base_h))动态点名如何才可以签到成功?识别的准确率已经高于设置的阈值很久了,但还是一直不能签到上
进入到已签到列表就算签到成功
大佬大佬,我又遇到了一些问题,人脸注册之后再次进入系统,想要测试点名功能,但打开摄像头时会卡死退掉
get_known_faces_data 'gbk' codec can't decode byte 0xff in position 0: illegal multibyte sequence
open_face_bank: cannot unpack non-iterable NoneType object
还有一个,专注度分析的功能,测试本地视频时,视频也比较小,那些分析的曲线画不出来,会满屏的报错,说画的图片太多了
RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (matplotlib.pyplot.figure
) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParamfigure.max_open_warning
).
fig = plt.figure(figsize=(self.plot_base_h * aspect, self.plot_base_h))动态点名如何才可以签到成功?识别的准确率已经高于设置的阈值很久了,但还是一直不能签到上
进入到已签到列表就算签到成功
你是不是自己改过代码?这个功能检测后会保留最好的匹配结果,改变阈值能动态调整签到列表。
大佬大佬,我又遇到了一些问题,人脸注册之后再次进入系统,想要测试点名功能,但打开摄像头时会卡死退掉
get_known_faces_data 'gbk' codec can't decode byte 0xff in position 0: illegal multibyte sequence
open_face_bank: cannot unpack non-iterable NoneType object
还有一个,专注度分析的功能,测试本地视频时,视频也比较小,那些分析的曲线画不出来,会满屏的报错,说画的图片太多了
RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (matplotlib.pyplot.figure
) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParamfigure.max_open_warning
).
fig = plt.figure(figsize=(self.plot_base_h * aspect, self.plot_base_h))动态点名如何才可以签到成功?识别的准确率已经高于设置的阈值很久了,但还是一直不能签到上
进入到已签到列表就算签到成功
你是不是自己改过代码?这个功能检测后会保留最好的匹配结果,改变阈值能动态调整签到列表。
改了代码,但点名这部分的功能没有改动,识别时准确率一直在65上下,所以就在运行的界面把识别的阈值调低了一点
大佬大佬,我又遇到了一些问题,人脸注册之后再次进入系统,想要测试点名功能,但打开摄像头时会卡死退掉
get_known_faces_data 'gbk' codec can't decode byte 0xff in position 0: illegal multibyte sequence
open_face_bank: cannot unpack non-iterable NoneType object
还有一个,专注度分析的功能,测试本地视频时,视频也比较小,那些分析的曲线画不出来,会满屏的报错,说画的图片太多了
RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (matplotlib.pyplot.figure
) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParamfigure.max_open_warning
).
fig = plt.figure(figsize=(self.plot_base_h * aspect, self.plot_base_h))动态点名如何才可以签到成功?识别的准确率已经高于设置的阈值很久了,但还是一直不能签到上
进入到已签到列表就算签到成功
你是不是自己改过代码?这个功能检测后会保留最好的匹配结果,改变阈值能动态调整签到列表。
改了代码,但点名这部分的功能没有改动,识别时准确率一直在65上下,所以就在运行的界面把识别的阈值调低了一点
你下一份原版的代码重新试一下吧
大佬大佬,我又遇到了一些问题,人脸注册之后再次进入系统,想要测试点名功能,但打开摄像头时会卡死退掉
get_known_faces_data 'gbk' codec can't decode byte 0xff in position 0: illegal multibyte sequence
open_face_bank: cannot unpack non-iterable NoneType object
还有一个,专注度分析的功能,测试本地视频时,视频也比较小,那些分析的曲线画不出来,会满屏的报错,说画的图片太多了
RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (matplotlib.pyplot.figure
) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParamfigure.max_open_warning
).
fig = plt.figure(figsize=(self.plot_base_h * aspect, self.plot_base_h))动态点名如何才可以签到成功?识别的准确率已经高于设置的阈值很久了,但还是一直不能签到上
进入到已签到列表就算签到成功
你是不是自己改过代码?这个功能检测后会保留最好的匹配结果,改变阈值能动态调整签到列表。
改了代码,但点名这部分的功能没有改动,识别时准确率一直在65上下,所以就在运行的界面把识别的阈值调低了一点
你下一份原版的代码重新试一下吧
还是不行的呀
你干脆把阈值设成1看看啥情况呗,也注意看看控制台有没有报错