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zhaoweicai / mscnn

Caffe implementation of our multi-scale object detection framework
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I want to train single channel images with cascade RCNN, which need to be modified #109

Open penghaoxiao opened 3 years ago

penghaoxiao commented 3 years ago

I1026 15:39:55.119289 15373 detection_data_layer.cpp:58] Window data layer: batch size: 2 cache_images: 0 root_folder: /VOCdevkit/ I1026 15:39:55.119340 15373 detection_data_layer.cpp:142] num: 0 /VOCdevkit/VOC2020/JPEGImages/3_3&18.tiff 1 1000 1000 windows to process I1026 15:39:55.119726 15373 detection_data_layer.cpp:150] Number of images: 53 I1026 15:39:55.119731 15373 detection_data_layer.cpp:155] class 0 has 0 samples I1026 15:39:55.119736 15373 detection_data_layer.cpp:155] class 1 has 803 samples I1026 15:39:55.119740 15373 detection_data_layer.cpp:163] Random aspect shuffling data I1026 15:39:55.120517 15373 detection_data_layer.cpp:233] output data size: 2,1,1024,1024 I1026 15:39:55.120568 15373 detection_data_layer.cpp:254] output label size 0 : 2,6,64,64 I1026 15:39:55.120611 15373 detection_data_layer.cpp:254] output label size 1 : 2,6,64,64 I1026 15:39:55.120657 15373 detection_data_layer.cpp:254] output label size 2 : 2,6,64,64 I1026 15:39:55.120709 15373 detection_data_layer.cpp:254] output label size 3 : 2,6,64,64 I1026 15:39:55.120752 15373 detection_data_layer.cpp:254] output label size 4 : 2,6,64,64 I1026 15:39:55.120791 15373 detection_data_layer.cpp:254] output label size 5 : 2,6,64,64 I1026 15:39:55.120843 15373 detection_data_layer.cpp:254] output label size 6 : 2,6,64,64 I1026 15:39:55.120882 15373 detection_data_layer.cpp:254] output label size 7 : 2,6,64,64 I1026 15:39:55.120923 15373 detection_data_layer.cpp:254] output label size 8 : 2,6,64,64 I1026 15:39:55.120961 15373 detection_data_layer.cpp:270] output gt boxes size: 1,8,1,1 F1026 15:39:55.120966 15373 detection_data_layer.cpp:281] Check failed: meanvalues.size() == 1 || meanvalues.size() == channels Speci Check failure stack trace: @ 0x7fbba1f655cd google::LogMessage::Fail() @ 0x7fbba1f67433 google::LogMessage::SendToLog() @ 0x7fbba1f6515b google::LogMessage::Flush() @ 0x7fbba1f67e1e google::LogMessageFatal::~LogMessageFatal() @ 0x7fbba26d1478 caffe::DetectionDataLayer<>::DataLayerSetUp() @ 0x7fbba2617775 caffe::BasePrefetchingDataLayer<>::LayerSetUp() @ 0x7fbba2564b5c caffe::Net<>::Init() @ 0x7fbba25673ae caffe::Net<>::Net() @ 0x7fbba2571b65 caffe::Solver<>::InitTrainNet() @ 0x7fbba2572f95 caffe::Solver<>::Init() @ 0x7fbba25732af caffe::Solver<>::Solver() @ 0x7fbba275cde1 caffe::Creator_SGDSolver<>() @ 0x416c5a caffe::SolverRegistry<>::CreateSolver() @ 0x40e25d train() @ 0x4097d3 main @ 0x7fbba0e5f840 __libc_start_main @ 0x40a1d9 _start @ (nil) (unknown)

zhaoweicai commented 3 years ago

Could you just pad your single channel image to rgb image?