param is too old, please regenerate
Your model file is being the old format converted by an old caffe2ncnn tool.
Checkout the latest ncnn code, build it and regenerate param and model binary files, and that should work.
Make sure that your param file starts with the magic number 7767517.
you may find more info on use-ncnn-with-alexnet
If the original model is missing, you can try to manually fix the layer specific parameters in param file
- Softmax append
1=1
before
Softmax xxx 1 1 in out ...
after
Softmax xxx 1 1 in out ... 1=1
- Reduction minus all axes value by 1 (except the leading array count) and append
5=1
before
Reduction xxx 1 1 in out ... -23303=2,2,3 ...
after
Reduction xxx 1 1 in out ... -23303=2,1,2 ... 5=1
find_blob_index_by_name XYZ failed
That means ncnn couldn't find the XYZ blob in the network.
You shall call Extractor::input()/extract() by blob name instead of layer name.
For models loaded from binary param file or external memory, you shall call Extractor::input()/extract() by the enum defined in xxx.id.h because all the visible string literals have been stripped in binary form.
This error usually happens when the input layer is not properly converted.
You shall upgrade caffe prototxt/caffemodel before converting it to ncnn. Following snippet type shall be ok.
layer {
name: "data"
type: "Input"
top: "data"
input_param { shape: { dim: 1 dim: 3 dim: 227 dim: 227 } }
}
you may find more info on use-ncnn-with-alexnet.
layer XYZ not exists or registered
Your network contains some operations that are not implemented in ncnn.
You may implement them as custom layer followed in how-to-implement-custom-layer-step-by-step.
Or you could simply register them as no-op if you are sure those operations make no sense.
class Noop : public ncnn::Layer {};
DEFINE_LAYER_CREATOR(Noop)
net.register_custom_layer("LinearRegressionOutput", Noop_layer_creator);
net.register_custom_layer("MAERegressionOutput", Noop_layer_creator);
fopen XYZ.param/XYZ.bin failed
File not found or not readable. Make sure that XYZ.param/XYZ.bin is accessible.
network graph not ready
You shall call Net::load_param() first, then Net::load_model().
This error may also happens when Net::load_param() failed, but not properly handled.
For more information about the ncnn model load api, see ncnn-load-model
memory not 32-bit aligned at XYZ
The pointer passed to Net::load_param() or Net::load_model() is not 32bit aligned.
In practice, the head pointer of std::vector is not guaranteed to be 32bit aligned.
you can store your binary buffer in ncnn::Mat structure, its internal memory is aligned.
undefined reference to '__kmpc_XYZ_XYZ'
use clang for building android shared library
comment the following line in your Application.mk
NDK_TOOLCHAIN_VERSION := 4.9
crash on android with '__kmp_abort_process'
This usually happens if you bundle multiple shared library with openmp linked
It is actually an issue of the android ndk https://github.com/android/ndk/issues/1028
On old android ndk, modify the link flags as
-Wl,-Bstatic -lomp -Wl,-Bdynamic
For recent ndk >= 21
-fstatic-openmp
dlopen failed: library "libomp.so" not found
Newer android ndk defaults to dynamic openmp runtime
modify the link flags as
-fstatic-openmp -fopenmp
crash when freeing a ncnn dynamic library(.dll/.so) built with openMP
for optimal performance, the openmp threadpool spin waits for about a second prior to shutting down in case more work becomes available.
If you unload a dynamic library that's in the process of spin-waiting, it will crash in the manner you see (most of the time).
Just set OMP_WAIT_POLICY=passive in your environment, before calling loadlibrary. or Just wait a few seconds before calling freelibrary.
You can also use the following method to set environment variables in your code:
for msvc++:
SetEnvironmentVariable(_T("OMP_WAIT_POLICY"), _T("passive"));
for g++:
setenv("OMP_WAIT_POLICY", "passive", 1)
reference: https://stackoverflow.com/questions/34439956/vc-crash-when-freeing-a-dll-built-with-openmp
Source: docs/how-to-use-and-FAQ/FAQ-ncnn-throw-error.md