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Added object Detection & Tracking using conv-rnn layer on frames from video

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This commit is contained in:
AlexeyAB
2019-03-02 03:32:24 +03:00
parent 50956447f8
commit 75f2a3e7cf
16 changed files with 962 additions and 187 deletions
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23
src/convolutional_kernels.cu
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@ -519,6 +519,15 @@ void forward_convolutional_layer_gpu(convolutional_layer l, network_state state)
else {
//#else
/*
int input_nan_inf = is_nan_or_inf(state.input, l.inputs * l.batch);
printf("\n is_nan_or_inf(state.input) = %d \n", input_nan_inf);
if (input_nan_inf) getchar();
int weights_nan_inf = is_nan_or_inf(l.weights_gpu, l.size * l.size * l.c * l.n);
printf("\n is_nan_or_inf(l.weights_gpu) = %d \n", weights_nan_inf);
if (weights_nan_inf) getchar();
*/
CHECK_CUDNN(cudnnConvolutionForward(cudnn_handle(),
&alpha, //&one,
@ -581,6 +590,10 @@ void forward_convolutional_layer_gpu(convolutional_layer l, network_state state)
//if(l.dot > 0) dot_error_gpu(l);
if(l.binary || l.xnor) swap_binary(&l);
//cudaDeviceSynchronize(); // for correct profiling of performance
if (state.net.try_fix_nan) {
fix_nan_and_inf(l.output_gpu, l.outputs*l.batch);
}
}
void backward_convolutional_layer_gpu(convolutional_layer l, network_state state)
@ -609,7 +622,6 @@ void backward_convolutional_layer_gpu(convolutional_layer l, network_state state
if (state.index != 0 && state.net.cudnn_half && !l.xnor && (!state.train || iteration_num > 3*state.net.burn_in) &&
l.c % 8 == 0 && l.n % 8 == 0)
{
const size_t input16_size = l.batch*l.c*l.w*l.h;
const size_t delta16_size = l.batch*l.n*l.out_w*l.out_h;
@ -762,6 +774,7 @@ void backward_convolutional_layer_gpu(convolutional_layer l, network_state state
&one,
l.dsrcTensorDesc,
state.delta));
if (l.binary || l.xnor) swap_binary(&l);
if (l.xnor) gradient_array_ongpu(original_input, l.batch*l.c*l.h*l.w, HARDTAN, state.delta);
}
@ -803,6 +816,14 @@ void backward_convolutional_layer_gpu(convolutional_layer l, network_state state
}
}
#endif
if (state.net.try_fix_nan) {
if (state.delta) {
fix_nan_and_inf(state.delta, l.inputs * l.batch);
}
int size = l.size * l.size * l.c * l.n;
fix_nan_and_inf(l.weight_updates_gpu, size);
fix_nan_and_inf(l.weights_gpu, size);
}
}
void pull_convolutional_layer(convolutional_layer layer)