<memory.h> #include <fstream> #include <iostream> const int state_dim = 34; const int act_dim = 12; using namespace std; static unsigned char *load_model(const char *filename, int *model_size) { FILE *fp = fopen(filename, "rb"); if (fp == nullptr) { printf("fopen %s fail...
size_with_stride);// Set memory for each input channelrknn_set_io_mem(ctx, app_ctx->input_mems[i], &input_attrs[0]);// Allocate memory for each output channelrknn_tensor_mem* output_mems[i] = rknn_create_mem(ctx, output_attrs[i].size_with_stride);// Set memory for each output...
I installed this yesterday, and RKNPU2 the day before. I have this same issue (terminal polluted with warnings, but otherwise working) with RKNPU2 1.5.2 and toolkit lite 1.5.2 but note that when I init the runtime it tells me: ...
Hello! I'm using your repo to convert default yolov8n model to rknn format. Running onnx2rknn_step2.py gives me the following errors: E RKNN: [16:20:31.860] REGTASK: The bit width of field value exceeds the limit, target: lite, offset: 0...
input_mems = rknn_create_mem(ctx, input_attrs.size); // create output tensor memory rknn_tensor_mem *output_mems; output_mems = rknn_create_mem(ctx, output_attrs.size); // Set input tensor memory ret = rknn_set_io_mem(ctx, input_mems, &input_attrs); if (ret < 0) { printf("...
memset(group, 0, sizeof(detect_result_group_t)); std::vector<float> filterBoxes; std::vector<float> boxesScore; std::vector<float> objProbs; std::vector<int> classId; // stride 8 int stride0 = 8; int grid_h0 = model_in_h / stride0; int grid_w0 = model_in_w / stride0;...