From f52b9f1aee90819db01afed83506ead8eb6d3267 Mon Sep 17 00:00:00 2001 From: Qiea <1310371422@qq.com> Date: Mon, 11 Nov 2024 14:34:09 +0800 Subject: [PATCH] =?UTF-8?q?=E5=85=A8=E5=8A=9F=E8=83=BD=E5=AE=9E=E7=8E=B0?= =?UTF-8?q?=EF=BC=8C=E9=AA=8C=E8=AF=81=E9=80=9A=E8=BF=87=EF=BC=8C=E6=9A=82?= =?UTF-8?q?=E6=9C=AA=E7=B2=BE=E7=AE=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- cnn.c | 132 +++++++++++++++++++++++++++++++++++++++++----------- cnn.h | 1 + cnn_model.h | 7 ++- main.c | 2 + 4 files changed, 115 insertions(+), 27 deletions(-) diff --git a/cnn.c b/cnn.c index e02d06a..b2d7a54 100644 --- a/cnn.c +++ b/cnn.c @@ -14,11 +14,14 @@ void print_rslt(float* rslt, u8 input_matrix_length, u32 length){ printf("\r\n"); } - - // 将原始矩阵复制到填充后的矩阵中央 float* expand(const float* old_matrix, int old_matrix_length, int layer){ float* new_matrix = (float *)malloc(sizeof(float)*layer*(old_matrix_length+2)*(old_matrix_length+2)); + if (new_matrix == NULL) { + // 处理 malloc 失败的情况，例如打印错误并退出 + perror("Memory allocation failed"); + exit(1); // 退出程序 + } memset(new_matrix, 0, sizeof(float)*layer*(old_matrix_length+2)*(old_matrix_length+2)); for(int l=0; l < layer; l++){ for (int i = 0; i < old_matrix_length; i++) { @@ -33,8 +36,6 @@ float* expand(const float* old_matrix, int old_matrix_length, int layer){ return new_matrix; } - - //model 模型名字 //input_matrix 输入图像 //input_matrix_length 输入图像的边长：102 @@ -42,7 +43,6 @@ float* expand(const float* old_matrix, int old_matrix_length, int layer){ //返回卷积的结果 float* convolution(Model model_w, Model model_b, const float* input_matrix, int input_matrix_length){ // 初始化卷积层参数 - int _debug=0; int im_l = input_matrix_length; int cr_l = input_matrix_length - 2; float conv_temp; // 临时变量，用于存储卷积计算的中间结果 @@ -93,11 +93,10 @@ float* convolution(Model model_w, Model model_b, const float* input_matrix, int } } } + free(_conv_rlst); return conv_rlst; } - - //num_kernels 卷积核的个数：32 //area 池化的面积：2*2 //input_matrix 输入图像 @@ -137,8 +136,6 @@ float* pooling(Model model_w, const float* input_matrix, u8 input_matrix_length) return pool_rslt; } - - float* hidden(const float* input_matrix){ float affine1_temp; // 临时变量，用于存储全连接层的中间结果 float *affine1_rslt = (float *) malloc(sizeof(float)*128); @@ -170,8 +167,6 @@ float* hidden(const float* input_matrix){ return affine1_rslt; } - - float* output(const float* input_matrix){ float affine2_temp; // 临时变量，用于存储输出层的中间结果 float *affine2_rslt = (float *) malloc(sizeof(float)*7); @@ -212,22 +207,107 @@ float* output(const float* input_matrix){ -void cnn_run(){ +void calculate_statistics(Model model, float* value) +{ + value[0] = fabsf(model.array[0]); + float sum = 0; + float sum_sq = 0; -//第一层：填充102 * 102 - float* expand_matrix_1 = expand(data.array, 100, 1); - float* conv_rlst_1 = convolution(conv1_weight,conv1_bias,expand_matrix_1, 102); - float* pool_rslt_1 = pooling(conv1_weight, conv_rlst_1, 100); -//第二层：填充32 * 52 * 52 - float* expand_matrix_2 = expand(pool_rslt_1, 50, 32); - float* conv_rlst_2 = convolution(conv2_weight,conv2_bias,expand_matrix_2, 52); - float* pool_rslt_2 = pooling(conv2_weight, conv_rlst_2, 50); -//第三层：填充 64 * 27 * 27 - float* expand_matrix_3 = expand(pool_rslt_2, 25, 64); - float* conv_rlst_3 = convolution(conv3_weight,conv3_bias,expand_matrix_3, 27); - float* pool_rslt_3 = pooling(conv3_weight, conv_rlst_3, 25); + for (int i = 0; i < model.maxlength; i++) { + float abs_val = fabsf(model.array[i]); - float* affine1_rslt = hidden(pool_rslt_3); - float* affine2_rslt = output(affine1_rslt); + if (abs_val > value[0]) { + value[0] = abs_val; + } + sum += abs_val; + sum_sq += abs_val * abs_val; + } + value[1] = sum / (float)model.maxlength; + + float variance = (sum_sq / (float)model.maxlength) - (value[1] * value[1]); + value[2] = sqrtf(variance); +} + +u8 check_threshold(Model model, const float* value) +{ + const float threshold = 20; + + for (int i = 0; i < model.maxlength; i++) { + float K = (fabsf(model.array[i]) - value[1]) / value[2]; + if (K > threshold) { + return 1; + } + } + return 0; +} + +float* generateMatrix(Model model, const float* value) +{ + float* CNN_data = (float*) malloc(sizeof(float)*100*100); + memset(CNN_data, 0, sizeof(float)*100*100); + + u16 x = model.maxlength / 100; + float y = value[0] / 100; + + for (int i = 0; i < model.maxlength; i++) { + float absolutevalue = fabsf(model.array[i]); + + if (!absolutevalue) { + continue; + } + + int xIndex = i / x; + if (xIndex >= 100) xIndex = 99; + + int yIndex = (int)(absolutevalue / y); + if (yIndex < 0) yIndex = 0; + + CNN_data[yIndex * 100 + xIndex]++; + } + return CNN_data; +} + +void cnn_run(){ + float value[3] = {0}; + calculate_statistics(data,&value[0]); + if (check_threshold(data,&value[0])){ + + float* _data = generateMatrix(data,&value[0]); + +// printf("最大值:%f 平均值:%f 标准差:%f\r\n",value[0],value[1],value[2]); +// print_rslt(_data,100,1*100*100); + + //第一层：填充102 * 102 + float* expand_matrix_1 = expand(_data, 100, 1); + float* conv_rlst_1 = convolution(conv1_weight,conv1_bias,expand_matrix_1, 102); + float* pool_rslt_1 = pooling(conv1_weight, conv_rlst_1, 100); + + free(_data); + free(expand_matrix_1); + free(conv_rlst_1); + //第二层：填充32 * 52 * 52 + float* expand_matrix_2 = expand(pool_rslt_1, 50, 32); + float* conv_rlst_2 = convolution(conv2_weight,conv2_bias,expand_matrix_2, 52); + float* pool_rslt_2 = pooling(conv2_weight, conv_rlst_2, 50); + + free(pool_rslt_1); + free(expand_matrix_2); + free(conv_rlst_2); + //第三层：填充 64 * 27 * 27 + float* expand_matrix_3 = expand(pool_rslt_2, 25, 64); + float* conv_rlst_3 = convolution(conv3_weight,conv3_bias,expand_matrix_3, 27); + float* pool_rslt_3 = pooling(conv3_weight, conv_rlst_3, 25); + + free(pool_rslt_2); + free(expand_matrix_3); + free(conv_rlst_3); + + float* affine1_rslt = hidden(pool_rslt_3); + float* affine2_rslt = output(affine1_rslt); + + free(pool_rslt_3); + free(affine1_rslt); + free(affine2_rslt); + } } diff --git a/cnn.h b/cnn.h index 5b754f7..a82a173 100644 --- a/cnn.h +++ b/cnn.h @@ -2,6 +2,7 @@ #define _CNN_H_ #include "cnn_model.h" #include +#include diff --git a/cnn_model.h b/cnn_model.h index db32eb5..0f57f68 100644 --- a/cnn_model.h +++ b/cnn_model.h @@ -8,6 +8,7 @@ #include + typedef struct { char* name; char* dname; @@ -33,7 +34,11 @@ typedef struct { #define FC1_WEIGHT_ARRSIZE (128*18432) //2359296 #define FC2_BIAS_ARRSIZE (7) #define FC2_WEIGHT_ARRSIZE (7*128) //896 -#define DATA_ARRSIZE (100*100) //1250000 +#if 1 + #define DATA_ARRSIZE (1250000) +#else + #define DATA_ARRSIZE (100 * 100) +#endif diff --git a/main.c b/main.c index 6787288..fe4d15a 100644 --- a/main.c +++ b/main.c @@ -83,6 +83,8 @@ int main(){ model_write("all"); run_dataset(); +// model_switchdata("C1autosave00095_right_new_2"); +// cnn_run(); DEBUG_PRINTF("\r\nEnd结束"); } \ No newline at end of file