From f7ce7b8f4efe6a8e72f71156f9c97aad4b18eebd Mon Sep 17 00:00:00 2001
From: Qiea <1310371422@qq.com>
Date: Tue, 12 Nov 2024 12:03:35 +0800
Subject: [PATCH] =?UTF-8?q?=E6=B7=BB=E5=8A=A0=E5=8A=9F=E8=83=BD?=
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1.calculate_probabilities计算概率
2.calculate_layer获取通道数
---
 cnn.c | 75 ++++++++++++++++++++++++++++++++++++++++++++++++-----------
 1 file changed, 61 insertions(+), 14 deletions(-)

diff --git a/cnn.c b/cnn.c
index 318fb5c..95e3a57 100644
--- a/cnn.c
+++ b/cnn.c
@@ -170,10 +170,6 @@ float* output(const float* input_matrix){
     float *affine2_rslt = (float *) malloc(sizeof(float)*7);
     memset(affine2_rslt, 0, sizeof(float)*7);
 
-// 比较输出层的最大值
-    float temp = -100; // 用于存储最大值的临时变量，初始化为一个非常小的值
-    int predict_num; // 用于存储预测的数字（对应最大值的索引）
-
 // 遍历10个输出神经元（假设有10个类别）
     for(int n=0; n<7; n++)
     {
@@ -188,18 +184,8 @@ float* output(const float* input_matrix){
         // 加上对应神经元的偏置
         affine2_temp = affine2_temp + fc2_weight.array[n];
         affine2_rslt[n] = affine2_temp; // 存储输出层的结果
-
-        // 寻找最大值
-        if(temp <= affine2_rslt[n])
-        {
-            temp = affine2_rslt[n]; // 更新最大值
-            predict_num = n; // 记录最大值对应的类别索引
-        }
     }
 
-    print_rslt(affine2_rslt,7,7);
-    printf("Label is:%d\r\n",predict_num+1);
-
     return affine2_rslt;
 }
 
@@ -266,6 +252,64 @@ float* generateMatrix(Model model, const float* value)
     return CNN_data;
 }
 
+float calculate_probabilities(float *input_array)
+{
+    float sum = 0;
+    u8 input_num = 7;
+    float *result = (float *) malloc(sizeof(float)*input_num);
+    memset(result, 0, sizeof(float)*input_num);
+
+    float *temp = (float *) malloc(sizeof(float)*input_num);
+    memset(temp, 0, sizeof(float)*input_num);
+
+    for (int i = 0; i < input_num; i++)
+    {
+        temp[i] = expf(input_array[i]);
+        sum = sum + temp[i];
+    }
+    for (int j = 0; j < input_num; j++)
+    {
+        result[j] = temp[j] / sum;
+        if(isnan(result[j]))result[j] = 1;
+    }
+
+    int max_index = 0;
+    float max_value = result[0];
+    for (int k = 1; k < input_num; k++)
+    {
+        if (result[k] > max_value)
+        {
+            max_value = result[k];
+            max_index = k;
+        }
+    }
+
+    float _tmp = result[max_index] * 100;
+    free(temp);
+    temp = NULL;
+    free(result);
+    result = NULL;
+    return _tmp;
+}
+
+
+u8 calculate_layer(float *input_array){
+    u8 input_num = 7;
+    u8 predict_num = 0;
+    float max_temp = -100;
+    for(int n=0; n<input_num; n++)
+    {
+        if(max_temp <= input_array[n])
+        {
+            max_temp = input_array[n]; // 更新最大值
+            predict_num = n; // 记录最大值对应的类别索引
+        }
+    }
+    //print_rslt(input_array,7,7);
+    return predict_num+1;
+}
+
+
 void cnn_run(){
     float value[3] = {0};
     calculate_statistics(data,&value[0]);
@@ -311,6 +355,9 @@ void cnn_run(){
         float* affine1_rslt = hidden(pool_rslt_3);
         float* affine2_rslt = output(affine1_rslt);
 
+        printf("概率：%f\r\n",calculate_probabilities(affine2_rslt));
+        printf("Label is:%d\r\n",calculate_layer(affine2_rslt));
+
         free(pool_rslt_3);
         pool_rslt_3 = NULL;
         free(affine1_rslt);