강현준 / 2018-1-capstone_design_1-Automated_calculation_system

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Hyunjun
bbb0ec9e 1 parent d4f81a61

add receipt code

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Showing 6 changed files with 114 additions and 12 deletions
...@@ -73,3 +73,7 @@ image_process.py : cropping을 통해 정사각형 형태를 만들고 32*32 크기로 resize, ...@@ -73,3 +73,7 @@ image_process.py : cropping을 통해 정사각형 형태를 만들고 32*32 크기로 resize,
73 73
74 15. params.pkl 추가 74 15. params.pkl 추가
75 제작한 데이터셋을 트레이닝하고 나온 가중치를 저장한 params.pkl 파일 추가 75 제작한 데이터셋을 트레이닝하고 나온 가중치를 저장한 params.pkl 파일 추가
76 +
77 +
78 +16. simple_convnet_rasberryPi 코드 추가
79 +인식한 결과에 따라 계산서가 나오도록 코드를 추가
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......
...@@ -26,9 +26,10 @@ private: ...@@ -26,9 +26,10 @@ private:
26 public: 26 public:
27 SimpleConvNet() {} 27 SimpleConvNet() {}
28 ~SimpleConvNet() {} 28 ~SimpleConvNet() {}
29 - SimpleConvNet(input_dim id, conv_param cp, int hidden_size=512, int output_size=10, bool pretrained=true) { 29 + SimpleConvNet(input_dim id, conv_param cp, int hidden_size = 512, int output_size = 10, bool pretrained = true) {
30 +
30 if (pretrained) 31 if (pretrained)
31 - load_trained("params.txt"); 32 + load_trained("params_noLNORM.txt");
32 33
33 layers.push_back(new Convolution(W[0], 1, 1)); 34 layers.push_back(new Convolution(W[0], 1, 1));
34 layers.push_back(new LightNormalization()); 35 layers.push_back(new LightNormalization());
...@@ -54,7 +55,7 @@ public: ...@@ -54,7 +55,7 @@ public:
54 layers.push_back(new Pooling(2, 2, 2)); 55 layers.push_back(new Pooling(2, 2, 2));
55 56
56 layers.push_back(new Affine(W[5])); 57 layers.push_back(new Affine(W[5]));
57 - layers.push_back(new LightNormalization()); 58 + //layers.push_back(new LightNormalization());
58 layers.push_back(new Relu()); 59 layers.push_back(new Relu());
59 60
60 layers.push_back(new Affine(W[6])); 61 layers.push_back(new Affine(W[6]));
...@@ -62,12 +63,15 @@ public: ...@@ -62,12 +63,15 @@ public:
62 63
63 std::vector< Mat > predict(std::vector<Mat>& x) { 64 std::vector< Mat > predict(std::vector<Mat>& x) {
64 for (int i = 0; i < layers.size(); i++) { 65 for (int i = 0; i < layers.size(); i++) {
66 + //printf("%d Layer : (%d, %d, %d, %d)\n",i, x.size(), x[0].dim, x[0].row, x[0].col);
65 x = layers[i]->forward(x); 67 x = layers[i]->forward(x);
66 } 68 }
69 + //printf("Layer : (%d %d %d %d)\n", x.size(), x[0].dim, x[0].row, x[0].col);
67 return x; 70 return x;
68 } 71 }
69 72
70 - double accuracy(std::vector< std::vector< unsigned char > > x, std::vector< int > ans, int batch_size=100) { 73 + double accuracy(std::vector< std::vector< unsigned char > > x, std::vector< int > ans, int batch_size = 100) {
74 + // ...
71 return 1.0; 75 return 1.0;
72 } 76 }
73 77
...@@ -87,7 +91,7 @@ public: ...@@ -87,7 +91,7 @@ public:
87 return pred; 91 return pred;
88 } 92 }
89 93
90 - void load_trained(const char* filename="params.txt") { 94 + void load_trained(const char* filename = "params.txt") {
91 FILE *f = fopen(filename, "r"); 95 FILE *f = fopen(filename, "r");
92 if (f == NULL) { 96 if (f == NULL) {
93 printf("File not found\n"); 97 printf("File not found\n");
...@@ -95,13 +99,13 @@ public: ...@@ -95,13 +99,13 @@ public:
95 } 99 }
96 char line[10] = { 0 }; 100 char line[10] = { 0 };
97 int keynum; 101 int keynum;
98 - while (fscanf(f, "%s", line)==1) { 102 + while (fscanf(f, "%s", line) == 1) {
99 char s[4][10] = { 0 }; 103 char s[4][10] = { 0 };
100 keynum = line[1] - '0' - 1; 104 keynum = line[1] - '0' - 1;
101 105
102 // get shape 106 // get shape
103 - fscanf(f, "%s", s[0]); 107 + fscanf(f, "%s", s[0]); // "(num
104 - fscanf(f, "%s", s[1]); 108 + fscanf(f, "%s", s[1]); // num
105 if (s[1][strlen(s[1]) - 1] != '\"') { 109 if (s[1][strlen(s[1]) - 1] != '\"') {
106 fscanf(f, "%s", s[2]); 110 fscanf(f, "%s", s[2]);
107 fscanf(f, "%s", s[3]); 111 fscanf(f, "%s", s[3]);
...@@ -109,7 +113,7 @@ public: ...@@ -109,7 +113,7 @@ public:
109 113
110 // nw = number of weights : shape[0] 114 // nw = number of weights : shape[0]
111 // size = input size of W[key] 115 // size = input size of W[key]
112 - int size = 1, nw=0; 116 + int size = 1, nw = 0;
113 for (int i = 0; i < 4; i++) { 117 for (int i = 0; i < 4; i++) {
114 int val = 0; 118 int val = 0;
115 for (int j = 0; j < strlen(s[i]); j++) { 119 for (int j = 0; j < strlen(s[i]); j++) {
...@@ -130,9 +134,9 @@ public: ...@@ -130,9 +134,9 @@ public:
130 for (int i = 0; i < size; i++) { 134 for (int i = 0; i < size; i++) {
131 fscanf(f, "%lf", &mm[i%fsize]); 135 fscanf(f, "%lf", &mm[i%fsize]);
132 if (i%fsize == fsize - 1) { 136 if (i%fsize == fsize - 1) {
133 - if(shape[keynum].size() == 2) 137 + if (shape[keynum].size() == 2)
134 W[keynum].push_back(Mat(1, 1, shape[keynum][1], std::vector<double>(mm, mm + fsize))); 138 W[keynum].push_back(Mat(1, 1, shape[keynum][1], std::vector<double>(mm, mm + fsize)));
135 - else if(shape[keynum].size() == 4) 139 + else if (shape[keynum].size() == 4)
136 W[keynum].push_back(Mat(shape[keynum][1], shape[keynum][2], 140 W[keynum].push_back(Mat(shape[keynum][1], shape[keynum][2],
137 shape[keynum][3], std::vector<double>(mm, mm + fsize))); 141 shape[keynum][3], std::vector<double>(mm, mm + fsize)));
138 } 142 }
......
1 #include"Layers.hpp" 1 #include"Layers.hpp"
2 #include"SimpleConvNet.hpp" 2 #include"SimpleConvNet.hpp"
3 +#include"fstream"
3 using namespace std; 4 using namespace std;
4 int main() { 5 int main() {
5 6
...@@ -44,6 +45,92 @@ int main() { ...@@ -44,6 +45,92 @@ int main() {
44 45
45 int num = 0, pd; 46 int num = 0, pd;
46 47
47 - printf("predict : %d ", pred[0]); 48 +
49 +
50 + char receipt[100];
51 + int total = 0;
52 +
53 + ifstream fin;
54 + ofstream fout;
55 + fin.open("receipt.txt");
56 + char c;
57 + int cnt=0;
58 +
59 + while(fin.get(c)){
60 + receipt[cnt] = c;
61 + cnt++;
62 + }
63 + fin.close();
64 +
65 + fout.open("receipt.txt");
66 + for(int i=0; i<cnt; i++){
67 + fout << receipt[i];
68 + }
69 +
70 + switch(pred[0]){
71 + case 0:
72 + cout << "can\n";
73 + fout << 0;
74 + break;
75 + case 1:
76 + cout << "ramen\n";
77 + fout << 1;
78 + break;
79 + case 2:
80 + cout << "cigarette\n";
81 + fout << 2;
82 + break;
83 + case 3:
84 + cout << "instant rice\n";
85 + fout << 3;
86 + break;
87 + case 4:
88 + cout << "wet tissue\n";
89 + fout << 4;
90 + break;
91 + default:
92 + cout << "try again\n";
93 + break;
94 + }
95 +
96 + fout.close();
97 +
98 + fin.open("receipt.txt");
99 + cnt=0;
100 +
101 + while(fin.get(c)){
102 + receipt[cnt] = c;
103 + cnt++;
104 + }
105 + fin.close();
106 + cout << "\n\n===================receipt===================\n\n\n";
107 + for(int i = 0; i<cnt; i++){
108 + switch(receipt[i]){
109 + case '0':
110 + cout << "can---------------------------------1,200Won\n";
111 + total += 1200;
112 + break;
113 + case '1':
114 + cout << "ramen-------------------------------1,000Won\n";
115 + total += 1000;
116 + break;
117 + case '2':
118 + cout << "cigarette---------------------------4,500Won\n";
119 + total += 4500;
120 + break;
121 + case '3':
122 + cout << "instant rice------------------------1,500Won\n";
123 + total += 1500;
124 + break;
125 + case '4':
126 + cout << "wet tissue--------------------------2,000Won\n";
127 + total += 2000;
128 + break;
129 + default:
130 + break;
131 + }
132 + }
133 + cout << "\nTotal-------------------------------" << total << "Won\n";
134 + cout << "\n\n=============================================\n\n\n";
48 return 0; 135 return 0;
49 } 136 }
......
...@@ -2,9 +2,14 @@ from numpy import array, savetxt ...@@ -2,9 +2,14 @@ from numpy import array, savetxt
2 from PIL import Image 2 from PIL import Image
3 import sys 3 import sys
4 import picamera 4 import picamera
5 +import time
5 6
6 camera = picamera.PiCamera() 7 camera = picamera.PiCamera()
7 8
9 +camera.start_preview()
10 +time.sleep(3)
11 +camera.stop_preview()
12 +
8 filename = 'image.jpg' 13 filename = 'image.jpg'
9 camera.capture(filename) 14 camera.capture(filename)
10 15
......
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1 +0201
2 +112
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