Kentarou Shimatani
action recognizer with theremin
Diff: predict.c
- Revision:
- 0:b9ac53c439ed
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/predict.c Wed Sep 14 13:42:46 2011 +0000
@@ -0,0 +1,237 @@
+#include <stdio.h>
+#include <ctype.h>
+#include <stdlib.h>
+#include <string.h>
+#include <errno.h>
+#include "svm.h"
+#include "predict.h"
+
+struct svm_node *x;
+int max_nr_attr = 64;
+
+struct svm_model* model;
+int predict_probability=0;
+
+static char *line = NULL;
+static int max_line_len;
+
+static char* readline(FILE *input)
+{
+ int len;
+
+ if(fgets(line,max_line_len,input) == NULL)
+ return NULL;
+
+ while(strrchr(line,'\n') == NULL)
+ {
+ max_line_len *= 2;
+ line = (char *) realloc(line,max_line_len);
+ len = (int) strlen(line);
+ if(fgets(line+len,max_line_len-len,input) == NULL)
+ break;
+ }
+ return line;
+}
+
+void exit_input_error(int line_num)
+{
+ printf("Wrong input format at line %d\n", line_num);
+ exit(1);
+}
+
+void predict(FILE *input, FILE *output)
+{
+ int correct = 0;
+ int total = 0;
+ double error = 0;
+ double sump = 0, sumt = 0, sumpp = 0, sumtt = 0, sumpt = 0;
+
+ int svm_type=svm_get_svm_type(model);
+ int nr_class=svm_get_nr_class(model);
+ double *prob_estimates=NULL;
+ int j;
+
+ if(predict_probability)
+ {
+ if (svm_type==NU_SVR || svm_type==EPSILON_SVR)
+ printf("Prob. model for test data: target value = predicted value + z,\nz: Laplace distribution e^(-|z|/sigma)/(2sigma),sigma=%g\n",svm_get_svr_probability(model));
+ else
+ {
+ int *labels=(int *) malloc(nr_class*sizeof(int));
+ svm_get_labels(model,labels);
+ prob_estimates = (double *) malloc(nr_class*sizeof(double));
+ fprintf(output,"labels");
+ for(j=0;j<nr_class;j++)
+ fprintf(output," %d",labels[j]);
+ fprintf(output,"\n");
+ free(labels);
+ }
+ }
+
+ max_line_len = 1024;
+ line = (char *)malloc(max_line_len*sizeof(char));
+ while(readline(input) != NULL)
+ {
+ int i = 0;
+ double target_label, predict_label;
+ char *idx, *val, *label, *endptr;
+ int inst_max_index = -1; // strtol gives 0 if wrong format, and precomputed kernel has <index> start from 0
+
+ label = strtok(line," \t");
+ target_label = strtod(label,&endptr);
+ if(endptr == label)
+ exit_input_error(total+1);
+
+ while(1)
+ {
+ if(i>=max_nr_attr-1) // need one more for index = -1
+ {
+ max_nr_attr *= 2;
+ x = (struct svm_node *) realloc(x,max_nr_attr*sizeof(struct svm_node));
+ }
+
+ idx = strtok(NULL,":");
+ val = strtok(NULL," \t");
+
+ if(val == NULL)
+ break;
+ errno = 0;
+ x[i].index = (int) strtol(idx,&endptr,10);
+ if(endptr == idx || errno != 0 || *endptr != '\0' || x[i].index <= inst_max_index)
+ exit_input_error(total+1);
+ else
+ inst_max_index = x[i].index;
+
+ errno = 0;
+ x[i].value = strtod(val,&endptr);
+ if(endptr == val || errno != 0 || (*endptr != '\0' && !isspace(*endptr)))
+ exit_input_error(total+1);
+
+ ++i;
+ }
+ x[i].index = -1;
+
+ if (predict_probability && (svm_type==C_SVC || svm_type==NU_SVC))
+ {
+ predict_label = svm_predict_probability(model,x,prob_estimates);
+ fprintf(output,"%g",predict_label);
+ for(j=0;j<nr_class;j++)
+ fprintf(output," %g",prob_estimates[j]);
+ fprintf(output,"\n");
+ }
+ else
+ {
+ predict_label = svm_predict(model,x);
+ fprintf(output,"%g\n",predict_label);
+ }
+ printf("predicted:%g\r\n",predict_label);
+ if(predict_label == target_label)
+ ++correct;
+ error += (predict_label-target_label)*(predict_label-target_label);
+ sump += predict_label;
+ sumt += target_label;
+ sumpp += predict_label*predict_label;
+ sumtt += target_label*target_label;
+ sumpt += predict_label*target_label;
+ ++total;
+ }
+ if (svm_type==NU_SVR || svm_type==EPSILON_SVR)
+ {
+ printf("Mean squared error = %g (regression)\n",error/total);
+ printf("Squared correlation coefficient = %g (regression)\n",
+ ((total*sumpt-sump*sumt)*(total*sumpt-sump*sumt))/
+ ((total*sumpp-sump*sump)*(total*sumtt-sumt*sumt))
+ );
+ }
+ else
+ printf("Accuracy = %g%% (%d/%d) (classification)\n",
+ (double)correct/total*100,correct,total);
+ if(predict_probability)
+ free(prob_estimates);
+}
+
+void exit_with_help()
+{
+ printf(
+ "Usage: svm-predict [options] test_file model_file output_file\n"
+ "options:\n"
+ "-b probability_estimates: whether to predict probability estimates, 0 or 1 (default 0); for one-class SVM only 0 is supported\n"
+ );
+ exit(1);
+}
+
+int main_(void)
+{
+ FILE *input, *output;
+ int i;
+
+ //printf("*in main_\r\n");
+ /*// parse options
+ for(i=1;i<argc;i++)
+ {
+ if(argv[i][0] != '-') break;
+ ++i;
+ switch(argv[i-1][1])
+ {
+ case 'b':
+ predict_probability = atoi(argv[i]);
+ break;
+ default:
+ // fprintf(stderr,"Unknown option: -%c\n", argv[i-1][1]);
+ printf("Unknown option: -%c\n", argv[i-1][1]);
+ exit_with_help();
+ }
+ }
+ if(i>=argc-2)
+ exit_with_help();
+ */
+ //printf("in main_\r\n");
+ input = fopen("/local/test.txt","r");
+ if(input == NULL)
+ {
+ // fprintf(stderr,"can't open input file %s\n",argv[i]);
+ printf("can't open input file %s\n","/local/test.txt");
+ exit(1);
+ }
+ //printf("in main_\r\n");
+ output = fopen("/local/output.txt","w");
+ if(output == NULL)
+ {
+ // fprintf(stderr,"can't open output file %s\n",argv[i+2]);
+ printf("can't open output file %s\n","/local/output.txt");
+ exit(1);
+ }
+ //printf("in main_\r\n");
+ if((model=svm_load_model("/local/model.txt"))==0)
+ {
+ // fprintf(stderr,"can't open model file %s\n",argv[i+1]);
+ printf("can't open model file %s\n","/local/model.txt");
+ exit(1);
+ }
+
+ //printf("in main_\r\n");
+ x = (struct svm_node *) malloc(max_nr_attr*sizeof(struct svm_node));
+ if(predict_probability)
+ {
+ if(svm_check_probability_model(model)==0)
+ {
+ printf("Model does not support probabiliy estimates\n");
+ exit(1);
+ }
+ }
+ else
+ {
+ if(svm_check_probability_model(model)!=0)
+ printf("Model supports probability estimates, but disabled in prediction.\n");
+ }
+ //printf("in main_\r\n");
+ predict(input,output);
+//printf("in main_\r\n");
+ svm_free_and_destroy_model(&model);
+//printf("in main_\r\n");
+ free(x);
+ free(line);
+ fclose(input);
+ fclose(output);
+ return 0;
+}