dump(codebook, f, protocol=HIGHEST_PROTOCOL)
print "---------------------"
print "## compute the visual words histograms for each image"
all_word_histgrams = {}
for imagefname in all_features:
word_histgram = computeHistograms(codebook, all_features[imagefname])
all_word_histgrams[imagefname] = word_histgram
print "---------------------"
print "## write the histograms to file to pass it to the svm"
writeHistogramsToFile(nclusters,
all_files_labels,
all_files,
all_word_histgrams,
datasetpath + HISTOGRAMS_FILE)
print "---------------------"
print "## train svm"
c, g, rate, model_file = libsvm.grid(datasetpath + HISTOGRAMS_FILE,
png_filename='grid_res_img_file.png')
print "--------------------"
print "## outputting results"
print "model file: " + datasetpath + model_file
print "codebook file: " + datasetpath + CODEBOOK_FILE
print "category ==> label"
for cat in cat_label:
print '{0:13} ==> {1:6d}'.format(cat, cat_label[cat])
thresh=K_THRESH)
with open(datasetpath + CODEBOOK_FILE, 'wb') as f:
dump(codebook, f, protocol=HIGHEST_PROTOCOL)
print "---------------------"
print "## compute the visual words histograms for each image"
all_word_histgrams = {}
for imagefname in all_features:
word_histgram = computeHistograms(codebook, all_features[imagefname])
all_word_histgrams[imagefname] = word_histgram
print "---------------------"
print "## write the histograms to file to pass it to the svm"
writeHistogramsToFile(nclusters, all_files_labels, all_files,
all_word_histgrams, datasetpath + HISTOGRAMS_FILE)
print "---------------------"
print "## train svm"
c, g, rate, model_file = libsvm.grid(datasetpath + HISTOGRAMS_FILE,
png_filename='grid_res_img_file.png')
print "--------------------"
print "## outputting results"
print "model file: " + datasetpath + model_file
print "codebook file: " + datasetpath + CODEBOOK_FILE
print "category ==> label"
for cat in cat_label:
print '{0:13} ==> {1:6d}'.format(cat, cat_label[cat])
