folder_output = "/home/prassanna/Development/workspace/CamVid_scripts/FrameworkDump3/crf/"
fh, filenames_ext = listFiles(folder_energy, ext_energy)
filenames = [f.replace(ext_energy, "") for f in filenames_ext]
for i in range(0, len(filenames)):
print i, "->", filenames[i]
print "Loading all files..."
energies = ocv.read_xml_file(folder_energy + filenames[i] + ext_energy,
"prob")
segments = ocv.read_xml_file(
folder_superpixels + filenames[i] + ext_superpixels, "Segments")
nbrs = ocv.read_xml_file(folder_superpixels + filenames[i] + ext_nbr,
"Neighbours")
ann = ocv.read_xml_file(folder_superpixels + filenames[i] + ext_ann, "Ann")
gt_labels = annImagetoLabels(ann, segments)
print "Necessary Transformations..."
edge_list, edge_features = SuperpixelAdjacency.convertToAdjacencyListPotts(
nbrs, segments, gt_labels)
#edge_features.shape=len(edge_features),1
x = (energies, edge_list, edge_features)
print "Inference...."
predlabelList = crf.inference(x, ssvm.w, relaxed=True)
print "Final Operations..."
predAnn = predLabelsToAnnIndex(segments, predlabelList)
predImage = labelsToImage(label_list, predAnn, True)
ocv.write_xml_file(folder_output + filenames[i] + ext_out_ann, "Ann",
predAnn)
cv2.imwrite(folder_output + filenames[i] + ext_out_image, predImage)
#gt_global = list();
#desc_global = list();
#cv2.namedWindow("Original");
#cv2.namedWindow("Predicted");
for i in range(0, len(filenames_sup)):
print i, "->", filenames_sup[i]
segments = ocv.read_xml_file(folder_location + filenames_sup[i],
"Segments")
desc = ocv.read_xml_file(folder_location + filenames_desc[i],
"Descriptors")
#ann = ocv.read_xml_file(folder_location+filenames_ann[i], "Ann")
print "Transforming.."
desc = imp.transform(desc)
print "Predicting.."
for k in range(0, len(clfs)):
clf = clfs[k]
folder_out = folder_outs[k]
pred_labels = clf.predict(desc)
predAnn = predLabelsToAnnIndex(segments, pred_labels)
#annImage = labelsToImage(dataset_colours, ann);
predImage = labelsToImage(dataset_colours, predAnn)
#cv2.imshow("Original", annImage);
#cv2.imshow("Predicted", predImage);
ocv.write_xml_file(folder_out + filenames_out[i] + ".xml", "Ann",
predAnn)
cv2.imwrite(folder_out + filenames_out[i], predImage)
#cv2.waitKey(0)
#cv2.destroyAllWindows();
folder_location = "/home/prassanna/Development/workspace/CamVid_scripts/FrameworkDump4/Train/"
#Getting filenames for Random Forests
filenames, filenames_desc = listFiles(folder_location, ext_desc)
filenames_sup = [
filename.replace(ext_desc, ext_sup) for filename in filenames_desc
]
filenames_ann = [
filename.replace(ext_desc, ext_ann) for filename in filenames_desc
]
filename_extless = [
filename.replace(ext_desc, "") for filename in filenames_desc
]
gt_global = list()
desc_global = list()
for i in range(0, 1): #len(filenames_sup)):
print i, "->", filenames_sup[i]
for j in range(0, len(clfs)):
print "On classifier : ", j
desc = ocv.read_xml_file(folder_location + filenames_desc[i],
"Descriptors")
desc = imp.transform(desc)
pred = clfs[j].predict_log_proba(desc)
#predEnergy = clf.predict_log_proba(desc);
ocv.write_xml_file(folder_out[j] + filename_extless[i] + "_prob.xml",
"prob", pred)
#ocv.write_xml_file(folder_out+filenames_extless[i]+"_energy.xml", "energy", predEnergy)