# load dataset loader = DataLoader(dataset, sampleEach) print("Decoding " + str(loader.getNumSamples()) + " samples now.") print("") # metrics calculates CER and WER for dataset m = Metrics(loader.lm.getWordChars()) # write results to csv csv = Utils.CSVWriter() # decode each sample from dataset for (idx, data) in enumerate(loader): # decode matrix res = wordBeamSearch(data.mat, 10, loader.lm, useNGrams) print("Sample: " + str(idx + 1)) print("Filenames: " + data.fn) print('Result: "' + res + '"') print('Ground Truth: "' + data.gt + '"') strEditDist = str(editdistance.eval(res, data.gt)) print("Editdistance: " + strEditDist) # output CER and WER m.addSample(data.gt, res) print("Accumulated CER and WER so far:", "CER:", m.getCER(), "WER:", m.getWER()) print("") # output to csv csv.write([res, data.gt, strEditDist])