(dirName)
| 412 | |
| 413 | |
| 414 | def loadImages(dirName): |
| 415 | from os import listdir |
| 416 | hwLabels = [] |
| 417 | print(dirName) |
| 418 | trainingFileList = listdir(dirName) # load the training set |
| 419 | m = len(trainingFileList) |
| 420 | trainingMat = zeros((m, 1024)) |
| 421 | for i in range(m): |
| 422 | fileNameStr = trainingFileList[i] |
| 423 | fileStr = fileNameStr.split('.')[0] # take off .txt |
| 424 | classNumStr = int(fileStr.split('_')[0]) |
| 425 | if classNumStr == 9: |
| 426 | hwLabels.append(-1) |
| 427 | else: |
| 428 | hwLabels.append(1) |
| 429 | trainingMat[i, :] = img2vector('%s/%s' % (dirName, fileNameStr)) |
| 430 | return trainingMat, hwLabels |
| 431 | |
| 432 | |
| 433 | def testDigits(kTup=('rbf', 10)): |
no test coverage detected