示例#1
0
            dump(dataRowsTestValid[0:10],f)
        print "Finished dumping to testSetMini.pickle"
        
        
    if 'testSetHD5' in STEPS:
        writeHD5(dataRowsTestValid, ROOT+'/caffeData/hd5/test.hd5', ROOT+'/caffeData/test.txt', MEAN_TRAIN_SET, STD_TRAIN_SET)
        print "Finished writing test to caffeData/test.txt"

 
DEBUG = True
if 'testErrorMini' in STEPS:
    with open('testSetMini.pickle','r') as f:
        dataRowsTrainValid = load(f)
        
    testErrorMini=ErrorAcum()
    predictor = Predictor(protoTXTPath=PATH_TO_DEPLOY_TXT, weightsPath=PATH_TO_WEIGHTS)
    for i, dataRow in enumerate(dataRowsTrainValid):
        dataRow40 = dataRow.copyCroppedByBBox(dataRow.fbbox).copyMirrored()
        image, lm_0_5 = predictor.preprocess(dataRow40.image, dataRow40.landmarks())
        prediction = predictor.predict(image)
        testErrorMini.add(lm_0_5, prediction)
        dataRow40.prediction = (prediction+0.5)*40.  # Scale -0.5..+0.5 to 0..40
        
        if DEBUG:
            dataRow.prediction = dataRow40.inverseScaleAndOffset(dataRow40.prediction) # Scale up to the original image scale
            dataRow.show()
            if i>40:
                print "Debug breaked after %d rows:" % i
            

    print "Test Error mini:", testErrorMini
示例#2
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###########################    STEPS TO RUN       ####################
STEPS = ['testErro']

##########################################    SCRIPT STEPS       ##################################################

if 'testErro' in STEPS:
    print "Loading image set....."
    dataRowsTest_CSV  = createDataRowsFromCSV(CSV_TEST , DataRow.DataRowFromNameBoxInterlaved_68, DATA_PATH)
    print "Finished reading %d rows from image" % len(dataRowsTest_CSV)
    dataRowsTestValid,R = getValidWithBBox_68(dataRowsTest_CSV)
    print "Original image:",len(dataRowsTest_CSV), "Valid Rows:", len(dataRowsTestValid), " noFacesAtAll", R.noFacesAtAll, " outside:", R.outsideLandmarks, " couldNotMatch:", R.couldNotMatch

    # Best models - yubing 20160718
    ROOT_DEPLOY_TXT = '/data/b0216.yu/LD_Train/68Data/Models60/vanilla_deploy_60x60.prototxt'
    ROOT_MODEL = '/data/b0216.yu/LD_Train/68Data/Models60/LD_usc_iter_90000.caffemodel'
    root_predictor = Predictor(protoTXTPath=ROOT_DEPLOY_TXT, weightsPath=ROOT_MODEL, meanPath=MEAN_TRAIN_SET, stdPath=STD_TRAIN_SET) 
    
    MEAN_TRAIN_LE_BEST = os.path.join('/data/b0216.yu/LD_Train/Parts/Models/LeftEye/', 'MeanFace.png')
    STD_TRAIN_LE_BEST  = os.path.join('/data/b0216.yu/LD_Train/Parts/Models/LeftEye/', 'StdVar.png')

    MEAN_TRAIN_RE_BEST = os.path.join('/data/b0216.yu/LD_Train/Parts/Models/RightEye/', 'MeanFace.png')
    STD_TRAIN_RE_BEST  = os.path.join('/data/b0216.yu/LD_Train/Parts/Models/RightEye/', 'StdVar.png')

    MEAN_TRAIN_Mo_BEST = os.path.join('/data/b0216.yu/LD_Train/Parts/Models/Mouth/', 'MeanFace.png')
    STD_TRAIN_Mo_BEST  = os.path.join('/data/b0216.yu/LD_Train/Parts/Models/Mouth/', 'StdVar.png')

    MEAN_TRAIN_No_BEST = os.path.join('/data/b0216.yu/LD_Train/Parts/Models/Nose/', 'MeanFace.png')
    STD_TRAIN_No_BEST  = os.path.join('/data/b0216.yu/LD_Train/Parts/Models/Nose/', 'StdVar.png') 
    
    MEAN_TRAIN_Co_BEST = os.path.join('/data/b0216.yu/LD_Train/Parts/Models/Contour/', 'MeanFace.png')
    STD_TRAIN_Co_BEST  = os.path.join('/data/b0216.yu/LD_Train/Parts/Models/Contour/', 'StdVar.png')
示例#3
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            if i>40:
                print "Debug breaked after %d rows:" % i
            

    print "Test Error mini:", testErrorMini
'''
   

# Run the same caffe test set using python
DEBUG = False  # Set this to true if you wish to plot the images
if 'testError' in STEPS:
    with open('testSet.pickle','r') as f:
        dataRowsTrainValid = load(f)
        
    testError=ErrorAcum()
    predictor = Predictor(protoTXTPath=PATH_TO_DEPLOY_TXT, weightsPath=PATH_TO_WEIGHTS)
    for i, dataRow in enumerate(dataRowsTrainValid):
        dataRow40 = dataRow.copyCroppedByBBox(dataRow.fbbox)
        image, lm40 = predictor.preprocess(dataRow40.image, dataRow40.landmarks())
        prediction = predictor.predict(image)
        testError.add(lm40, prediction)
        dataRow40.prediction = (prediction+0.5)*40.
        
        if DEBUG and i%40 ==0:
            dataRow.prediction = dataRow40.inverseScaleAndOffset(dataRow40.prediction)
            dataRow.show()
            break
        
            
    print "Test Error:", testError
示例#4
0
sys.path.append(os.path.join('/home/ly/workspace/Vanilla-40', 'python'))  # Assume git root directory

###########################    PATHS TO SET   ####################
# Either define CAFFE_ROOT in your enviroment variables or set it here
CAFFE_ROOT = os.environ.get('CAFFE_ROOT','~/caffe/distribute')
sys.path.append(CAFFE_ROOT+'/python')  # Add caffe python path so we can import it
import caffe

#Import helper functions
from DataRow import DataRow, BBox, Predictor


PATH_TO_WEIGHTS  = os.path.join('/home/ly/workspace/Vanilla-40', 'caffeData', 'snapshots_60_medium_ibug_0.04c_0.04s', 'snap_iter_80000.caffemodel')
#PATH_TO_WEIGHTS  = os.path.join('/home/ly/workspace/Vanilla-40', 'caffeData', 'snapshots-40-unit-cvt1-inner', 'snap_iter_670000.caffemodel')
PATH_TO_DEPLOY_TXT = os.path.join('/home/ly/workspace/Vanilla-40', 'ZOO', 'vanilla_deploy_60_medium.prototxt')
predictor = Predictor(protoTXTPath=PATH_TO_DEPLOY_TXT, weightsPath=PATH_TO_WEIGHTS)

# Make sure dlib python path exists on PYTHONPATH else "pip install dlib" if needed.
import dlib
detector=dlib.get_frontal_face_detector() # Load dlib's face detector


img_path = os.path.join('/home/ly/workspace/Vanilla-40/TestSet','helen_3139620200_1.jpg')


img = cv2.imread(img_path)
#dets = detector( np.array(img, dtype = 'uint8' ), 1)
dets = [[1]]

for det in dets: