Example #1
0
def plot(arg, main=False):
    global i
    f = open(arg, "r")
    points = cPickle.load(f)
    f.close()
    label = arg
    if label.find(".") != -1:
        label = label[:label.rfind(".")]
    if label.find("/") != -1:
        label = label[label.rfind("/") + 1:]
    color = colors[i % 6]
    width = 2
    #    if main == True:
    if label == "ConvNet-MRC-Unsup":
        style = "-"
        color = "r"
        width = 3
        i -= 1
    elif label == "ConvNet-MRC-Random":
        style = "--"
        color = "r"
        width = 3
        i -= 1
    elif label == "ConvNet-Unsup":
        style = "-"
        color = '#00FF00'
        width = 3
        i -= 1
    elif label == "ConvNet-Random":
        style = "--"
        color = '#00FF00'
        width = 3
        i -= 1
    elif i < n_colors:
        style = "-"
    elif i < 2 * n_colors:
        style = "--"
    elif i < 3 * n_colors:
        style = ":"
    else:
        style = "-."
    i += 1
    index = i  # index of this curve

    ############################################################################
    # compute this curve's AUC score

    # score: area under curve between x0 and x1
    # find minimum and maximum x in points
    x0 = 0
    y0 = 1
    x1 = 1
    score = measures.auc_percent(points, x0, y0, x1)
    print "area under curve for x between " + str(x0) + " and " + str(x1) \
        + " AUC" + str(x0) + "_" + str(x1) + "=" + str(score) + "%"

    curves_auc.append([
        score, index, [a[0] for a in points], [-a[1] for a in points], style,
        color, label + " (%.2f%%)" % score, width
    ])
    global auc_title
    auc_title = "Area Under Curve [" + str(x0) + ', ' + str(x1) + '] FPPI'

    ############################################################################
    # compute this curve's score, with y for a particular x

    # find y for x=val
    val = 1
    y = 0
    x1 = 0
    x2 = 0
    y1 = 0
    y2 = 0
    for a in points:
        x2 = x1
        y2 = y1
        x1 = a[0]
        y1 = -a[1]
        if (x1 > 1 and x2 <= 1):  # interpolate
            y = y2 + (y1 - y2) * (val - x2) / (x1 - x2)
    if (x1 <= 1 and x2 <= 1):
        y = y1
    y = y * 100  # use percentage
    score = y

    curves.append([
        score, index, [a[0] for a in points], [-a[1] for a in points], style,
        color, label + " (%.2f%%)" % score, width
    ])
Example #2
0
def print_DET(multi_result, n_imgs, save_filename = None, show_curve = True,
              xmin = None, ymin = None, xmax = None, ymax = None,
              grid_major = False, grid_minor = False):
    print "Printing DET curve with xmin: " + str(xmin) + " xmax: " + str(xmax) \
        + " ymin: " + str(ymin) + " ymax: " + str(ymax)
    points = []
    n_imgs = float(n_imgs)
    # each result is defined for a given threshold
    for result in multi_result:
        tp = float(result.n_true_positives())
        fp = float(result.n_false_positives())
        fn = float(result.n_false_negatives())
        #n_imgs = float(len(result.images))
        #the "-" is a trick for sorting
        points.append((max(xmin, fp / n_imgs), - fn / (tp + fn)))
    points.sort()
    # interpolate value at 100FPPI
    y = 100 * interpolate(100.0, 0, 1, 1000, 10000, points)
    print "miss rate at 100FPPI=" + "%.2f%%"%y
    # interpolate value at 10FPPI
    y = 100 * interpolate(10.0, 0, 1, 1000, 10000, points)
    print "miss rate at 10FPPI=" + "%.2f%%"%y
    # interpolate value at 1FPPI
    y = 100 * interpolate(1.0, 0, 1, 1000, 10000, points)
    print "miss rate at 1FPPI=" + "%.2f%%"%y
    # interpolate value at .001FPPI
    y = 100 * interpolate(.01, 0, 1, 1000, 10000, points)
    print "miss rate at .01FPPI=" + "%.2f%%"%y
    # get area under curve percentage in 0-100
    x0 = 0
    y0 = 1
    x1 = 100
    auc = measures.auc_percent(points, x0, y0, x1);
    print "area under curve in range [" + str(x0) + ", " + str(x1) + "]: " \
        + "AUC" + str(x0) + "-" + str(x1) + "=" + str(auc) + "%"
    # get area under curve percentage in 0-10
    x0 = 0
    y0 = 1
    x1 = 10
    auc = measures.auc_percent(points, x0, y0, x1);
    print "area under curve in range [" + str(x0) + ", " + str(x1) + "]: " \
        + "AUC" + str(x0) + "-" + str(x1) + "=" + str(auc) + "%"
    # get area under curve percentage in 0-1
    x0 = 0
    y0 = 1
    x1 = 1
    auc = measures.auc_percent(points, x0, y0, x1);
    print "area under curve in range [" + str(x0) + ", " + str(x1) + "]: " \
        + "AUC" + str(x0) + "-" + str(x1) + "=" + str(auc) + "%"
#     # get total area under curve
#     auc = measures.auc_percent(points, x0, y0, x1);
#     print "area under curve in range [" + str(x0) + ", " + str(x1) + "]: " \
#         + "AUC" + str(x0) + "-" + str(x1) + "=" + str(auc) + "%"    
    # save curve
    if save_filename != None:
        f = open(save_filename, "w")
        cPickle.dump(points, f)
        f.close()
    #TODO : params
    if show_curve:
        pylab.loglog([a[0] for a in points], [- a[1] for a in points])
        if xmin != None:
            pylab.axis(xmin = xmin)
        if xmax != None:
            pylab.axis(xmax = xmax)
        if ymin != None:
            pylab.axis(ymin = ymin)
        if ymax != None:
            pylab.axis(ymax = ymax)
        pylab.xlabel("False positives per image (FPPI)")
        pylab.ylabel("Miss rate")
        if grid_major:
            pylab.grid(True, which='major')
        if grid_minor:
            pylab.grid(True, which='minor')
        pylab.show()
Example #3
0
def plot(arg, main = False):
    global i
    f = open(arg, "r")
    points = cPickle.load(f)
    f.close()
    label = arg
    if label.find(".") != -1:
        label = label[:label.rfind(".")]
    if label.find("/") != -1:
        label = label[label.rfind("/")+1:]
    color = colors[i%6]
    width = 2
#    if main == True:
    if label == "ConvNet-MRC-Unsup":
        style = "-"
        color = "r"
        width = 3
        i -= 1
    elif label == "ConvNet-MRC-Random":
        style = "--"
        color = "r"
        width = 3
        i -= 1
    elif label == "ConvNet-Unsup":
        style = "-"
        color = '#00FF00'
        width = 3
        i -= 1
    elif label == "ConvNet-Random":
        style = "--"
        color = '#00FF00'
        width = 3
        i -= 1
    elif i < n_colors:
        style = "-"
    elif i < 2*n_colors:
        style = "--"
    elif i < 3*n_colors:
        style = ":"
    else:
        style = "-."
    i += 1
    index = i # index of this curve

    ############################################################################
    # compute this curve's AUC score

    # score: area under curve between x0 and x1
    # find minimum and maximum x in points
    x0 = 0
    y0 = 1
    x1 = 1
    score = measures.auc_percent(points, x0, y0, x1)
    print "area under curve for x between " + str(x0) + " and " + str(x1) \
        + " AUC" + str(x0) + "_" + str(x1) + "=" + str(score) + "%"
        
    curves_auc.append([score, index, [a[0] for a in points],
                       [- a[1] for a in points],
                       style, color, label + " (%.2f%%)"%score, width])
    global auc_title
    auc_title = "Area Under Curve [" + str(x0) + ', ' + str(x1) + '] FPPI'

    
    ############################################################################
    # compute this curve's score, with y for a particular x

    # find y for x=val
    val = 1
    y = 0
    x1 = 0
    x2 = 0
    y1 = 0
    y2 = 0
    for a in points:
        x2 = x1
        y2 = y1
        x1 = a[0]
        y1 = -a[1]
        if (x1 > 1 and x2 <= 1): # interpolate
            y = y2 + (y1 - y2) * (val - x2) / (x1 - x2)
    if (x1 <= 1 and x2 <= 1):
        y = y1
    y = y * 100 # use percentage
    score = y
    
    curves.append([score, index, [a[0] for a in points],
                   [- a[1] for a in points],
                   style, color, label + " (%.2f%%)"%score, width])
Example #4
0
def print_DET(multi_result,
              n_imgs,
              save_filename=None,
              show_curve=True,
              xmin=None,
              ymin=None,
              xmax=None,
              ymax=None,
              grid_major=False,
              grid_minor=False):
    print "Printing DET curve with xmin: " + str(xmin) + " xmax: " + str(xmax) \
        + " ymin: " + str(ymin) + " ymax: " + str(ymax)
    points = []
    n_imgs = float(n_imgs)
    # each result is defined for a given threshold
    for result in multi_result:
        tp = float(result.n_true_positives())
        fp = float(result.n_false_positives())
        fn = float(result.n_false_negatives())
        #n_imgs = float(len(result.images))
        #the "-" is a trick for sorting
        points.append((max(xmin, fp / n_imgs), -fn / (tp + fn)))
    points.sort()
    # interpolate value at 100FPPI
    y = 100 * interpolate(100.0, 0, 1, 1000, 10000, points)
    print "miss rate at 100FPPI=" + "%.2f%%" % y
    # interpolate value at 10FPPI
    y = 100 * interpolate(10.0, 0, 1, 1000, 10000, points)
    print "miss rate at 10FPPI=" + "%.2f%%" % y
    # interpolate value at 1FPPI
    y = 100 * interpolate(1.0, 0, 1, 1000, 10000, points)
    print "miss rate at 1FPPI=" + "%.2f%%" % y
    # interpolate value at .001FPPI
    y = 100 * interpolate(.01, 0, 1, 1000, 10000, points)
    print "miss rate at .01FPPI=" + "%.2f%%" % y
    # get area under curve percentage in 0-100
    x0 = 0
    y0 = 1
    x1 = 100
    auc = measures.auc_percent(points, x0, y0, x1)
    print "area under curve in range [" + str(x0) + ", " + str(x1) + "]: " \
        + "AUC" + str(x0) + "-" + str(x1) + "=" + str(auc) + "%"
    # get area under curve percentage in 0-10
    x0 = 0
    y0 = 1
    x1 = 10
    auc = measures.auc_percent(points, x0, y0, x1)
    print "area under curve in range [" + str(x0) + ", " + str(x1) + "]: " \
        + "AUC" + str(x0) + "-" + str(x1) + "=" + str(auc) + "%"
    # get area under curve percentage in 0-1
    x0 = 0
    y0 = 1
    x1 = 1
    auc = measures.auc_percent(points, x0, y0, x1)
    print "area under curve in range [" + str(x0) + ", " + str(x1) + "]: " \
        + "AUC" + str(x0) + "-" + str(x1) + "=" + str(auc) + "%"
    #     # get total area under curve
    #     auc = measures.auc_percent(points, x0, y0, x1);
    #     print "area under curve in range [" + str(x0) + ", " + str(x1) + "]: " \
    #         + "AUC" + str(x0) + "-" + str(x1) + "=" + str(auc) + "%"
    # save curve
    if save_filename != None:
        f = open(save_filename, "w")
        cPickle.dump(points, f)
        f.close()
    #TODO : params
    if show_curve:
        pylab.loglog([a[0] for a in points], [-a[1] for a in points])
        if xmin != None:
            pylab.axis(xmin=xmin)
        if xmax != None:
            pylab.axis(xmax=xmax)
        if ymin != None:
            pylab.axis(ymin=ymin)
        if ymax != None:
            pylab.axis(ymax=ymax)
        pylab.xlabel("False positives per image (FPPI)")
        pylab.ylabel("Miss rate")
        if grid_major:
            pylab.grid(True, which='major')
        if grid_minor:
            pylab.grid(True, which='minor')
        pylab.show()