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
])
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()
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])
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()
