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allow multiple detectors

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marina.kolpakova 2013-01-21 15:53:25 +04:00
parent 469eeea370
commit 11f3927c58
2 changed files with 48 additions and 43 deletions
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72
apps/sft/misk/roc_test.py
View File

@ -7,6 +7,8 @@ import sys, os, os.path, glob, math, cv2
from datetime import datetime
import numpy
plot_colors = ['b', 'r', 'g', 'c', 'm']
# "key" : ( b, g, r)
bgr = { "red" : ( 0, 0, 255),
"green" : ( 0, 255, 0),
@ -19,7 +21,7 @@ if __name__ == "__main__":
parser = argparse.ArgumentParser(description = 'Plot ROC curve using Caltech mathod of per image detection performance estimation.')
# positional
parser.add_argument("cascade", help = "Path to the tested detector.")
parser.add_argument("cascade", help = "Path to the tested detector.", nargs='+')
parser.add_argument("input", help = "Image sequence pattern.")
parser.add_argument("annotations", help = "Path to the annotations.")
@ -34,47 +36,53 @@ if __name__ == "__main__":
args = parser.parse_args()
# parse annotations
print args.cascade
# # parse annotations
sft.initPlot()
samples = call_parser(args.anttn_format, args.annotations)
cascade = sft.cascade(args.min_scale, args.max_scale, args.nscales, args.cascade)
pattern = args.input
camera = cv2.VideoCapture(pattern)
for idx, each in enumerate(args.cascade):
print each
cascade = sft.cascade(args.min_scale, args.max_scale, args.nscales, each)
pattern = args.input
camera = cv2.VideoCapture(pattern)
# for plotting over dataset
nannotated = 0
nframes = 0
# for plotting over dataset
nannotated = 0
nframes = 0
confidenses = []
tp = []
confidenses = []
tp = []
while True:
ret, img = camera.read()
if not ret:
break;
while True:
ret, img = camera.read()
if not ret:
break;
name = pattern % (nframes,)
_, tail = os.path.split(name)
name = pattern % (nframes,)
_, tail = os.path.split(name)
boxes = samples[tail]
boxes = sft.norm_acpect_ratio(boxes, 0.5)
boxes = samples[tail]
boxes = sft.norm_acpect_ratio(boxes, 0.5)
nannotated = nannotated + len(boxes)
nframes = nframes + 1
rects, confs = cascade.detect(img, rois = None)
nannotated = nannotated + len(boxes)
nframes = nframes + 1
rects, confs = cascade.detect(img, rois = None)
if confs is None:
continue
if confs is None:
continue
dts = sft.convert2detections(rects, confs)
dts = sft.convert2detections(rects, confs)
confs = confs.tolist()[0]
confs.sort(lambda x, y : -1 if (x - y) > 0 else 1)
confidenses = confidenses + confs
confs = confs.tolist()[0]
confs.sort(lambda x, y : -1 if (x - y) > 0 else 1)
confidenses = confidenses + confs
matched = sft.match(boxes, dts)
tp = tp + matched
matched = sft.match(boxes, dts)
tp = tp + matched
print nframes, nannotated
print nframes, nannotated
fppi, miss_rate = sft.computeROC(confidenses, tp, nannotated, nframes)
sft.plotLogLog(fppi, miss_rate)
fppi, miss_rate = sft.computeROC(confidenses, tp, nannotated, nframes)
sft.plotLogLog(fppi, miss_rate, plot_colors[idx])
sft.showPlot("roc_curve.png")

19
apps/sft/misk/sft.py
View File

@ -55,7 +55,7 @@ def crop_rect(rect, factor):
#
def plotLogLog(fppi, miss_rate):
def initPlot():
fig, ax = plt.subplots()
fig.canvas.draw()
@ -63,22 +63,19 @@ def plotLogLog(fppi, miss_rate):
plt.xlabel("fppi")
plt.ylabel("miss rate")
plt.title("ROC curve Bahnhof")
# plt.yticks( [0.05, 0.10, 0.20, 0.30, 0.40, 0.50, 0.64, 0.80])
# ylabels = [item.get_text() for item in ax.get_yticklabels()]
# ax.set_yticklabels( ylabels )
plt.grid(True)
# plt.xticks( [pow(10, -4), pow(10, -3), pow(10, -2), pow(10, -1), pow(10, 0), pow(10, 1)])
# xlabels = [item.get_text() for item in ax.get_xticklabels()]
# ax.set_xticklabels( xlabels )
plt.xscale('log')
plt.yscale('log')
plt.semilogy(fppi, miss_rate, color='m', linewidth=2)
def showPlot(name):
plt.savefig(name)
plt.show()
def plotLogLog(fppi, miss_rate, c):
plt.semilogy(fppi, miss_rate, color = c, linewidth = 2)
def draw_rects(img, rects, color, l = lambda x, y : x + y):
if rects is not None:
for x1, y1, x2, y2 in rects: