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https://github.com/opencv/opencv.git
synced 2024-11-24 11:10:21 +08:00
add plotting function (matplotlib required)
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@ -63,5 +63,7 @@ if __name__ == "__main__":
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sft.draw_rects(img, rects[0], (0, 255, 0))
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sft.draw_rects(img, rects[0], (0, 255, 0))
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cv2.imshow("result", img);
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cv2.imshow("result", img);
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if (cv2.waitKey (5) != -1):
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if (cv2.waitKey (0) == 27):
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break;
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break;
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# sft.plot_curve()
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@ -2,33 +2,67 @@
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import cv2, re, glob
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import cv2, re, glob
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import numpy as np
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import numpy as np
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import matplotlib.pyplot as plt
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def plot_curve():
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fig, ax = plt.subplots()
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fig.canvas.draw()
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x = np.linspace(pow(10,-4), pow(10,1), 101)
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y = 1 - x
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plt.semilogy(x,y,color='m',linewidth=2)
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plt.xlabel("fppi")
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plt.ylabel("miss rate")
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plt.title("ROC curve Bahnhof")
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plt.yticks( [0.05, 0.10, 0.20, 0.30, 0.40, 0.50, 0.64, 0.80])
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ylabels = [item.get_text() for item in ax.get_yticklabels()]
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ax.set_yticklabels( ylabels )
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plt.grid(True)
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# plt.xticks( [pow(10, -4), pow(10, -3), pow(10, -2), pow(10, -1), pow(10, 0), pow(10, 0)])
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# xlabels = [item.get_text() for item in ax.get_xticklabels()]
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# ax.set_xticklabels( xlabels )
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plt.xscale('log')
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plt.show()
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def draw_rects(img, rects, color, l = lambda x, y : x + y):
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def draw_rects(img, rects, color, l = lambda x, y : x + y):
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if rects is not None:
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if rects is not None:
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for x1, y1, x2, y2 in rects:
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for x1, y1, x2, y2 in rects:
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cv2.rectangle(img, (x1, y1), (l(x1, x2), l(y1, y2)), color, 2)
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cv2.rectangle(img, (x1, y1), (l(x1, x2), l(y1, y2)), color, 2)
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class Sample:
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class Annotation:
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def __init__(self, bbs, img):
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def __init__(self, bb):
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self.image = img
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self.bb = bb
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self.bbs = bb
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class Detection:
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class Detection:
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def __init__(self, bb, conf):
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def __init__(self, bb, conf):
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self.bb = bb
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self.bb = bb
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self.conf = conf
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self.conf = conf
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self.matched = False
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# def crop(self):
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# rel_scale = self.bb[1] / 128
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# we use rect-stype for dt and box style for gt. ToDo: fix it
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# we use rect-stype for dt and box style for gt. ToDo: fix it
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def overlap(self, b):
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def overlap(self, b):
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a = self.bb
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a = self.bb
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print "HERE:", a, b
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w = min( a[0] + a[2], b[2]) - max(a[0], b[0]);
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w = min( a[0] + a[2], b[0] + b[2]) - max(a[0], b[0]);
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h = min( a[1] + a[3], b[3]) - max(a[1], b[1]);
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h = min( a[1] + a[3], b[1] + b[3]) - max(a[1], b[1]);
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cross_area = 0.0 if (w < 0 or h < 0) else float(w * h)
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cross_area = 0.0 if (w < 0 or h < 0) else float(w * h)
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union_area = (a[2] * a[3]) + ((b[2] - b[0]) * (b[3] - b[1])) - cross_area;
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union_area = (a[2] * a[3]) + ((b[2] - b[0]) * (b[3] - b[1])) - cross_area;
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return cross_area / union_area;
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return cross_area / union_area
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def mark_matched(self):
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self.matched = True
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def parse_inria(ipath, f):
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def parse_inria(ipath, f):
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@ -64,11 +98,37 @@ def match(gts, rects, confs):
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if rects is None:
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if rects is None:
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return 0
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return 0
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fp = 0
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fn = 0
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dts = zip(*[rects.tolist(), confs.tolist()])
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dts = zip(*[rects.tolist(), confs.tolist()])
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dts = zip(dts[0][0], dts[0][1])
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dts = zip(dts[0][0], dts[0][1])
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dts = [Detection(r,c) for r, c in dts]
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dts = [Detection(r,c) for r, c in dts]
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for dt in dts:
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for gt in gts:
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for gt in gts:
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# exclude small
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if gt[2] - gt[0] < 27:
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continue
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matched = False
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for dt in dts:
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# dt.crop()
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overlap = dt.overlap(gt)
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overlap = dt.overlap(gt)
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print overlap
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print dt.bb, "vs", gt, overlap
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if overlap > 0.5:
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dt.mark_matched()
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matched = True
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print "matched ", dt.bb, gt
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if not matched:
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fn = fn + 1
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print "fn", fn
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for dt in dts:
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if not dt.matched:
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fp = fp + 1
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print "fp", fp
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