Open Source Computer Vision Library
https://opencv.org/
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74 lines
1.9 KiB
74 lines
1.9 KiB
#!/usr/bin/env python |
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import cv2, re, glob |
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import numpy as np |
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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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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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class Sample: |
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def __init__(self, bbs, img): |
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self.image = img |
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self.bbs = bb |
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class Detection: |
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def __init__(self, bb, conf): |
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self.bb = bb |
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self.conf = conf |
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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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a = self.bb |
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print "HERE:", a, b |
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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[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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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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def parse_inria(ipath, f): |
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bbs = [] |
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path = None |
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for l in f: |
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box = None |
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if l.startswith("Bounding box"): |
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b = [x.strip() for x in l.split(":")[1].split("-")] |
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c = [x[1:-1].split(",") for x in b] |
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d = [int(x) for x in sum(c, [])] |
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bbs.append(d) |
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if l.startswith("Image filename"): |
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path = l.split('"')[-2] |
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return Sample(path, bbs) |
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def glob_set(pattern): |
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return [__n for __n in glob.iglob(pattern)] #glob.iglob(pattern) |
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# parse ETH idl file |
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def parse_idl(f): |
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map = {} |
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for l in open(f): |
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l = re.sub(r"^\"left\/", "{\"", l) |
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l = re.sub(r"\:", ":[", l) |
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l = re.sub(r"(\;|\.)$", "]}", l) |
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map.update(eval(l)) |
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return map |
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def match(gts, rects, confs): |
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if rects is None: |
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return 0 |
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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 = [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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overlap = dt.overlap(gt) |
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print overlap |