add cropping and aspect ratio normalization
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18df46fbe9
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d1952f28d9
@ -40,6 +40,7 @@ if __name__ == "__main__":
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frame = 0
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pattern = args.input
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camera = cv2.VideoCapture(args.input)
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while True:
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ret, img = camera.read()
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if not ret:
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@ -50,17 +51,18 @@ if __name__ == "__main__":
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_, tail = os.path.split(name)
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boxes = samples[tail]
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boxes = sft.norm_acpect_ratio(boxes, 0.5)
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if boxes is not None:
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sft.draw_rects(img, boxes, (255, 0, 0), lambda x, y : y)
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frame = frame + 1
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rects, confs = cascade.detect(img, rois = None)
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fp = sft.match(boxes, rects, confs)
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dt_old = sft.match(boxes, rects, confs)
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# # draw results
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if rects is not None:
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sft.draw_rects(img, rects[0], (0, 255, 0))
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if dt_old is not None:
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sft.draw_dt(img, dt_old, (0, 255, 0))
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cv2.imshow("result", img);
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if (cv2.waitKey (0) == 27):
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@ -29,13 +29,25 @@ def plot_curve():
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plt.xscale('log')
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plt.show()
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def crop_rect(rect, factor):
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val_x = factor * float(rect[2])
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val_y = factor * float(rect[3])
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x = [int(rect[0] + val_x), int(rect[1] + val_y), int(rect[2] - 2.0 * val_x), int(rect[3] - 2.0 * val_y)]
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return x
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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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def draw_dt(img, dts, color, l = lambda x, y : x + y):
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if dts is not None:
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for dt in dts:
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bb = dt.bb
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x1, y1, x2, y2 = dt.bb[0], dt.bb[1], dt.bb[2], dt.bb[3]
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cv2.rectangle(img, (x1, y1), (l(x1, x2), l(y1, y2)), color, 2)
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class Annotation:
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def __init__(self, bb):
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self.bb = bb
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@ -49,6 +61,10 @@ class Detection:
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# def crop(self):
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# rel_scale = self.bb[1] / 128
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def crop(self, factor):
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print "was", self.bb
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self.bb = crop_rect(self.bb, factor)
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print "bec", self.bb
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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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@ -94,6 +110,16 @@ def parse_idl(f):
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map.update(eval(l))
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return map
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def norm_box(box, ratio):
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middle = float(box[0] + box[2]) / 2.0
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new_half_width = float(box[3] - box[1]) * ratio / 2.0
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return (int(round(middle - new_half_width)), box[1], int(round(middle + new_half_width)), box[3])
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def norm_acpect_ratio(boxes, ratio):
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return [ norm_box(box, ratio) for box in boxes]
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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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@ -105,6 +131,11 @@ def match(gts, rects, confs):
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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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factor = 1.0 / 8.0
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dt_old = dts
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for dt in dts:
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dt.crop(factor)
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for gt in gts:
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# exclude small
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@ -132,3 +163,4 @@ def match(gts, rects, confs):
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fp = fp + 1
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print "fp", fp
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return dt_old
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