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71 lines
2.5 KiB
Python
Executable File
71 lines
2.5 KiB
Python
Executable File
#!/usr/bin/env python
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import argparse
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import sft
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import sys, os, os.path, glob, math, cv2
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from datetime import datetime
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import numpy
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def call_parser(f, a):
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return eval( "sft.parse_" + f + "('" + a + "')")
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description = 'Plot ROC curve using Caltech mathod of per image detection performance estimation.')
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# positional
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parser.add_argument("cascade", help = "Path to the tested detector.")
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parser.add_argument("input", help = "Image sequence pattern.")
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parser.add_argument("annotations", help = "Path to the annotations.")
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# optional
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parser.add_argument("-m", "--min_scale", dest = "min_scale", type = float, metavar= "fl", help = "Minimum scale to be tested.", default = 0.4)
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parser.add_argument("-M", "--max_scale", dest = "max_scale", type = float, metavar= "fl", help = "Maximum scale to be tested.", default = 5.0)
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parser.add_argument("-o", "--output", dest = "output", type = str, metavar= "path", help = "Path to store resultiong image.", default = "./roc.png")
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parser.add_argument("-n", "--nscales", dest = "nscales", type = int, metavar= "n", help = "Prefered count of scales from min to max.", default = 55)
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# required
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parser.add_argument("-f", "--anttn-format", dest = "anttn_format", choices = ['inria', 'caltech', "idl"], help = "Annotation file for test sequence.", required = True)
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args = parser.parse_args()
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samples = call_parser(args.anttn_format, args.annotations)
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# where we use nms cv::SCascade::DOLLAR == 2
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cascade = cv2.SCascade(args.min_scale, args.max_scale, args.nscales, 2)
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xml = cv2.FileStorage(args.cascade, 0)
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dom = xml.getFirstTopLevelNode()
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assert cascade.load(dom)
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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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break;
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name = pattern % (frame,)
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qq = pattern.format(frame)
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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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dt_old = sft.match(boxes, rects, confs)
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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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break;
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# sft.plot_curve() |