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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-12-24 13:58:45 -08:00
parent 8319011489
commit f7ac56db39
1 changed files with 4 additions and 4 deletions
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8
test.py
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@ -214,13 +214,13 @@ if __name__ == '__main__':
parser.add_argument('--conf-thres', type=float, default=0.001, help='object confidence threshold') parser.add_argument('--conf-thres', type=float, default=0.001, help='object confidence threshold')
parser.add_argument('--nms-thres', type=float, default=0.5, help='iou threshold for non-maximum suppression') parser.add_argument('--nms-thres', type=float, default=0.5, help='iou threshold for non-maximum suppression')
parser.add_argument('--save-json', action='store_true', help='save a cocoapi-compatible JSON results file') parser.add_argument('--save-json', action='store_true', help='save a cocoapi-compatible JSON results file')
parser.add_argument('--task', default='test', help="'test', 'study', 'benchmark'")
parser.add_argument('--device', default='', help='device id (i.e. 0 or 0,1) or cpu') parser.add_argument('--device', default='', help='device id (i.e. 0 or 0,1) or cpu')
opt = parser.parse_args() opt = parser.parse_args()
opt.save_json = opt.save_json or any([x in opt.data for x in ['coco.data', 'coco2014.data', 'coco2017.data']]) opt.save_json = opt.save_json or any([x in opt.data for x in ['coco.data', 'coco2014.data', 'coco2017.data']])
print(opt) print(opt)
task = 'test' # 'test', 'study', 'benchmark' if opt.task == 'test': # task = 'test', 'study', 'benchmark'
if task == 'test':
# Test # Test
test(opt.cfg, test(opt.cfg,
opt.data, opt.data,
@ -231,7 +231,7 @@ if __name__ == '__main__':
opt.nms_thres, opt.nms_thres,
opt.save_json) opt.save_json)
elif task == 'benchmark': elif opt.task == 'benchmark':
# mAPs at 320-608 at conf 0.5 and 0.7 # mAPs at 320-608 at conf 0.5 and 0.7
y = [] y = []
for i in [320, 416, 512, 608]: for i in [320, 416, 512, 608]:
@ -241,7 +241,7 @@ if __name__ == '__main__':
y.append(r + (time.time() - t,)) y.append(r + (time.time() - t,))
np.savetxt('benchmark.txt', y, fmt='%10.4g') # y = np.loadtxt('study.txt') np.savetxt('benchmark.txt', y, fmt='%10.4g') # y = np.loadtxt('study.txt')
elif task == 'study': elif opt.task == 'study':
# Parameter study # Parameter study
y = [] y = []
x = np.arange(0.4, 0.9, 0.05) x = np.arange(0.4, 0.9, 0.05)