Bienqq
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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-12-15 12:43:30 -08:00
parent 03b5408e70
commit d884c33d21
4 changed files with 6 additions and 5 deletions
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0
data/coco.data → data/coco2017.data
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2
detect.py
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@ -155,7 +155,7 @@ def detect(save_txt=False, save_img=False):
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
parser.add_argument('--data', type=str, default='data/coco.data', help='coco.data file path')
parser.add_argument('--data', type=str, default='data/coco2017.data', help='*.data file path')
parser.add_argument('--weights', type=str, default='weights/yolov3-spp.weights', help='path to weights file')
parser.add_argument('--source', type=str, default='data/samples', help='source') # input file/folder, 0 for webcam
parser.add_argument('--output', type=str, default='output', help='output folder') # output folder

4
test.py
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@ -204,7 +204,7 @@ def test(cfg,
if __name__ == '__main__':
parser = argparse.ArgumentParser(prog='test.py')
parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
parser.add_argument('--data', type=str, default='data/coco.data', help='coco.data file path')
parser.add_argument('--data', type=str, default='data/coco2017.data', help='*.data file path')
parser.add_argument('--weights', type=str, default='weights/yolov3-spp.weights', help='path to weights file')
parser.add_argument('--batch-size', type=int, default=16, help='size of each image batch')
parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
@ -225,4 +225,4 @@ if __name__ == '__main__':
opt.iou_thres,
opt.conf_thres,
opt.nms_thres,
opt.save_json or (opt.data == 'data/coco.data'))
opt.save_json or any([x in opt.data for x in ['coco.data', 'coco2014.data', 'coco2017.data']]))

5
train.py
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@ -324,13 +324,14 @@ def train():
print_model_biases(model)
elif not opt.notest or final_epoch: # Calculate mAP
with torch.no_grad():
is_coco = any([x in data for x in ['coco.data', 'coco2014.data', 'coco2017.data']]) and model.nc == 80
results, maps = test.test(cfg,
data,
batch_size=batch_size,
img_size=opt.img_size,
model=model,
conf_thres=0.001 if final_epoch else 0.1, # 0.1 for speed
save_json=final_epoch and 'coco.data' in data and model.nc == 80,
save_json=final_epoch and is_coco,
dataloader=testloader)
# Write epoch results
@ -419,7 +420,7 @@ if __name__ == '__main__':
parser.add_argument('--batch-size', type=int, default=16) # effective bs = batch_size * accumulate = 16 * 4 = 64
parser.add_argument('--accumulate', type=int, default=4, help='batches to accumulate before optimizing')
parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
parser.add_argument('--data', type=str, default='data/coco.data', help='*.data file path')
parser.add_argument('--data', type=str, default='data/coco2017.data', help='*.data file path')
parser.add_argument('--multi-scale', action='store_true', help='adjust (67% - 150%) img_size every 10 batches')
parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
parser.add_argument('--rect', action='store_true', help='rectangular training')