updates
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@ -25,7 +25,6 @@ parser.add_argument('-img_size', type=int, default=32 * 13, help='size of each i
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opt = parser.parse_args()
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print(opt)
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def detect(opt):
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os.system('rm -rf ' + opt.output_folder)
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os.makedirs(opt.output_folder, exist_ok=True)
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@ -66,8 +65,7 @@ def detect(opt):
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# Get detections
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with torch.no_grad():
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chip = torch.from_numpy(img).unsqueeze(0).to(device)
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pred = model(chip)
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pred = model(torch.from_numpy(img).unsqueeze(0).to(device))
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pred = pred[pred[:, :, 4] > opt.conf_thres]
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if len(pred) > 0:
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2
train.py
2
train.py
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@ -1,6 +1,5 @@
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import argparse
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import time
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import test
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from models import *
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from utils.datasets import *
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@ -182,6 +181,7 @@ def main(opt):
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os.system('cp weights/latest.pt weights/backup' + str(epoch) + '.pt')
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# Calculate mAP
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import test
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test.opt.weights_path = 'weights/latest.pt'
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mAP = test.main(test.opt)
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