updates
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@ -4,9 +4,9 @@
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# subdivisions=1
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# subdivisions=1
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# Training
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# Training
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batch=64
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batch=64
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subdivisions=16
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subdivisions=8
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width=608
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width=320
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height=608
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height=320
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channels=3
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channels=3
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momentum=0.9
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momentum=0.9
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decay=0.0005
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decay=0.0005
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@ -16,7 +16,7 @@ exposure = 1.5
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hue=.1
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hue=.1
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learning_rate=0.001
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learning_rate=0.001
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burn_in=1000
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burn_in=366
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max_batches = 500200
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max_batches = 500200
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policy=steps
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policy=steps
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steps=400000,450000
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steps=400000,450000
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4
train.py
4
train.py
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@ -233,8 +233,8 @@ def train(
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pbar.set_description(s) # print(s)
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pbar.set_description(s) # print(s)
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# Report time
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# Report time
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dt = (time.time() - t0) / 3600
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# dt = (time.time() - t0) / 3600
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print('%g epochs completed in %.3f hours.' % (epoch - start_epoch + 1, dt))
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# print('%g epochs completed in %.3f hours.' % (epoch - start_epoch + 1, dt))
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# Calculate mAP (always test final epoch, skip first 5 if opt.nosave)
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# Calculate mAP (always test final epoch, skip first 5 if opt.nosave)
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if not (opt.notest or (opt.nosave and epoch < 10)) or epoch == epochs - 1:
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if not (opt.notest or (opt.nosave and epoch < 10)) or epoch == epochs - 1:
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@ -50,7 +50,7 @@ python3 train.py --nosave --data data/coco_10img.data && mv results.txt results0
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python3 train.py --nosave --data data/coco_100img.data && mv results.txt results0r_100img.txt
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python3 train.py --nosave --data data/coco_100img.data && mv results.txt results0r_100img.txt
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# python3 train.py --nosave --data data/coco_100img.data --transfer && mv results.txt results3_100imgTL.txt
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# python3 train.py --nosave --data data/coco_100img.data --transfer && mv results.txt results3_100imgTL.txt
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python3 -c "from utils import utils; utils.plot_results()"
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python3 -c "from utils import utils; utils.plot_results()"
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gsutil cp results*.txt gs://ultralytics
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# gsutil cp results*.txt gs://ultralytics
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gsutil cp results.png gs://ultralytics
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gsutil cp results.png gs://ultralytics
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sudo shutdown
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sudo shutdown
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@ -92,7 +92,6 @@ python3 test.py --data ../supermarket2/supermarket2.data --weights weights/yolov
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python3 test.py --data ../supermarket2/supermarket2.data --weights ../darknet/backup/yolov3-spp-sm2-1cls-scalexy_variable_5000.weights --cfg ../yolov3-spp-sm2-1cls-scalexy_variable.cfg --img-size 320 --conf-thres 0.2 # test
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python3 test.py --data ../supermarket2/supermarket2.data --weights ../darknet/backup/yolov3-spp-sm2-1cls-scalexy_variable_5000.weights --cfg ../yolov3-spp-sm2-1cls-scalexy_variable.cfg --img-size 320 --conf-thres 0.2 # test
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# Debug/Development
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# Debug/Development
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python3 train.py --data data/coco.data --img-size 320 --single-scale --batch-size 64 --accumulate 1 --epochs 1 --evolve --giou
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python3 train.py --data data/coco.data --img-size 320 --single-scale --batch-size 64 --accumulate 1 --epochs 1 --evolve --giou
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python3 test.py --weights weights/latest.pt --cfg cfg/yolov3-spp.cfg --img-size 320
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python3 test.py --weights weights/latest.pt --cfg cfg/yolov3-spp.cfg --img-size 320
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