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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-06-23 22:01:11 +02:00
parent 0f2e136c05
commit 57b616b8b1
3 changed files with 5 additions and 37 deletions
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35
train.py
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@ -25,39 +25,6 @@ hyp = {'giou': .035, # giou loss gain
'weight_decay': 0.0005} # optimizer weight decay
# Hyperparameters: Original, Metrics: 0.172 0.304 0.156 0.205 (square)
# hyp = {'xy': 0.5, # xy loss gain
# 'wh': 0.0625, # wh loss gain
# 'cls': 0.0625, # cls loss gain
# 'conf': 4, # conf loss gain
# 'iou_t': 0.1, # iou target-anchor training threshold
# 'lr0': 0.001, # initial learning rate
# 'lrf': -5., # final learning rate = lr0 * (10 ** lrf)
# 'momentum': 0.9, # SGD momentum
# 'weight_decay': 0.0005} # optimizer weight decay
# Hyperparameters: train.py --evolve --epochs 2 --img-size 320, Metrics: 0.225 0.251 0.145 0.218 (rect)
# hyp = {'xy': 0.4499, # xy loss gain
# 'wh': 0.05121, # wh loss gain
# 'cls': 0.04207, # cls loss gain
# 'conf': 2.853, # conf loss gain
# 'iou_t': 0.2487, # iou target-anchor training threshold
# 'lr0': 0.0005301, # initial learning rate
# 'lrf': -5., # final learning rate = lr0 * (10 ** lrf)
# 'momentum': 0.8823, # SGD momentum
# 'weight_decay': 0.0004149} # optimizer weight decay
# Hyperparameters: train.py --evolve --epochs 2 --img-size 320, Metrics: 0.178 0.313 0.167 0.212 (square)
# hyp = {'xy': 0.4664, # xy loss gain
# 'wh': 0.08437, # wh loss gain
# 'cls': 0.05145, # cls loss gain
# 'conf': 4.244, # conf loss gain
# 'iou_t': 0.09121, # iou target-anchor training threshold
# 'lr0': 0.0004938, # initial learning rate
# 'lrf': -5., # final learning rate = lr0 * (10 ** lrf)
# 'momentum': 0.9025, # SGD momentum
# 'weight_decay': 0.0005417} # optimizer weight decay
def train(
cfg,
data_cfg,
@ -312,7 +279,7 @@ def print_mutation(hyp, results):
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--epochs', type=int, default=68, help='number of epochs')
parser.add_argument('--epochs', type=int, default=100, help='number of epochs')
parser.add_argument('--batch-size', type=int, default=8, help='batch size')
parser.add_argument('--accumulate', type=int, default=8, help='number of batches to accumulate before optimizing')
parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')

5
utils/gcp.sh
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@ -3,9 +3,10 @@
# New VM
rm -rf yolov3 weights coco
git clone https://github.com/ultralytics/yolov3
git clone https://github.com/cocodataset/cocoapi && cd cocoapi/PythonAPI && make && cd ../.. && cp -r cocoapi/PythonAPI/pycocotools yolov3
git clone https://github.com/NVIDIA/apex && cd apex && pip install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" . --user && cd .. && rm -rf apex
bash yolov3/weights/download_yolov3_weights.sh && cp -r weights yolov3
bash yolov3/data/get_coco_dataset.sh
git clone https://github.com/cocodataset/cocoapi && cd cocoapi/PythonAPI && make && cd ../.. && cp -r cocoapi/PythonAPI/pycocotools yolov3
sudo shutdown
# Re-clone
@ -95,7 +96,7 @@ python3 test.py --data ../supermarket2/supermarket2.data --weights ../darknet/ba
# Debug/Development
python3 train.py --data data/coco.data --img-size 320 --single-scale --batch-size 32 --accumulate 2 --epochs 1
python3 train.py --data data/coco.data --img-size 320 --single-scale --batch-size 64 --accumulate 1 --epochs 1 --evolve
python3 test.py --weights weights/latest.pt --cfg cfg/yolov3-spp.cfg --img-size 320
gsutil cp evolve.txt gs://ultralytics

2
utils/utils.py
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@ -641,7 +641,7 @@ def plot_targets_txt(): # from utils.utils import *; plot_targets_txt()
x = np.loadtxt('targets.txt', dtype=np.float32)
x = x.T
s = ['x targets','y targets','width targets','height targets']
s = ['x targets', 'y targets', 'width targets', 'height targets']
fig, ax = plt.subplots(2, 2, figsize=(8, 8))
ax = ax.ravel()
for i in range(4):