$ train.py [-h] [--epochs EPOCHS] [--batch_size BATCH_SIZE]
[--gradient_accumulations GRADIENT_ACCUMULATIONS]
[--model_def MODEL_DEF] [--data_config DATA_CONFIG]
[--pretrained_weights PRETRAINED_WEIGHTS] [--n_cpu N_CPU]
[--img_size IMG_SIZE]
[--checkpoint_interval CHECKPOINT_INTERVAL]
[--evaluation_interval EVALUATION_INTERVAL]
[--compute_map COMPUTE_MAP]
[--multiscale_training MULTISCALE_TRAINING]
To train on COCO using a Darknet-53 backend pretrained on ImageNet run:
$ python3 train.py --data_config config/coco.data --pretrained_weights weights/darknet53.conv.74
---- [Epoch 7/100, Batch 7300/14658] ----
+------------+--------------+--------------+--------------+
| Metrics | YOLO Layer 0 | YOLO Layer 1 | YOLO Layer 2 |
+------------+--------------+--------------+--------------+
| grid_size | 16 | 32 | 64 |
| loss | 1.554926 | 1.446884 | 1.427585 |
| x | 0.028157 | 0.044483 | 0.051159 |
| y | 0.040524 | 0.035687 | 0.046307 |
| w | 0.078980 | 0.066310 | 0.027984 |
| h | 0.133414 | 0.094540 | 0.037121 |
| conf | 1.234448 | 1.165665 | 1.223495 |
| cls | 0.039402 | 0.040198 | 0.041520 |
| cls_acc | 44.44% | 43.59% | 32.50% |
| recall50 | 0.361111 | 0.384615 | 0.300000 |
| recall75 | 0.222222 | 0.282051 | 0.300000 |
| precision | 0.520000 | 0.300000 | 0.070175 |
| conf_obj | 0.599058 | 0.622685 | 0.651472 |
| conf_noobj | 0.003778 | 0.004039 | 0.004044 |
+------------+--------------+--------------+--------------+
Total Loss 4.429395
---- ETA 0:35:48.821929
Track training progress in Tensorboard:
- Initialize training
- Run the command below
- Go to http://localhost:6006/
$ tensorboard --logdir='logs' --port=6006
####you should create three Directories in Directory 'data'
$----data
--Annotations
--ImageSets
--JPEGImages
If you wanna use the custom dataset of VOC,please set up you classes what u want to train,just as: from the path
data\custom
you can look a file named 'class.names '
click the file
write you class on the file, just as
aircraft
Run
$ cd data
$ python label.py
$ cd ..
$ python voc_annotation.py
To train on the custom dataset run:
$ python train.py --model_def config/yolov3-tiny.cfg --data_config config/custom.data --python train.py --pretrained_weights weights/yolov3-tiny.conv.15
Add --pretrained_weights weights/darknet53.conv.74
to train using a backend pretrained on ImageNet.