yolo_trainer
Module
YoloTrainer
class uses YOLO: Real-Time Object Detection model,
which is originally proposed in this arXiv . However implemented trainer module refers to Yolo-v3 and
uses this Git code as reference work.
References
-
class
farabio.models.detection.yolov3.yolo_trainer.
YoloTrainer
(config)[source]
YoloTrainer trainer class. Override with custom methods here.
- Parameters
- ConvnetTrainerBaseTrainer
Inherits ConvnetTrainer class
-
get_trainloader
()[source]
Hook: Retreives training set of torch.utils.data.DataLoader class
-
define_data_attr
()[source]
Define data related attributes here
-
define_model_attr
()[source]
Define model related attributes here
-
define_train_attr
()[source]
Define training related attributes here
-
define_test_attr
()[source]
Define training related attributes here
-
define_log_attr
()[source]
Define log related attributes here
-
define_compute_attr
()[source]
Define compute related attributes here
-
define_misc_attr
()[source]
Define miscellaneous attributes here
-
build_model
()[source]
Abstract method that builds model
-
on_train_epoch_start
()[source]
Hook: On epoch start
-
on_start_training_batch
(args)[source]
Hook: On training batch start
-
training_step
()[source]
Hook: During training batch
-
on_end_training_batch
()[source]
Hook: On end of training batch
-
on_epoch_end
()[source]
Hook: on epoch end
-
save_model
()[source]
Hook: saves model
-
on_evaluate_epoch_start
()[source]
Hook: on evaluation start
-
on_evaluate_batch_start
(args)[source]
-
evaluate_batch
(*args)[source]
Hook: batch of evaluation loop
-
on_evaluate_epoch_end
()[source]
-
test
()[source]
Hook: Test lifecycle
-
detect_perform
()[source]
-
get_detections
()[source]
-
plot_bbox
()[source]