yolov4 v1.2.0

CHANGELOG

• model: remove tpu argument
• tf: reflect model changes
• tflite: remove tpu_hair
• tf, tflite: move inference into BaseClass
• model: yolov4: remove unused import
• pylint: update .pylintrc
• common: base_class: modify inference() to be able to use cam
• common: base_class: add fps display to screen

yolov4 v1.1.0

CHANGELOG

• model: add kernel_regularizer argument
• tf: remove subdivision
• tf: dataset: fix issue where coordinates become 0 due to repeated division
• tf: dataset: modify to shuffle when augmentation
• tf: train: modify order of declaration
• tf: train: give xiou_loss to more weight
• tf: train: use keras.losses.BinaryCrossentropy to avoid nan problem
• tf: train: add verbose argument
• tf: dataset: change converted_coco format
• tf: add image_path_prefix argument to load_dataset()
• tf: add loss_verbose argument to compile()
• tf: reflect dataset format change to save_dataset_for_mAP()

yolov4 v1.0.0

CHANGELOG

• tf: dataset: add label smooting argument
• tf: add label_smooting argument to load_dataset()
• tf: train: set truth_conf threshold to 0.5 because of label smoothing

yolov4 v0.24.0

CHANGELOG

• tf: set default num of sample for mAP to 1000
• tf: fix error handling when image is empty

yolov4 v0.23.0

CHANGELOG

• tf: dataset: add error handling when bboxes are empty
• common: media: replace space of class name to underbar
• tf: implement save_dataset_for_mAP()
• tf: dataset: add error handling when image is empty

yolov4 v0.22.0

CHANGELOG

• tf: add TFLITE_BUILTINS, SELECT_TF_OPS to default supported_ops
• tf: dataset: modify to check if image exists when creating a dataset
• tf: dataset: remove preprocess_dataset
• tf: dataset: add cut_out
• tf: dataset: add _next_random_augmentation_data()
• tf: dataset: add mix_up
• tf: dataset: implement mosaic

yolov4 v0.21.0

CHANGELOG

• tf: train: set epsilon used for division to 1e-8
• tf: train: add giou and iou to iou_type
• tf: train: fix loss function of bbox_probabilities

yolov4 v0.20.0

CHANGELOG

• tf: train: modify epsilon to 1e-9
• tf: train: remove weight for conf_noobj_loss
• tf: add arguments to fit()
• tf: dataset: fix problem of not finding images
• tf: add SaveWeightsCallback

yolov4 v0.19.0

CHANGELOG

• tf: weights: modify 'set' to 'load'
• tf: weights: implement *_save_weights
• tf: add save_weights()

yolov4 v0.18.0

CHANGELOG

• yolov4: clarify batch number
• tf: remove by_name in load_weights
• tf: dataset: simplify code
• tf: dataset: fix problem of making a batch with same image

Thanks to @anklebreaker