v6.0.5

What's Changed

• coco dataset support, automatic aws weight upload by @fcakyon in #54
• add dataset upload, add neptune dataset tracking by @fcakyon in #59
• add windows support for dataset upload by @fcakyon in #61
• make pycocotools optional by @fcakyon in #56
• remove python 3.6 in tests by @fcakyon in #57
• add missing argument in readme by @fcakyon in #60
• fix omp error in windows by @fcakyon in #62
• fix weight s3 uri for windows by @fcakyon in #63

Full Changelog: 6.0.4...6.0.5

COCO Dataset Support

• Start a training using a COCO formatted dataset:

# data.yml
train_json_path: "train.json"
train_image_dir: "train_image_dir/"
val_json_path: "val.json"
val_image_dir: "val_image_dir/"

$ yolov5 train --data data.yaml --weights yolov5s.pt

New AWS and Neptune.AI Utilities

• Automatically upload weights and datasets to AWS S3 (with Neptune.AI artifact tracking integration):

export AWS_ACCESS_KEY_ID=YOUR_KEY
export AWS_SECRET_ACCESS_KEY=YOUR_KEY

$ yolov5 train --data data.yaml --weights yolov5s.pt --s3_upload_dir YOUR_S3_FOLDER_DIRECTORY --upload_dataset

• Add yolo_s3_data_dir into data.yaml to match Neptune dataset with a present dataset in S3.

# data.yml
train_json_path: "train.json"
train_image_dir: "train_image_dir/"
val_json_path: "val.json"
val_image_dir: "val_image_dir/"
yolo_s3_data_dir: s3://bucket_name/data_dir/