v0.0.10

What's Changed

• support latest ultralytics by @fcakyon in #19

Full Changelog: 0.0.9...0.0.10

v0.0.9

What's Changed

• improve segmentation visualization by @fcakyon in #17

Full Changelog: 0.0.8...0.0.9

v0.0.8

What's Changed

• support all 3 tasks by @fcakyon in #15

Full Changelog: 0.0.7...0.0.8

v0.0.7

What's Changed

• minor refactor by @fcakyon in #12

Full Changelog: 0.0.6...0.0.7

v0.0.6

What's Changed

• fix some bugs by @keremberke in #10

New Contributors

• @keremberke made their first contribution in #10

Full Changelog: 0.0.5...0.0.6

v0.0.5

What's Changed

• add thumbnail generation by @fcakyon in #8

Full Changelog: 0.0.4...0.0.5

v0.0.4

What's Changed

• fix typos by @fcakyon in #6

Full Changelog: 0.0.3...0.0.4

v0.0.3

ultralytics+

Extra features for ultralytics/ultralytics.

installation

pip install ultralyticsplus

push to 🤗 hub

ultralyticsplus --exp_dir runs/detect/train --hf_model_id HF_USERNAME/MODELNAME

load from 🤗 hub

from ultralyticsplus import YOLO, render_predictions

# load model
model = YOLO('HF_USERNAME/MODELNAME')

# set model parameters
model.overrides['conf'] = 0.25  # NMS confidence threshold
model.overrides['iou'] = 0.45  # NMS IoU threshold
model.overrides['agnostic_nms'] = False  # NMS class-agnostic
model.overrides['max_det'] = 1000  # maximum number of detections per image

# set image
img = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg'

# perform inference
for result in model.predict(img, imgsz=640, return_outputs=True):
    print(result) # [x1, y1, x2, y2, conf, class]
    render = render_predictions(model, img=img, det=result["det"])
    render.show()

What's Changed

• refactor project by @fcakyon in #4

Full Changelog: 0.0.2...0.0.3

v0.0.2

What's Changed

• fix hf card by @fcakyon in #1
• update version by @fcakyon in #2

New Contributors

• @fcakyon made their first contribution in #1

Full Changelog: 0.0.1...0.0.2

v0.0.1

YOLOv8 to 🤗

HuggingFace utilities for Ultralytics/YOLOv8

installation

pip install yolov8tohf

push to hub

yolov8tohf --exp_dir runs/detect/train --hf_model_id HF_USERNAME/MODELNAME

load from hub

from yolov8tohf import YOLO

# load model
model = YOLO('HF_USERNAME/MODELNAME')

# set model parameters
model.overrides['conf'] = 0.25  # NMS confidence threshold
model.overrides['iou'] = 0.45  # NMS IoU threshold
model.overrides['agnostic_nms'] = False  # NMS class-agnostic
model.overrides['max_det'] = 1000  # maximum number of detections per image

# set image
img = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg'

# perform inference
model.predict(img, imgsz=640)

Full Changelog: https://github.com/fcakyon/yolov8tohuggingface/commits/0.0.1