ultralyticsplus

Huggingface utilities for Ultralytics/YOLOv8

GPL-3.0 License

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ultralyticsplus - v0.0.10

Published by fcakyon almost 2 years ago

ultralyticsplus - v0.0.9

Published by fcakyon almost 2 years ago

What's Changed

Full Changelog: https://github.com/fcakyon/ultralyticsplus/compare/0.0.8...0.0.9

ultralyticsplus - v0.0.8

Published by fcakyon almost 2 years ago

ultralyticsplus - v0.0.7

Published by fcakyon almost 2 years ago

ultralyticsplus - v0.0.6

Published by fcakyon almost 2 years ago

What's Changed

New Contributors

Full Changelog: https://github.com/fcakyon/ultralyticsplus/compare/0.0.5...0.0.6

ultralyticsplus - v0.0.5

Published by fcakyon almost 2 years ago

ultralyticsplus - v0.0.4

Published by fcakyon almost 2 years ago

ultralyticsplus - v0.0.3

Published by fcakyon almost 2 years ago

ultralytics+

Extra features for ultralytics/ultralytics.

installation

pip install ultralyticsplus

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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

Full Changelog: https://github.com/fcakyon/ultralyticsplus/compare/0.0.2...0.0.3

ultralyticsplus - v0.0.2

Published by fcakyon almost 2 years ago

What's Changed

New Contributors

Full Changelog: https://github.com/fcakyon/yolov8tohuggingface/compare/0.0.1...0.0.2

ultralyticsplus - v0.0.1

Published by fcakyon almost 2 years ago

YOLOv8 to 🤗

HuggingFace utilities for Ultralytics/YOLOv8

installation

pip install yolov8tohf

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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

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