ultralyticsplus

Name	ultralyticsplus JSON
Version	0.1.0 JSON
	download
home_page
Summary	HuggingFace utilities for Ultralytics/YOLOv8.
upload_time	2024-02-03 20:02:13
maintainer
docs_url	None
author
requires_python	>=3.7
license	MIT
keywords	machine-learning deep-learning ml vision yolov8 object-detection huggingface datasets
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # ultralytics+

Extra features for [ultralytics/ultralytics](https://github.com/ultralytics/ultralytics).

## installation

```bash
pip install ultralyticsplus
```

## push to 🤗 hub

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

## load from 🤗 hub

```python
from ultralyticsplus import YOLO, render_result

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

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

# parse results
result = results[0]
boxes = result.boxes.xyxy # x1, y1, x2, y2
scores = result.boxes.conf
categories = result.boxes.cls
scores = result.probs # for classification models
masks = result.masks # for segmentation models

# show results on image
render = render_result(model=model, image=image, result=result)
render.show()
```

            

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