kadirnar / yolov10s

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Total runs: 11
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7-day runs: 1
30-day runs: 5
Model's Last Updated: May 27 2024
object-detection

Introduction of yolov10s

Model Details of yolov10s

Model Description

YOLOv10: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Paper Repo: Implementation of paper - YOLOv10

Installation
pip install supervision git+https://github.com/THU-MIG/yolov10.git
Yolov10 Inference
from ultralytics import YOLOv10
import supervision as sv
import cv2

MODEL_PATH = 'yolov10n.pt'
IMAGE_PATH = 'dog.jpeg'

model = YOLOv10(MODEL_PATH)
image  = cv2.imread(IMAGE_PATH)
results = model(source=image, conf=0.25, verbose=False)[0]
detections = sv.Detections.from_ultralytics(results)
box_annotator = sv.BoxAnnotator()

category_dict = {
    0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus',
    6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant',
    11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat',
    16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear',
    22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag',
    27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard',
    32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove',
    36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle',
    40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl',
    46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli',
    51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake',
    56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table',
    61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard',
    67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink',
    72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors',
    77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'
}

labels = [
    f"{category_dict[class_id]} {confidence:.2f}"
    for class_id, confidence in zip(detections.class_id, detections.confidence)
]
annotated_image = box_annotator.annotate(
    image.copy(), detections=detections, labels=labels
)

cv2.imwrite('annotated_dog.jpeg', annotated_image)
BibTeX Entry and Citation Info
@misc{wang2024yolov10,
     title={YOLOv10: Real-Time End-to-End Object Detection}, 
     author={Ao Wang and Hui Chen and Lihao Liu and Kai Chen and Zijia Lin and Jungong Han and Guiguang Ding},
     year={2024},
     eprint={2405.14458},
     archivePrefix={arXiv},
     primaryClass={cs.CV}
}

Runs of kadirnar yolov10s on huggingface.co

11
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More yolov10s license Visit here:

https://choosealicense.com/licenses/agpl-3.0

yolov10s huggingface.co

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kadirnar yolov10s online free url in huggingface.co:

https://huggingface.co/kadirnar/yolov10s

yolov10s install

yolov10s is an open source model from GitHub that offers a free installation service, and any user can find yolov10s on GitHub to install. At the same time, huggingface.co provides the effect of yolov10s install, users can directly use yolov10s installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

yolov10s install url in huggingface.co:

https://huggingface.co/kadirnar/yolov10s

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