GitHub PyPI - Downloads

DetExecutor

Python package with latest versions of YOLO architecture for training and inference

Install

Installing is quite simple, just use pip:

pip3 install det_executor

Train

Training support is still in progress!

Inference

Get available models

from det_executor import DetExecutor
# print list of supported arches
DetExecutor.list_arch()

Output

{
    "yolov7": YoloArch(
        version="7",
        img_size=(640, 640),
        size="75.6MB",
        params="37.6M",
        flops="",
        module="yolov7_package",
        load_link="yolov7.pt",
        trainable=False,
        traced=False,
    ),
    "yolov7x": YoloArch(
        version="7",
        img_size=(640, 640),
        size="75.6MB",
        params="71.3M",
        flops="",
        module="yolov7_package",
        load_link="yolov7x.pt",
        trainable=False,
        traced=False,
    ),
    "yolov7-w6": YoloArch(
        version="7",
        img_size=(1280, 1280),
        size="141.3MB",
        params="70.4M",
        flops="",
        module="yolov7_package",
        load_link="yolov7-w6.pt",
        trainable=False,
        traced=False,
    ),
    "yolov7-e6": YoloArch(
        version="7",
        img_size=(1280, 1280),
        size="195.0MB",
        params="97.2M",
        flops="",
        module="yolov7_package",
        load_link="yolov7-e6.pt",
        trainable=False,
        traced=False,
    ),
    "yolov7-d6": YoloArch(
        version="7",
        img_size=(1280, 1280),
        size="286.3MB",
        params="133.8M",
        flops="",
        module="yolov7_package",
        load_link="yolov7-d6.pt",
        trainable=False,
        traced=False,
    ),
    "yolov7-e6e": YoloArch(
        version="7",
        img_size=(1280, 1280),
        size="304.4MB",
        params="151.8M",
        flops="",
        module="yolov7_package",
        load_link="yolov7-e6e.pt",
        trainable=False,
        traced=False,
    ),
    "yolov7-traced": YoloArch(
        version="7",
        img_size=(640, 640),
        size="74.3MB",
        params="36.9M",
        flops="",
        module="yolov7_package",
        load_link="1L8mPcUvabUscEk6Nr8ck5EFgopgPAMDW",
        trainable=False,
        traced=True,
    ),
    "yolov7-tiny": YoloArch(
        version="7",
        img_size=(640, 640),
        size="12.6MB",
        params="6.2M",
        flops="",
        module="yolov7_package",
        load_link="yolov7-tiny.pt",
        trainable=False,
        traced=False,
    ),
    "yolov7-tiny-traced": YoloArch(
        version="7",
        img_size=(640, 640),
        size="12.7MB",
        params="6.2M",
        flops="",
        module="yolov7_package",
        load_link="18zJyljtolPENDI_kFw3FlRFnQTnaLuDF",
        trainable=False,
        traced=True,
    ),
    "yolov8n": YoloArch(
        version="8",
        img_size=(640, 640),
        size="6.5MB",
        params="3.2M",
        flops="",
        module="yolov8",
        load_link="yolov8n.pt",
        trainable=False,
        traced=False,
    ),
    "yolov8s": YoloArch(
        version="8",
        img_size=(640, 640),
        size="22.6MB",
        params="11.2M",
        flops="",
        module="yolov8",
        load_link="yolov8s.pt",
        trainable=False,
        traced=False,
    ),
    "yolov8m": YoloArch(
        version="8",
        img_size=(640, 640),
        size="52.1MB",
        params="25.9M",
        flops="",
        module="yolov8",
        load_link="yolov8m.pt",
        trainable=False,
        traced=False,
    ),
    "yolov8l": YoloArch(
        version="8",
        img_size=(640, 640),
        size="87.8MB",
        params="43.7M",
        flops="",
        module="yolov8",
        load_link="yolov8l.pt",
        trainable=False,
        traced=False,
    ),
    "yolov8x": YoloArch(
        version="8",
        img_size=(640, 640),
        size="136.9MB",
        params="68.2M",
        flops="",
        module="yolov8",
        load_link="yolov8x.pt",
        trainable=False,
        traced=False,
    ),
    "yolos-tiny": YoloArch(
        version="s",
        img_size=None,
        size="136.9MB",
        params="6.5M",
        flops="512x*>18.8G|256x*>3.4G",
        module="yolos",
        load_link="hustvl/yolos-tiny",
        trainable=False,
        traced=False,
    ),
}

Loading model

from det_executor import DetExecutor

# loading model
name = 'yolov7'
ex = DetExecutor(name)

Predict and draw

from det_executor import DetExecutor, draw_on_image
import cv2

# loading model
name = 'yolov7'
ex = DetExecutor(name)

# loading image
img = ex.load_image('test/img.jpg')
# or img = cv2.imread('test/img.jpg')

# predict
classes, boxes, scores = ex.predict(img)

# draw
img = draw_on_image(img, boxes[0], scores[0], classes[0])
cv2.imshow("image", img)
cv2.waitKey()

Roadmap

Training pipeline for all models
Load from custom weights
More models

Citation

@article{wang2022yolov7,
  title={{YOLOv7}: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors},
  author={Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark},
  journal={arXiv preprint arXiv:2207.02696},
  year={2022}
}

@misc{fang2021look,
      title={You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection}, 
      author={Yuxin Fang and Bencheng Liao and Xinggang Wang and Jiemin Fang and Jiyang Qi and Rui Wu and Jianwei Niu and Wenyu Liu},
      year={2021},
      eprint={2106.00666},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

License
- OSI Approved :: MIT License
Operating System
- OS Independent
Programming Language
- Python :: 3.6

Metadata

License
- OSI Approved :: MIT License
Operating System
- OS Independent
Programming Language
- Python :: 3.6

Release files for det-executor 0.0.9

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for det-executor 0.0.9
File	Size	Uploaded	Provenance
det_executor-0.0.9.tar.gz	97.2 kB	Oct 6, 2023	Without provenance	Details

Built distribution (wheel)

Table of built distributions (wheels) for det-executor 0.0.9
File	Interpreter	ABI	Platform	Reset
det_executor-0.0.9-py3-none-any.whl 103.2 kB Oct 6, 2023 Without provenance	Python 3	none	any	Details

Total release size: 200.5 kB

Release files / det_executor-0.0.9.tar.gz

Download URL	det_executor-0.0.9.tar.gz
Size	97.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`bf91cb2371d5e6c2d67646c4eb5483853b7f571e9da5bff6896986b8eb508667`
BLAKE2b-256 checksum How to use checksums	`7b4faa99baf2d68347ec3a01f1a6289f14eb8d27f16b70bda20be79139df1d78`
Upload date	Oct 6, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.2 CPython/3.11.0`

Release files / det_executor-0.0.9-py3-none-any.whl

Download URL	det_executor-0.0.9-py3-none-any.whl
Size	103.2 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`b36858a2a60337e048eb396ba8f98c160b497177dfa31d31474a2c5a4adaf79c`
BLAKE2b-256 checksum How to use checksums	`38b76726bb3c2c9b61ea911977dfc0dc283cfc84a20a22b5b0962bb06d8702ac`
Upload date	Oct 6, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.2 CPython/3.11.0`

Security for det-executor 0.0.9

Report project as malware

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.