Instructions to use mobilint/YOLOv8m-face with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/YOLOv8m-face with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="YOLOv8m-face", model_type="DEFAULT", model_path="", core_mode="global8", ) try: image = model.preprocess("path/to/image.jpg") output = model(image) result = model.postprocess(output) finally: model.dispose() - Notebooks
- Google Colab
- Kaggle
YOLOv8m_face
aries-rb/ holds the MXQ reproduced from the published arxiv folder (https://github.com/mobilint/mblt-model-arxiv/tree/main/models/face_detection/YOLOv8m_face). It was compiled by qbcompiler 1.3.0 in the image mobilint/qbcompiler:1.3-cuda12.8.1-ubuntu22.04 (sha256:6ad69aaa9581487ac6a1864b88d4c2179c7a4a486a3ab1ac376dbdfe763415e7) with --inference-scheme all, so it supports the core mode(s) single, multi, global4, global8 only.
It was evaluated with qbruntime 1.5.0 in async inference mode on widerface (3226 samples): hard_ap 0.87199, easy_ap 0.95745, medium_ap 0.94767. Only the evaluated core mode was measured.
SHA-256: 59e9396e3aa029267711944fb80a12269beed4b4873f04808946854fe645d21a (34668445 bytes). Verify a download with sha256sum <file>.mxq and compare the digest with this value and with aries-rb/metadata.json.
aries-rb/best_result.json contains legacy build values and is retained for mblt-vision-python compile defaults. The legacy aries/ directory was removed; mblt-model-zoo <= 2.12 must pin an older revision.
{
"schema_version": 2,
"model": "YOLOv8m_face",
"variant": "gptq",
"qbcompiler": "1.3.0",
"qbruntime": "1.5.0",
"compile": {
"image_tag": "1.3-cuda12.8.1-ubuntu22.04",
"image_digest": "sha256:6ad69aaa9581487ac6a1864b88d4c2179c7a4a486a3ab1ac376dbdfe763415e7",
"inference_scheme": "all",
"device": "gpu"
},
"evaluation": {
"dataset": "widerface",
"sample_count": 3226,
"primary": {
"hard_ap": 0.87199
},
"secondary": {
"easy_ap": 0.95745,
"medium_ap": 0.94767
},
"protocol": null,
"eval_data_identity": {
"annotation_sha256": "4dedbd4eb5d00dafe5fdae9040014dc5ed04eeb493ed7661d6804bc87d9089d0",
"sample_list_sha256": "2e8cd912637ea1af513fd8203d0f195eb500593fb4eb4918e116da0562266519"
},
"identity_audit": "verified",
"inference_mode": "async",
"image_tag": "1.3-cpu-ubuntu22.04",
"image_digest": "sha256:7c25b894fc0807acdf27f15c61b910b96dc66d3f5d97e04b595b2d7a8008e77c"
},
"retention_percent": {
"hard_ap": 98.45318339373821
},
"content_sha256": "eaef496f5de6a8fbd98740fca9e0a26c8363fd99f9fb026c25eb440f03f1e043",
"attempt_id": "YOLOv8m_face-jinman-coreall-d04038015c1d",
"superseded_attempt_ids": [],
"sha256": "59e9396e3aa029267711944fb80a12269beed4b4873f04808946854fe645d21a",
"format": "MXQv7",
"supported_modes": [
"single",
"multi",
"global4",
"global8"
],
"size": 34668445,
"ops_commits": {
"selection": "d642f96eda9bcd0a04ac02d8b73b28aecfc0311f"
},
"arxiv_folder": "https://github.com/mobilint/mblt-model-arxiv/tree/main/models/face_detection/YOLOv8m_face",
"publication": {
"status": "public",
"reason": "approved"
}
}
- Downloads last month
- 18