{"adoption": {"forks": 278, "observed_at": "2026-08-28T04:05:30.576498+00:00", "stars": 1744}, "canonical_url": "https://ross.abutalabs.com/products/mobilenet-yolo", "card": {"archived": false, "artifact_type": "library", "description": "MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB:fire::fire::fire:", "domain": ["computer-vision", "deep-learning", "mobile-development"], "enriched": true, "function": ["machine-learning", "computer-vision", "image-processing"], "health_score": 20, "homepage": null, "language": "C", "license": "NOASSERTION", "license_family": "other", "maturity": "abandoned", "member_repos": ["dog-qiuqiu/MobileNet-Yolo"], "name": "dog-qiuqiu/MobileNet-Yolo", "platform": ["cross-platform", "cpp", "python"], "pushed_at": "2021-02-06T02:16:46+00:00", "repo": "dog-qiuqiu/MobileNet-Yolo", "stars": 1744, "tags": ["object-detection", "yolov3", "mobilenetv2", "face-detection", "ncnn", "mnn", "darknet", "lightweight-models", "edge-inference", "landmark-detection", "android", "linux"], "topics": ["cnn", "yolov3", "yolo", "mobilenetv2", "mobilenet-yolo", "ncnn", "cv", "object-detection", "computer-vision", "deep-learning", "darknet", "mnn", "face-detection", "ncnn-model", "mnn-framework", "landmark", "landmark-detection"], "urls": [], "use_cases": ["run real-time object detection on mobile phones", "deploy a tiny face detection model under 500KB", "train a lightweight YOLOv3 model in Darknet and deploy with NCNN", "detect human pose keypoints on edge devices", "benchmark small detection models on ARM CPUs", "build an embedded camera app with low-FLOPS detection"], "what_it_is": "A collection of ultra-lightweight YOLOv3-based object detection models (MobileNetV2-YOLOv3-Lite/Nano, YoloFace) designed for mobile and embedded inference with NCNN and MNN. It includes Darknet training configurations, pre-trained weights, and C samples for detection and landmark tasks.", "when_to_avoid": ["you need the latest state-of-the-art detection models, since the project is no longer updated and points to Yolo-Fastest", "you require GPU training with Darknet group convolutions on Pascal GPUs, which is known to be problematic", "you need a maintained project with active support and recent releases"], "when_to_choose": ["you need extremely small and fast object detection models for mobile or embedded ARM devices", "you want NCNN or MNN deployment of YOLO-style detectors", "you need a minimal face detection model with tiny weight size"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/mobilenet-yolo", "repo": "dog-qiuqiu/MobileNet-Yolo", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T03:29:19.050644+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "937730b99915be704523f6283c75a26876f6800b385868f02e49786844a9dab6", "fetched_at": "2026-08-28T04:05:30.576498+00:00", "kind": "readme", "missing": false, "url": "https://github.com/dog-qiuqiu/MobileNet-Yolo"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T03:29:19.050644+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "937730b99915be704523f6283c75a26876f6800b385868f02e49786844a9dab6", "fetched_at": "2026-08-28T04:05:30.576498+00:00", "kind": "readme", "missing": false, "url": "https://github.com/dog-qiuqiu/MobileNet-Yolo"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T03:29:19.050644+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "937730b99915be704523f6283c75a26876f6800b385868f02e49786844a9dab6", "fetched_at": "2026-08-28T04:05:30.576498+00:00", "kind": "readme", "missing": false, "url": "https://github.com/dog-qiuqiu/MobileNet-Yolo"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T03:29:19.050644+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "937730b99915be704523f6283c75a26876f6800b385868f02e49786844a9dab6", "fetched_at": "2026-08-28T04:05:30.576498+00:00", "kind": "readme", "missing": false, "url": "https://github.com/dog-qiuqiu/MobileNet-Yolo"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T03:29:19.050644+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "937730b99915be704523f6283c75a26876f6800b385868f02e49786844a9dab6", "fetched_at": "2026-08-28T04:05:30.576498+00:00", "kind": "readme", "missing": false, "url": "https://github.com/dog-qiuqiu/MobileNet-Yolo"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T03:29:19.050644+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "937730b99915be704523f6283c75a26876f6800b385868f02e49786844a9dab6", "fetched_at": "2026-08-28T04:05:30.576498+00:00", "kind": "readme", "missing": false, "url": "https://github.com/dog-qiuqiu/MobileNet-Yolo"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:05:30.576498+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T03:29:19.050644+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "937730b99915be704523f6283c75a26876f6800b385868f02e49786844a9dab6", "fetched_at": "2026-08-28T04:05:30.576498+00:00", "kind": "readme", "missing": false, "url": "https://github.com/dog-qiuqiu/MobileNet-Yolo"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T03:29:19.050644+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "937730b99915be704523f6283c75a26876f6800b385868f02e49786844a9dab6", "fetched_at": "2026-08-28T04:05:30.576498+00:00", "kind": "readme", "missing": false, "url": "https://github.com/dog-qiuqiu/MobileNet-Yolo"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T03:29:19.050644+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "937730b99915be704523f6283c75a26876f6800b385868f02e49786844a9dab6", "fetched_at": "2026-08-28T04:05:30.576498+00:00", "kind": "readme", "missing": false, "url": "https://github.com/dog-qiuqiu/MobileNet-Yolo"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T03:29:19.050644+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "937730b99915be704523f6283c75a26876f6800b385868f02e49786844a9dab6", "fetched_at": "2026-08-28T04:05:30.576498+00:00", "kind": "readme", "missing": false, "url": "https://github.com/dog-qiuqiu/MobileNet-Yolo"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 35}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_releases", "no_license"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2268, "days_push": 2035, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 32, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}