{"adoption": {"forks": 1050, "observed_at": "2026-08-28T04:06:29.432693+00:00", "stars": 2237}, "canonical_url": "https://ross.abutalabs.com/products/tensorflow-vgg", "card": {"archived": false, "artifact_type": "library", "description": "VGG19 and VGG16 on Tensorflow", "domain": ["deep-learning", "computer-vision", "image-processing"], "enriched": true, "function": ["machine-learning", "deep-learning"], "health_score": 20, "homepage": null, "language": "Python", "license": null, "license_family": "other", "maturity": "maintenance", "member_repos": ["machrisaa/tensorflow-vgg"], "name": "machrisaa/tensorflow-vgg", "platform": ["python"], "pushed_at": "2022-07-23T08:07:49+00:00", "repo": "machrisaa/tensorflow-vgg", "stars": 2237, "tags": ["vgg16", "vgg19", "tensorflow", "pretrained-models", "image-classification", "convolutional-networks"], "topics": [], "urls": [], "use_cases": ["extract features from images using pretrained VGG layers", "classify images with VGG16 or VGG19 in TensorFlow", "build a VGG network with custom batch size or removed FC layers", "fine-tune or train VGG19 from pretrained weights or scratch", "use VGG as a backbone for style transfer or other vision models"], "what_it_is": "A Python library implementing the VGG16 and VGG19 convolutional neural networks in TensorFlow, loading pretrained weights from npy files for fast initialization and lower memory usage. It exposes all network layers as accessible tensors and includes a trainable variant of VGG19.", "when_to_avoid": ["you are using TensorFlow 2.x or Keras, where built-in pretrained VGG applications are better maintained", "you need a license-protected or actively maintained project", "you require models beyond VGG16/VGG19 or modern architectures like ResNet or EfficientNet"], "when_to_choose": ["you need a simple, modifiable VGG implementation in TensorFlow with easy access to intermediate layers", "you want faster initialization and lower memory usage than default TensorFlow model loading", "you need a trainable VGG19 variant to fine-tune on your own data"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/tensorflow-vgg", "repo": "machrisaa/tensorflow-vgg", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T02:44:15.783202+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "57b27b3878143ed7c22be668a00352d989d5c955af2f6c08e3b34ffcfc9e7b26", "fetched_at": "2026-08-28T04:06:29.432693+00:00", "kind": "readme", "missing": false, "url": "https://github.com/machrisaa/tensorflow-vgg"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T02:44:15.783202+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "57b27b3878143ed7c22be668a00352d989d5c955af2f6c08e3b34ffcfc9e7b26", "fetched_at": "2026-08-28T04:06:29.432693+00:00", "kind": "readme", "missing": false, "url": "https://github.com/machrisaa/tensorflow-vgg"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T02:44:15.783202+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "57b27b3878143ed7c22be668a00352d989d5c955af2f6c08e3b34ffcfc9e7b26", "fetched_at": "2026-08-28T04:06:29.432693+00:00", "kind": "readme", "missing": false, "url": "https://github.com/machrisaa/tensorflow-vgg"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T02:44:15.783202+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "57b27b3878143ed7c22be668a00352d989d5c955af2f6c08e3b34ffcfc9e7b26", "fetched_at": "2026-08-28T04:06:29.432693+00:00", "kind": "readme", "missing": false, "url": "https://github.com/machrisaa/tensorflow-vgg"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T02:44:15.783202+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "57b27b3878143ed7c22be668a00352d989d5c955af2f6c08e3b34ffcfc9e7b26", "fetched_at": "2026-08-28T04:06:29.432693+00:00", "kind": "readme", "missing": false, "url": "https://github.com/machrisaa/tensorflow-vgg"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T02:44:15.783202+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "57b27b3878143ed7c22be668a00352d989d5c955af2f6c08e3b34ffcfc9e7b26", "fetched_at": "2026-08-28T04:06:29.432693+00:00", "kind": "readme", "missing": false, "url": "https://github.com/machrisaa/tensorflow-vgg"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:06:29.432693+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T02:44:15.783202+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "57b27b3878143ed7c22be668a00352d989d5c955af2f6c08e3b34ffcfc9e7b26", "fetched_at": "2026-08-28T04:06:29.432693+00:00", "kind": "readme", "missing": false, "url": "https://github.com/machrisaa/tensorflow-vgg"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T02:44:15.783202+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "57b27b3878143ed7c22be668a00352d989d5c955af2f6c08e3b34ffcfc9e7b26", "fetched_at": "2026-08-28T04:06:29.432693+00:00", "kind": "readme", "missing": false, "url": "https://github.com/machrisaa/tensorflow-vgg"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T02:44:15.783202+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "57b27b3878143ed7c22be668a00352d989d5c955af2f6c08e3b34ffcfc9e7b26", "fetched_at": "2026-08-28T04:06:29.432693+00:00", "kind": "readme", "missing": false, "url": "https://github.com/machrisaa/tensorflow-vgg"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T02:44:15.783202+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "57b27b3878143ed7c22be668a00352d989d5c955af2f6c08e3b34ffcfc9e7b26", "fetched_at": "2026-08-28T04:06:29.432693+00:00", "kind": "readme", "missing": false, "url": "https://github.com/machrisaa/tensorflow-vgg"}], "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": 3822, "days_push": 1502, "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}}