# machrisaa/tensorflow-vgg

VGG19 and VGG16 on Tensorflow

Repository: https://github.com/machrisaa/tensorflow-vgg
Canonical: https://ross.abutalabs.com/products/tensorflow-vgg
Language: Python
License Family: other
Last push: 2022-07-23T08:07:49+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3822, "days_push": 1502, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2237, forks 1050 (observed 2026-08-28T04:06:29.432693+00:00)

## 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.

## 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

## 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

## 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

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: deep-learning, computer-vision, image-processing
- platform: python
- tags: vgg16, vgg19, tensorflow, pretrained-models, image-classification, convolutional-networks

## Member repositories
- machrisaa/tensorflow-vgg (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:29.432693+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:44:15.783202+00:00, confidence not recorded.
  - readme: https://github.com/machrisaa/tensorflow-vgg (fetched 2026-08-28T04:06:29.432693+00:00, sha 57b27b387814)
- Data as of 2026-08-30T08:39:29.467469+00:00.