# fchollet/deep-learning-models

Keras code and weights files for popular deep learning models.

Repository: https://github.com/fchollet/deep-learning-models
Canonical: https://ross.abutalabs.com/products/deep-learning-models
Language: Python
License: MIT
License Family: permissive
Last push: 2020-10-01T05:28:40+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3682, "days_push": 2162, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 7348, forks 2428 (observed 2026-08-28T04:09:58.384564+00:00)

## What it is
A deprecated collection of Keras code and pre-trained weights for popular deep learning image classification models such as VGG16, VGG19, ResNet50, and Inception v3. It has been superseded by the built-in keras.applications module.

## Use cases
- classify images with pretrained imagenet models in keras
- extract features from images using vgg or resnet
- get intermediate layer features from pretrained networks
- load pretrained weights for vgg16 vgg19 resnet50 inception v3
- music tagging with a CRNN model

## When to choose
- you are on a very old Keras setup that predates keras.applications
- you need the original standalone model files or weights for reference

## When to avoid
- starting any new project - use keras.applications instead
- you need maintained code, bug fixes, or support
- you use modern TensorFlow/Keras versions

## Facets
- artifact type: library
- maturity: abandoned
- function: machine-learning, deep-learning, image-processing, computer-vision
- domain: deep-learning, computer-vision, image-processing, machine-learning
- platform: python
- tags: keras, pretrained-models, imagenet, vgg16, resnet50, inception, deprecated, transfer-learning

## Member repositories
- fchollet/deep-learning-models (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:58.384564+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 2026-08-29T17:38:26.636509+00:00, confidence not recorded.
  - readme: https://github.com/fchollet/deep-learning-models (fetched 2026-08-28T04:09:58.384564+00:00, sha 384671ac1217)
- Data as of 2026-08-30T08:39:29.467469+00:00.