soeaver/caffe-model resource
Caffe models (including classification, detection and segmentation) and deploy files for famouse networks observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3840
- days_rel: n/a
- days_push: 3086
- n_releases_24m: 0
Adoption not part of the score
1276 stars · 608 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A model zoo of pre-trained Caffe models (caffemodel files) and deploy prototxt files for popular architectures such as ResNet, ResNeXt, Inception, Xception, DenseNet, Wide ResNet, SENet, and DPN. It covers ImageNet classification, PASCAL VOC object detection (e.g., Faster R-CNN), and segmentation, with most weights converted from other frameworks like MXNet, TensorFlow, and Keras.
Use cases
- download pretrained caffe models for imagenet classification
- find caffemodel weights for resnet inception resnext densenet
- get deploy prototxt files for famous cnn architectures
- pretrained faster rcnn detection models on pascal voc
- semantic segmentation pretrained models in caffe
- compare imagenet top-1 top-5 accuracy across caffe backbones
- bootstrap caffe experiments without training from scratch
When to choose
- You use the Caffe framework and need ready-made pretrained weights instead of training from scratch
- You need deploy-ready prototxt definitions for classic CNN backbones
- You want ImageNet classification, PASCAL VOC detection, or segmentation baselines in Caffe format
- You are reproducing 2017-2018 era computer vision results with py-RFCN-priv or similar Caffe pipelines
When to avoid
- You work natively in PyTorch, TensorFlow, or MXNet, since weights here target Caffe
- You need modern architectures or ongoing maintenance - the repository has not been updated since 2018
- You need training code rather than converted inference models
- You need models for domains beyond image classification, detection, and segmentation
Facets
dataset · maturity abandoned
deep-learning machine-learning computer-vision deep-learning machine-learning computer-vision image-processing python cpp caffe model-zoo pretrained-models caffemodel deploy-prototxt imagenet resnet resnext inception densenet dpn image-classification object-detection semantic-segmentation faster-rcnn linux gpu
1 source
- readme: https://github.com/soeaver/caffe-model · fetched 2026-08-28 · 94084bf89bd3
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| soeaver/caffe-model | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="soeaver/caffe-model")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem