- [Installation instructions](/installation.html)<br />
Tested on Ubuntu, Red Hat, OS X.
* [Model Zoo](/model_zoo.html)<br />
-BVLC suggests a standard distribution format for Caffe models, and provides trained models for non-commercial use.
+BVLC suggests a standard distribution format for Caffe models, and provides trained models.
* [Developing & Contributing](/development.html)<br />
Guidelines for development and contributing to Caffe.
* [API Documentation](/doxygen/)<br />
+---
+---
# Caffe Model Zoo
Lots of people have used Caffe to train models of different architectures and applied to different problems, ranging from simple regression to AlexNet-alikes to Siamese networks for image similarity to speech applications.
"metadata": {
"description": "Use the pre-trained ImageNet model to classify images with the Python interface.",
"example_name": "ImageNet classification",
- "include_in_docs": true,
+ "include_in_docs": true
},
"nbformat": 3,
"nbformat_minor": 0,
"metadata": {
"description": "Run a pretrained model as a detector in Python.",
"example_name": "R-CNN detection",
- "include_in_docs": true,
+ "include_in_docs": true
},
"nbformat": 3,
"nbformat_minor": 0,
"metadata": {
"description": "Extracting features and visualizing trained filters with an example image, viewed layer-by-layer.",
"example_name": "Filter visualization",
- "include_in_docs": true,
+ "include_in_docs": true
},
"nbformat": 3,
"nbformat_minor": 0,
"metadata": {
"description": "How to do net surgery and manually change model parameters, making a fully-convolutional classifier for dense feature extraction.",
"example_name": "Editing model parameters",
- "include_in_docs": true,
+ "include_in_docs": true
},
"nbformat": 3,
"nbformat_minor": 0,