From bc601e9060cc71b95f0250b9efacaffcbb5d8c0e Mon Sep 17 00:00:00 2001 From: Sergey Karayev Date: Thu, 4 Sep 2014 01:43:35 +0100 Subject: [PATCH] minor fixes to docs --- docs/index.md | 2 +- docs/model_zoo.md | 2 ++ examples/classification.ipynb | 2 +- examples/detection.ipynb | 2 +- examples/filter_visualization.ipynb | 2 +- examples/net_surgery.ipynb | 2 +- 6 files changed, 7 insertions(+), 5 deletions(-) diff --git a/docs/index.md b/docs/index.md index 83ba236..af4b50c 100644 --- a/docs/index.md +++ b/docs/index.md @@ -39,7 +39,7 @@ A 4-page report for the ACM Multimedia Open Source competition. - [Installation instructions](/installation.html)
Tested on Ubuntu, Red Hat, OS X. * [Model Zoo](/model_zoo.html)
-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)
Guidelines for development and contributing to Caffe. * [API Documentation](/doxygen/)
diff --git a/docs/model_zoo.md b/docs/model_zoo.md index 490bb68..5fd3ecf 100644 --- a/docs/model_zoo.md +++ b/docs/model_zoo.md @@ -1,3 +1,5 @@ +--- +--- # 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. diff --git a/examples/classification.ipynb b/examples/classification.ipynb index 7c01b9e..9c9d247 100644 --- a/examples/classification.ipynb +++ b/examples/classification.ipynb @@ -2,7 +2,7 @@ "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, diff --git a/examples/detection.ipynb b/examples/detection.ipynb index e162041..62263b6 100644 --- a/examples/detection.ipynb +++ b/examples/detection.ipynb @@ -2,7 +2,7 @@ "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, diff --git a/examples/filter_visualization.ipynb b/examples/filter_visualization.ipynb index 4d69dc0..abf4c0d 100644 --- a/examples/filter_visualization.ipynb +++ b/examples/filter_visualization.ipynb @@ -2,7 +2,7 @@ "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, diff --git a/examples/net_surgery.ipynb b/examples/net_surgery.ipynb index 336c845..0854018 100644 --- a/examples/net_surgery.ipynb +++ b/examples/net_surgery.ipynb @@ -2,7 +2,7 @@ "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, -- 2.7.4