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panovr / readme.md
Created May 15, 2016 10:50 — forked from baraldilorenzo/readme.md
VGG-19 pre-trained model for Keras

##VGG19 model for Keras

This is the Keras model of the 19-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

@panovr
panovr / readme.md
Created May 15, 2016 10:50 — forked from baraldilorenzo/readme.md
VGG-16 pre-trained model for Keras

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

@panovr
panovr / caffe_feature_extractor.py
Created April 23, 2016 02:30 — forked from marekrei/caffe_feature_extractor.py
Caffe feature extractor
import numpy as np
import os, sys, getopt
# Main path to your caffe installation
caffe_root = '/path/to/your/caffe/'
# Model prototxt file
model_prototxt = caffe_root + 'models/bvlc_googlenet/deploy.prototxt'
# Model caffemodel file
@panovr
panovr / softmax.py
Created January 27, 2016 12:36 — forked from stober/softmax.py
Softmax in Python
#! /usr/bin/env python
"""
Author: Jeremy M. Stober
Program: SOFTMAX.PY
Date: Wednesday, February 29 2012
Description: Simple softmax function.
"""
import numpy as np
npa = np.array
#include <opencv2/opencv.hpp>
#include <iostream>
#include <vector>
#include <cmath>
#include <assert.h>
using namespace std;
using namespace cv;