sightmachine/SimpleCV — pull request #607 by lastlegion (2014-01-28 20:55:45+00:00)
Title: Added findHOGFeatures()

HOG(Histogram of Oriented Gradients) features are widely used in various Computer Vision and image processing for object detection.

Usage
```python
I = Image("lena.jpg")
H1 = I.findHOGFeatures()
H2 = I.findHOGFeatures(2,6)
```
For sample image:
![lena_color](https://f.cloud.github.com/assets/748711/2023588/cbea9764-885d-11e3-8923-ab147052eeb3.gif)
It would return the hog descriptor:
```
>H1
array([[ 0.70799777, 0.31031786, 0.43538802, 0.7119953 , 0.35283551,
0.44640515, 1.39636142, 0.66822192, 0.9737663 , 1.35927688,
0.61152601, 1.03855733, 1.69911792, 0.62897737, 1.92188941,
1.67472578, 0.63001834, 1.99064839, 0.84245818, 0.80247882,
0.79771883, 0.65534026, 0.76592214, 0.7464986 , 1.95349545,
0.73081933, 1.0270115 , 1.88424318, 0.86515135, 1.01216288,
0.79783098, 0.63841941, 0.56898374, 0.72427718, 0.6168658 ,
0.72017109, 0.89275505, 0.46247547, 0.58670203, 0.93734243,
0.41994468, 0.51827528, 0.95650341, 0.39389738, 0.71125951,
0.83805511, 0.4436618 , 0.74813277, 0.97483522, 0.36429496,
0.8730933 , 0.93598927, 0.48391781, 0.61659925]])
```
```
>H2
array([[ 2.3547329 , 1.24260293, 1.34765038, 2.16142711, 1.28855857,
1.59244553, 3.73639567, 1.53089352, 3.16332987, 3.63308637,
1.47675359, 3.25464767, 2.11491471, 1.1703252 , 1.68901189,
2.11247633, 1.32217436, 1.43717833, 2.09424087, 1.08864922,
1.72708496, 1.89273196, 1.13458106, 1.58801289]])
```