Week 2: Image Processing 1

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## Images as Arrays

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### RGB Images

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<img style="width:70%" src="../../images/lenna_rgb.jpg">

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### Scaler Images

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<img style="width:70%" src="../../images/lenda_gray.jpeg">

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### Binary Images

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<img style="width:70%" src="../../images/lenda_binary.jpg">

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#### Converting from RGB to Grayscale

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<img style="width:80%" src="../../images/sphinx_rgb.png">

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#### Cont'd

For each RGB pixel, we compute:

$$ I = \big[0.299, 0.587, 0.114\big] . \big[R, G, B\big]^T$$

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```python
def rgb2gray(rgb_image):
    return np.dot(rgb_image[...,:3], [0.299, 0.587, 0.114])
```

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#### Results

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<img style="width:80%" src="../../images/sphinx_gray.png">

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### Converting from Grayscale to Binary Image

#### Thresholding

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```python
def binarize( gray_image , threshold ):
    threshold = np.max( gray_image ) * threshold
    return 1 * ( gray_image > threshold )
```

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#### Results

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<img style="width:80%" src="../../images/sphinx_bin.png">

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### Hyperspectral Images

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Pixels in Hyperspectral images consists of many channels.

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<img style="width:100%" src="../../images/stones_hsi.png">

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### Cont'd

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## Mean and Variance

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```python
print( np.mean( image ))

print( np.std( image ))
```

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## Profiles

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<img style="width:80%" src="../../images/pegion_profile.png">

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## Edges
### First-Order Derivatives

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$$ \begin{bmatrix}
\frac{\partial f}{\partial x} \\
\frac{\partial f}{\partial y}
\end{bmatrix} $$

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where:

$$\textstyle\frac{\partial f}{\partial x}$$ is the derivative with respect to x (gradient in the x direction)

$$\textstyle\frac{\partial f}{\partial y}$$ is the derivative with respect to y (gradient in the y direction).

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#### Results

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<img style="width:80%" src="../../images/cat_gradient.png">

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## Computer Vision Opportunities in Egypt

### Internship at [{Affectiva}](https://www.affectiva.com)

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<img style="width:80%" src="../../images/affectiva.png">

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[{Internship 1: Machine Learning}](https://www.affectiva.com/machine-learning-intern/)

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[{Internship 2: Empath Summer Internship}](https://www.affectiva.com/empath-high-school-summer-internship-program-at-affectiva/)

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A very interesting talk by *Rana Elkaliouby* about Affectiva:

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### 360imaging in Egypt

[{Website}](http://www.360imaging.com/)

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* Planned Dental Surgeries.
* They demand highly skilled C++ developers.
* Computer Vision background is a plus
* They offer opportunities through Wuzzuf.

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### Egyptian AI & Big Data Geeks

#### Follow the latest news, technologies, and vacancies in Egypt

[{Egyptian AI & Big Data Geeks}](https://www.facebook.com/groups/big.data.egypt/?hc_ref=ARRdEaEGxIrwkMjEnvNxD81ZxbGlFmE6i92Dd4Vdw0vboAUOg05qsCcMkLJNv3-28OE)

Also visit the [{**pinned** post}](https://www.facebook.com/groups/big.data.egypt/permalink/1762260707366456/) for lots of info about many related topics.

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## Resources

* [{Awsome Computer Vision}](https://github.com/jbhuang0604/awesome-computer-vision), **+5K** starts.
* [{Awesome Machine Learning}](https://github.com/josephmisiti/awesome-machine-learning), **30K** starts.

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## Interesting Application: Artistic Flavor

### Neural Doodle

[Neural Doodle](https://github.com/alexjc/neural-doodle)