Week 1: Introduction to Python and Images

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# Information about your TAs

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* Asem Alaa and Ayman Anwar, graduates of 2016 class.
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* e-mail: `asem.a.abdelaziz@gmail.com`
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* e-mail: `ayman.anwar.bio@gmail.com`
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* Office hours and materials are available on the course page.
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* Asem`s main research interests: Bioinformatics Algorithms and Machine Learning
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* Ayman`s main research interests: Neuroinformatics and Machine Learning.

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# Attendance

* Attendance is a requirement to pass the courses.
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* Not showing in more than 25% of lectures or tutorials is penalized by failing in the course.

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# .red[Cheating] 
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## be it in exams or assignments

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* [{الغش في الامتحانات | دار الإفتاء المصرية}](http://dar-alifta.org/AR/ViewFatwa.aspx?ID=13501&LangID=1)
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* [{الغش فى الامتحانات |  سقفية الشباب بالكنيسة القبطية الأرثوذكسية}](https://youthbishopric.com/%D8%A7%D9%84%D8%BA%D8%B4-%D9%81%D9%89-%D8%A7%D9%84%D8%A7%D9%85%D8%AA%D8%AD%D8%A7%D9%86%D8%A7%D8%AA/)

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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 Opportunity

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

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<blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">📢⁉️ Calling all interns! Looking for a <a href="https://twitter.com/hashtag/Boston?src=hash&ref_src=twsrc%5Etfw">#Boston</a> –based <a href="https://twitter.com/hashtag/engineering?src=hash&ref_src=twsrc%5Etfw">#engineering</a> <a href="https://twitter.com/hashtag/internship?src=hash&ref_src=twsrc%5Etfw">#internship</a>? We are offering exciting opportunities in 2019, see all our openings here!  <a href="https://t.co/iMdBXzMcfz">https://t.co/iMdBXzMcfz</a></p>— Rana el Kaliouby (@kaliouby) <a href="https://twitter.com/kaliouby/status/1088185353180274696?ref_src=twsrc%5Etfw">January 23, 2019</a></blockquote>

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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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## 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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## Demo files

```bash
$ git clone https://github.com/sbme-tutorials/sbe401-week2-demo.git
```

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## Assignment

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* Assignment [{page}](/2019/cv/assignments/1_assignment1.html)
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* Deadline: **Thursday 26/2/2019 10:00 AM.**