Computer Vision – Teaching Machines to See the World

What Is Computer Vision?

Computer Vision (CV) is a field of Artificial Intelligence that enables machines to see, interpret, and understand visual information, just like humans.

 ✅ It uses cameras, algorithms, and AI to process images or video
✅ Recognizes objects, people, gestures, text, and more
✅ Powers apps like facial recognition, smart cameras, and medical imaging

📸 1. What Can Computer Vision Do?

 ✅ Object Detection – Identify and locate objects in images
✅ Image Classification – Predict what’s in a photo (e.g., “dog”, “car”)
✅ Facial Recognition – Recognize people from face images
✅ OCR – Read text from images (e.g., ID cards)
✅ Motion Detection – Spot changes in video
✅ Scene Understanding – Identify scenes (street, classroom, etc.)

🧠 2. Real-World Use Cases (Global + Ethiopia)

In Ethiopia, CV can support agriculture, security, healthcare, and education systems.

🔧 3. Popular Python Libraries for CV

🔍 4. Basic CV Workflow

Capture or Load Image
import cv2

img = cv2.imread("photo.jpg")

1. Preprocess ✅ Resize, grayscale, remove noise

2. Feature Extraction ✅ Detect edges, shapes, or faces

3. Classification or Detection ✅ Use AI model to identify what's in the image

4. Display or Save Result ✅ Show processed image or save to file

📷 5. Key Concepts in CV

🧠 6. Deep Learning in Computer Vision

Modern CV uses Convolutional Neural Networks (CNNs) for:

 ✅ High accuracy in image classification
✅ Object detection (YOLO, SSD)
✅ Semantic segmentation (coloring each pixel based on class)

Example:

from tensorflow.keras.applications import MobileNetV2

model = MobileNetV2(weights="imagenet")

📦 7. Projects You Can Build

 ✅ Face detection for class attendance
✅ Object counting (e.g., sheep or cattle)
✅ Sign language or gesture recognition
✅ OCR to digitize Amharic books or IDs
✅ Smart farming app using plant image classification

💼 Careers in Computer Vision

 ✅ CV Engineer
✅ AI/ML Engineer
✅ Robotics Developer
✅ Automation System Designer
✅ Data Annotation Specialist
✅ Image Processing Researcher

🌐 Bonus: CV Challenges in Ethiopia

 ✅ Low-resolution images
✅ Multilingual text (Amharic, Afaan Oromo)
✅ Lack of labeled datasets
✅ Limited access to GPU computing

But with growing interest and global tools, CV is becoming more accessible to African developers.