Image Recognition

Computer vision enables machines to interpret and understand visual information from images and videos.

Syntax

AI

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from tensorflow.keras.applications import ResNet50
from tensorflow.keras.preprocessing import image

model = ResNet50(weights='imagenet')
img = image.load_img('photo.jpg', target_size=(224, 224))

Image Classification Concept

PYTHON

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# Concept: pixel-based classification
def simple_image_classifier(pixels):
    avg_brightness = sum(pixels) / len(pixels)

    if avg_brightness > 200:
        return "Bright image (likely sky/snow)"
    elif avg_brightness > 100:
        return "Medium brightness (normal photo)"
    else:
        return "Dark image (night/shadow)"

# Simulate 8x8 grayscale image
dark_image = [30] * 64
bright_image = [220] * 64
normal_image = [128] * 64

print(simple_image_classifier(dark_image))
print(simple_image_classifier(bright_image))
print(simple_image_classifier(normal_image))

Try It Yourself

Practice

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Exercise

Practice this concept.

Answer

Write the code as shown above.

Quick Quiz

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What did you learn?

Concept A

Concept B

Concept C

Concept D

This covers the basics.

Retry Quiz

Interview Questions

Explain this concept.

It is a fundamental AI feature.

Next Lesson

Object Detection