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L0 Zero
Afonso Diela edited this page Sep 17, 2024
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These challenges introduce fundamental computer vision concepts and hands-on projects for beginners.
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- Description: Learn the basics of working with images in Python. Load images, display them, and perform basic transformations like rotations, color conversions, and more.
- Key Concepts: Image loading, transformations, color models, OpenCV basics.
- Notebook: Open in Colab
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- Description: Modify pixel values, resize, flip, crop, and add annotations to images using OpenCV. Develop a basic understanding of pixel-level operations.
- Key Concepts: Resizing, cropping, flipping, drawing on images, pixel-level access.
- Notebook: Open in Colab
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- Description: Apply filters to enhance or manipulate image features. Experiment with blurring, sharpening, and noise removal techniques.
- Key Concepts: Image filtering, noise removal, sharpening, Gaussian filters.
- Notebook: Open in Colab
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- Description: Use arithmetic and bitwise operations to enhance images. Learn how to apply operations like image addition, subtraction, and more.
- Key Concepts: Bitwise operations, image enhancement, pixel-level operations.
- Notebook: Open in Colab
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Image Segmentation (Traditional)
- Description: Learn about traditional image segmentation techniques to divide an image into meaningful parts (regions or objects).
- Key Concepts: Thresholding, edge detection, contour detection.
- Notebook: Open in Colab
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Feature Extraction & Alignment
- Description: Extract features using various descriptors and align them for matching or comparison tasks.
- Key Concepts: Feature extraction, keypoints, feature matching.
- Notebook: Open in Colab
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Optical Character Recognition (OCR)
- Description: Learn to recognize and extract text from images using OCR libraries like Tesseract, PyTesseract, and EasyOCR.
- Key Concepts: OCR, text extraction, image-to-text conversion.
- Notebook: Open in Colab