Practical Computer Vision: Build Applications with OpenCV and YOLO

Master computer vision fundamentals, object detection, and tracking by writing clean Python code to build real-world detection and pose estimation applications.

4.1 (181) ⏱ 1 jam 38 min 📚 7 pelajaran 🎧 Versi audio

Tentang kursus ini

Computer vision is transforming industries from security to automation, but transitioning from theory to building functional applications can feel overwhelming. This text-based guide bridges that gap by teaching you how to write clean, efficient Python code for real-world visual data processing. You will start with the core mathematical and programming foundations of image processing before moving on to state-of-the-art deep learning models. By reading detailed explanations and analyzing structured code snippets, you will gain the skills to build, configure, and deploy computer vision pipelines that can detect, segment, and track objects in real time. What you'll learn: - Understand foundational image processing concepts including contours, perspective warping, and thresholding using OpenCV. - Build custom object detection pipelines using advanced architectures like YOLOv8 and YOLO-NAS. - Implement real-time object tracking and segmentation utilizing algorithms such as SORT and DeepSORT. - Apply pose estimation techniques with MediaPipe to track human movement and recognize gestures. - Configure modern Python virtual environments and write clean, type-hinted code suitable for production-ready vision pipelines. - Create practical applications like license plate detectors, lane trackers, and gesture-controlled interfaces. The course begins with essential terminology and basic pixel manipulation, ensuring you have a strong foundation before progressing to advanced deep learning models. You will progress through step-by-step written walkthroughs that demonstrate how to train models on custom datasets and optimize them for real-world performance. This course is designed for beginners, developers, and aspiring data scientists who want to learn computer vision from the ground up. No prior experience with image processing or machine learning is required, though a basic understanding of Python is helpful. Start reading today to build your first intelligent computer vision application.

Apa yang anda dapat

  • 📜 Sijil tamat
    Tambah ke profil LinkedIn anda
  • 🎧 Termasuk versi audio
    Belajar sambil bergerak — tanpa skrin
  • ♾️ Akses seumur hidup
    Kembali bila-bila masa, tiada tamat tempoh
  • 📱 Telefon atau komputer
    Berfungsi di mana-mana, mana-mana peranti
  • 💸 Pulangan 30 hari
    Tanpa soalan
  • Pendek dan fokus
    1 jam 38 min kandungan praktikal

Ulasan (3)

مريم خالد AE
★ 4 · 2026-04-06T10:25:56+00:00

Kandungan yang mantap dan disampaikan dengan jelas. Saya menghargai aplikasi dunia sebenar yang ditunjukkan. Boleh menggunakan beberapa peluang latihan.

Paula Navarro PE Pelajar disahkan
★ 5 · 2026-01-16T05:30:56+00:00

Kursus ini melebihi jangkaan saya. Aplikasi dunia sebenar yang dibincangkan sangat berguna. Kerja yang bagus!

Mariana Silva MX Pelajar disahkan
★ 5 · 2025-07-03T06:25:56+00:00

Saya suka contoh aplikasi praktikal. Tepat jenis pembelajaran praktikal yang saya cari.

Tulis ulasan

Selepas hantar kami akan meminta anda log masuk — draf disimpan.

Pelajar lain juga mengambil

Soalan lazim

Apa yang saya perlukan untuk mengikuti kursus ini? +

Hanya telefon atau komputer dengan internet. Tiada pemasangan, tiada perkakasan khas.

Bagaimana untuk membayar? +

Dengan kad melalui Stripe, atau kripto. Kami tidak menyimpan butiran kad — Stripe menguruskannya dengan selamat.

Bolehkah saya dapatkan bayaran balik? +

Ya — pulangan penuh dalam 30 hari, tanpa soalan.

Berapa lama saya akan mempunyai akses? +

Selamanya. Setelah membeli, kursus adalah milik anda — boleh lawat semula bila-bila masa.

Adakah saya akan mendapat sijil? +

Ya. Setelah tamat, anda akan menerima sijil yang boleh ditambah ke profil LinkedIn anda.

Direka untuk pelajar dalam
Teknologi Reka bentuk Kewangan Pemasaran Kesihatan Pendidikan Hospitaliti Pembuatan