🎯 OpenCV Computer Vision Practice (Python)

Master OpenCV from Pixels to Real-World Projects in 17 Hands-on Chapters
OpenCV 计算机视觉实战 — From Basics to Deep-Learning-Powered Vision

🇬🇧 English • 🇨🇳 中文

Highlights • Curriculum • Quick Start • Showcase • Learning Path • Contributing

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📖 About This Repository

A progressive, project-driven OpenCV learning repository. It walks you from the very basics — reading an image, thresholding, morphology — all the way to production-flavored projects: credit-card OCR, panorama stitching, parking-spot detection, exam-sheet grading, deep-learning inference with the DNN module, multi-object tracking, and drowsiness detection.

Every chapter ships with:

• ✅ Runnable Python code (built on opencv-python / numpy)
• ✅ Bundled images & videos — clone the repo and reproduce results instantly
• ✅ A matching long-form article (Chinese WeChat column, linked in the table below)

💡 Who is this for? CV beginners, engineers brushing up traditional vision, students preparing for CV interviews, and developers who want to combine classical OpenCV with modern deep learning.

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✨ Highlights

🚀 17 Progressive Chapters	🛠 9+ End-to-End Projects	📦 Batteries Included
Smooth difficulty curve from pixel ops to DNN inference	Credit-card OCR · panorama · parking lot · OMR · drowsiness · more	Data, models and code — just python xxx.py

📝 Article per Chapter	🎓 Classic CV + Deep Learning	🌱 Actively Maintained
Each chapter has a deep-dive article explaining theory & code	Harris / SIFT / Optical Flow + Caffe / dlib / DNN	Issues and PRs warmly welcomed

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📚 Curriculum

#	Chapter	Keywords	Companion Article	Code Folder
01	Introduction	Roadmap & motivation	📖 Kickoff post	—
02	Image Basics	Read image / video · ROI · channels · blending · padding	📖 Image Basics	Chapter 2
03	Thresholding & Smoothing	Binarization · mean / Gaussian / median blur	📖 Thresholding & Smoothing	Chapter 3
04	Morphological Operations	Erode · Dilate · Open / Close · Top-hat / Black-hat	📖 Morphology	Chapter 4
05	Image Gradients	Sobel · Scharr · Laplacian	📖 Gradients	—
06	Edge Detection	Canny full pipeline	📖 Edge Detection	—
07	Pyramids & Contours	Gaussian / Laplacian pyramid · contour approximation	📖 Pyramids & Contours	—
08	Histograms & Fourier Transform	Histogram · DFT · frequency-domain filtering	📖 Histograms & Fourier	—
09	💳 Project 1: Credit-Card OCR	Template matching · morphology · perspective	📖 Credit-Card OCR (with code)	Chapter 9
10	Corner Detection	Harris	📖 Harris Corners	Chapter 11
11	SIFT Features	Scale-invariant feature transform	📖 SIFT	Chapter 12
12	🌄 Project 2: Panorama Stitching	Feature matching · homography · Stitcher	📖 Panorama Stitching	Chapter 13
13	🅿️ Project 3: Parking-Spot Detection	Video processing · CNN classification · occupancy state	📖 Parking Lot	Chapter 14
14	📝 Project 4: OMR Sheet Grading	Perspective transform · contour sorting · bubble detection	📖 OMR / Answer Sheet	Chapter 15
15	🎥 Project 5: Background Subtraction	MOG2 · KNN · foreground extraction	📖 Background Modeling	Chapter 16
16	🎞 Project 6: Optical Flow	Lucas-Kanade optical flow	📖 Optical Flow	Chapter 17
17	🧠 Project 7: OpenCV DNN	Caffe · GoogleNet · image classification	📖 OpenCV DNN	Chapter 18
18	🚗 Project 8: Multi-Object Tracking	dlib · multithreaded tracking	code only	Chapter 19
19	😴 Project 9: Drowsiness Detection	Facial landmarks · EAR · blink / yawn detection	code only	Chapter 21

⭐ Found it useful? Drop a Star so more people can discover it!

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🚀 Quick Start

1. Clone the repository

git clone https://github.com/tinyzqh/Opencv-Computer-Vision-Practice-Python-.git
cd Opencv-Computer-Vision-Practice-Python-

2. Install dependencies

We recommend an isolated environment with conda or venv:

pip install -r requirements.txt

That single file pulls everything you need: OpenCV (contrib build, for SIFT and legacy trackers), NumPy, Matplotlib, imutils, PyTorch + torchvision (for Chapter 14), dlib and SciPy (for Chapter 19 & 21).

Click to expand — manual install

# Core
pip install "opencv-contrib-python>=4.5,<5.0" numpy matplotlib

# Extras used by selected chapters
pip install imutils                       # Chapter 9 / 15
pip install torch torchvision             # Chapter 14 — Parking Lot (PyTorch)
pip install dlib scipy                    # Chapter 19 / 21 — Tracking & Drowsiness

✅ Tested on Python 3.12 + OpenCV 4.13 + PyTorch 2.11 + NumPy 2.4. All 32 example scripts run end-to-end. The codebase has been adapted to modern OpenCV 4.x (new findContours return shape, cv2.legacy.* trackers, strict integer coordinate types) — no version pinning gymnastics required.

3. Run any example

# Credit-card OCR
cd "Chapter 9"
python ocr_template_match.py --image images/credit_card_01.png --template ocr_a_reference.png

# Panorama stitching
cd "Chapter 13"
python ImageStiching.py

# Background subtraction
cd "Chapter 16"
python "back model.py"

# Parking-spot detection (Chapter 14) — two-step
cd "Chapter 14"
python train.py           # transfer-learning a VGG16 classifier (~90% val acc)
python park_test.py       # run the full detection + classification pipeline

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🖼 Project Showcase

Project	What You Will Learn	Folder
💳 Credit-Card OCR	Combine template matching with morphology to solve real-world OCR	Chapter 9
🌄 Panorama Stitching	SIFT keypoint matching + homography + image blending	Chapter 13
🅿️ Parking-Spot Detection	Classical CV to segment ROIs + a PyTorch VGG16 transfer-learning classifier (90%+ val acc) — end-to-end	Chapter 14
📝 OMR Sheet Grading	Perspective rectification + contour sorting + bubble recognition	Chapter 15
🧠 DNN Image Classification	Load a Caffe model directly from OpenCV — no DL framework needed	Chapter 18
🚗 Multi-Object Tracking	dlib correlation tracker + multithreading for real-time tracking	Chapter 19
😴 Drowsiness Detection	68-point facial landmarks + EAR — build a tiny app that keeps you awake	Chapter 21

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🗺 Learning Path

Basics (Ch.2~4)
        │
        ▼
Feature Engineering (Ch.5~8) ──► Histograms / Frequency / Edges / Contours
        │
        ▼
Keypoint Detection (Ch.10~11) ──► Harris / SIFT
        │
        ├──► 💳 First project: Credit-Card OCR (Ch.9)
        │
        ▼
Registration & Stitching (Ch.12) ──► 🌄 Panorama
        │
        ▼
Video & Temporal Vision (Ch.16~17) ──► 🎥 Background Subtraction / 🎞 Optical Flow
        │
        ├──► 🅿️ Parking-Spot Detection (Ch.14)
        ├──► 📝 OMR Sheet Grading (Ch.15)
        │
        ▼
Meets Deep Learning (Ch.18~21) ──► 🧠 DNN / 🚗 Multi-Tracking / 😴 Drowsiness

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📦 Repository Structure

Opencv-Computer-Vision-Practice-Python-/
├── Chapter 2/   # Image basics (I/O, ROI, channels, blending, padding)
├── Chapter 3/   # Thresholding
├── Chapter 4/   # Morphology (erode / dilate / open / close / gradient / hat)
├── Chapter 9/   # 💳 Credit-Card OCR
├── Chapter 11/  # Harris corners
├── Chapter 12/  # SIFT & feature matching
├── Chapter 13/  # 🌄 Panorama stitching
├── Chapter 14/  # 🅿️ Parking-spot detection (with CNN training data)
├── Chapter 15/  # 📝 OMR sheet grading
├── Chapter 16/  # 🎥 Background subtraction
├── Chapter 17/  # 🎞 Optical flow
├── Chapter 18/  # 🧠 OpenCV DNN (Caffe / GoogleNet)
├── Chapter 19/  # 🚗 Multi-object tracking (dlib + multithreading)
├── Chapter 21/  # 😴 Drowsiness & blink detection
├── requirements.txt   # one-shot pip install
├── COMPATIBILITY.md   # OpenCV 4.x / NumPy 2 / PyTorch porting notes
├── README.md          # English (default)
└── README_CN.md       # 中文版

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🛠 Troubleshooting

Running into a findContours unpack error, a missing TrackerKCF_create, or a Keras import in Chapter 14? See COMPATIBILITY.md — every porting tweak (and the modern API it now uses) is documented there.

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🤝 Contributing

The material is based on notes from the NetEase Cloud Classroom course 《OpenCV Computer Vision Practice》, reorganized and extended with comments and additional examples.

You are very welcome to contribute in any form:

• 🐞 Found a bug or broken example? — open an Issue
• ✨ Want to add a new project? — send a PR
• 📝 Notes / typo fixes / extra explanations? — PR the README or add a notes/ folder
• ⭐ Got value out of it? — a Star is the simplest and most powerful thank-you

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📜 License

• The code in this repository is released under the MIT License — feel free to study, modify and build on it.
• The companion WeChat articles are shared for educational purposes and do not necessarily reflect the platform's views.
• Any referenced course material remains copyright of the original course authors. Please contact the maintainer if you believe there is an infringement.

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If this repo helped you skip a few miles of detours, please consider giving it a ⭐ Star — so it can light the path for other learners.

_{Made with ❤️ for everyone who loves computer vision.}