Metadata-Version: 2.4
Name: cvlab-practical-toolkit
Version: 1.0.0
Summary: Computer Vision Lab Practical Toolkit & CLI
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: opencv-python
Requires-Dist: numpy<2
Requires-Dist: matplotlib

# Computer Vision Practical Handbook & `cvlab` CLI Toolkit

A scenario-based laboratory engineering handbook and command-line toolkit (`cvlab`) designed for undergraduate Computer Science students.

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## 💻 `cvlab` CLI Toolkit Quick Start

Install locally in editable mode to use the `cvlab` command from any terminal prompt:

```bash
# 1. Install dependencies and CLI toolkit
pip install -e .

# 2. Launch Interactive Terminal Menu
cvlab

# 3. Direct Command Shortcuts (Instant Execution)
cvlab face                    # Run Face Detection with sample dataset
cvlab ocr                     # Run Scene Text Detection (OCR)
cvlab vehicle "my_traffic.mp4" # Run Vehicle Detection on custom video (drag & drop path)
cvlab lane "road.jpg"         # Run Road Lane Detection
cvlab qr                      # Run QR Code Scanner
cvlab batch                   # Batch process an entire folder of images
```

---

## 📦 Features

- **⚡ Instant Subcommands**: Execute any experiment instantly with shortcuts like `cvlab face`, `cvlab ocr`, `cvlab vehicle`, `cvlab qr`, `cvlab lane`, `cvlab motion`, etc.
- **📂 Drag & Drop File Path Support**: Drag and drop any image/video file directly into the command prompt. Quotes (`"..."`) are automatically sanitized.
- **🧪 Built-in Sample Datasets**: Includes sample test images for all 16 experiments in `cvlab/samples/` so you can test offline without webcams or external downloads.
- **⚡ Batch Processing Mode (`cvlab batch`)**: Process an entire directory of test images in a single step and output annotated panels.
- **📊 Automatic Panel Generation**: Generates annotated side-by-side comparison images saved automatically in `outputs/`.

---

## Handbook Structure

- `cvlab/`: Python package containing CLI runner (`cli.py`), batch processor (`batch.py`), command handlers, and sample datasets.
- `handbook/`: Detailed laboratory chapter documentation (16 Experiments + 10 Reference Chapters).
- `experiments/`: Executable stand-alone Python scripts (`main.py`) for all 16 experiments.
- `pyproject.toml` & `requirements.txt`: Package configuration and dependencies.

---

## Experiments Index

1. Basic Image Handling (`cvlab basic`)
2. Image 2D to 3D Conversion (`cvlab 3d`)
3. Motion Detection (`cvlab motion`)
4. Image Captioning (`cvlab caption`)
5. Vehicle Detection (`cvlab vehicle`)
6. Contour Segmentation (`cvlab contour`)
7. Region Based Segmentation (`cvlab region`)
8. Social Distancing Application (`cvlab social`)
9. Shape Detection (`cvlab shape`)
10. Face Detection (`cvlab face`)
11. Scene Text Detection (`cvlab ocr`)
12. Road Lane Detection (`cvlab lane`)
13. Emotion Recognition (`cvlab emotion`)
14. People Counting (`cvlab people`)
15. Vehicle Counting (`cvlab vcount`)
16. QR Code Scanner (`cvlab qr`)

---

## Reference Chapters Index

- **R1:** Master Scenario Decoder
- **R2:** OpenCV Function Cheat Sheet
- **R3:** Python Library Cheat Sheet
- **R4:** Model Download Checklist
- **R5:** requirements.txt
- **R6:** Installation Guide
- **R7:** Common Errors & Fixes
- **R8:** 100+ Viva Questions
- **R9:** Last-Minute Revision Sheet
- **R10:** Glossary of Computer Vision Terms
