🧠 Objective Detect and highlight differences between before and after images of the same scene by drawing bounding boxes around changed regions.

📁 Folder Structure arduino Copy Edit . ├── task_2_code.py ← Python script to run the detection ├── task_2_output/ ← Folder containing input and output images │ ├── 1.jpg ← Input "before" image │ ├── 13.jpg ← Output: "after" image with bounding boxes │ ├── 2.jpg │ ├── 23.jpg │ └── ... ⚠️ X~2.jpg (original after image) is used internally but not stored in the final output.

🚀 How to Run

1. Install dependencies (once):

pip install -r requirements.txt

2. Place images in the task_2_output/ folder:

Before image: X.jpg After image: X~2.jpg

3. Run the script:

python task_2_code.py

The script will generate: X~3.jpg: Annotated image showing the changes It will also ensure X.jpg is retained in the folder

🧪 How It Works Converts both images to grayscale and applies Gaussian blur.

Computes differences using: cv2.absdiff (raw pixel difference) SSIM (structural difference)

Combines both masks and applies morphological operations to reduce noise.

Detects contours and draws bounding boxes using smart filtering: Area threshold Aspect ratio Solidity Pixel change ratio inside each box

📦 Dependencies See requirements.txt: opencv-python numpy scikit-image