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https://github.com/hs094/instance-segmentation-and-detection
A sophisticated computer vision application that performs real-time instance segmentation and object detection using a user-friendly Tkinter interface. The project identifies and isolates individual objects within images, providing both bounding box visualization and segmentation masks.
https://github.com/hs094/instance-segmentation-and-detection
matplotlib opencv pillow setuptools tkinter-gui torch torchvision
Last synced: 12 days ago
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A sophisticated computer vision application that performs real-time instance segmentation and object detection using a user-friendly Tkinter interface. The project identifies and isolates individual objects within images, providing both bounding box visualization and segmentation masks.
- Host: GitHub
- URL: https://github.com/hs094/instance-segmentation-and-detection
- Owner: hs094
- Created: 2024-11-30T08:33:10.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-11-30T08:53:15.000Z (about 1 month ago)
- Last Synced: 2024-12-22T14:16:20.153Z (12 days ago)
- Topics: matplotlib, opencv, pillow, setuptools, tkinter-gui, torch, torchvision
- Language: Python
- Homepage:
- Size: 3.2 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Instance Segmentation and Detection using a Tkinter-based interface
This project is a sophisticated computer vision application that performs real-time instance segmentation and object detection using a user-friendly Tkinter interface. The project identifies and isolates individual objects within images, providing both bounding box visualization and segmentation masks.
## Key Features
- Interactive GUI built with Tkinter for easy image processing
- Detects and highlights the top 3 most confident object instances
- Dual visualization modes:
- Bounding box detection with class labels
- Precise segmentation masks with custom color overlays
- Supports multiple image transformations:
- Blur
- Flip (horizontal/vertical)
- Rotate
- Crop (center/random)
- Rescale
## Technical Highlights
- Built on PyTorch's powerful deep learning framework
- Efficient image processing using NumPy and PIL
- Custom transformation pipeline for image preprocessing
- Confidence-based filtering for optimal detection results
- Clean architecture with modular design for easy extensibility
## Use Cases
- Object detection in natural scenes
- Instance segmentation for image analysis
- Educational tool for computer vision concepts
- Rapid prototyping of image processing workflows
## Dependencies
1. PyTorch
`pip3 install torch torchvision torchaudio`
2. Numpy
`pip3 install numpy`
3. Matplotlib
`pip3 install matplotlib`
4. Pillow
`pip3 install pillow`
5. mypackage-hs094
`pip3 install ./my_package_hs094-0.0.1-py3-none-any.whl`
### Notes
1. This software determines only the top 3 entities in the given image based on a confidence score. Other detected entities are not covered by segmentation masks or bounding boxes.
2. Temporary image files (1 for bounding box and 1 for segmentation mask) are saved to disk in the working directory during the runtime of the script. It is destroyed automatically afterwards.
## Screenshots
