https://github.com/eshan-sud/imagesense
A powerful platform for image processing, segmentation & recognition
https://github.com/eshan-sud/imagesense
eshan-sud image image-processing image-recognition image-segmentation python3
Last synced: 9 months ago
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A powerful platform for image processing, segmentation & recognition
- Host: GitHub
- URL: https://github.com/eshan-sud/imagesense
- Owner: eshan-sud
- License: mit
- Created: 2025-01-31T06:54:16.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-08-21T05:11:03.000Z (10 months ago)
- Last Synced: 2025-10-09T15:43:16.812Z (9 months ago)
- Topics: eshan-sud, image, image-processing, image-recognition, image-segmentation, python3
- Language: Python
- Homepage:
- Size: 22.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# ImageSense
A powerful platform for image processing & recognition.
## Software
- Python 3.13
- Streamlit
- OpenCV2
## Features & Details:
1. User Interface
- [x] Basic UI
- [x] Upload the image (JPG, PNG, SVG, WEBp)
- [x] Rename image file
- [x] Save image file
- [] Add undo, redo options
- [] Add the ability to share the image to other mediums
2. Image Preprocessing
- [x] Display the uploaded image
- [] Convert to grayscale & histogram equalization
- [] Image resize, crop, rotate, compression, contrast streching, colour processing, inpainting, fusion - Stable Diffusion
- [] Apply smoothing & sharpening filters (Gaussian, Median, Bilateral)
- [] Deblurring & Denoising
- [] Colouring & Declouring images - Using GANs
- [] Image reslution increases - Using GANs
- [] Professional photo generator from user's photo
3. Edge Detection & Segmentation
- [] Edge detection using Sobel, Prewitt, Laplacian, Canny
- [] Image thresholding (Global, Adaptive, Otsu's method)
- [] Segmentation using K-Means, Watershed, GrabCut
- [] Morphological operations (Erosion, Dilation, Opening, Closing)
4. Feature Extraction
- [] Extract & visualize key features using SIFT, SURF, ORB, HOG
- [] PCA-based dimensionality reduction visualization
- [] Compute texture features (GLCM, LBP)
- [] Histogram-based feature analysis
5. Pattern Recognition & Classification
- [] Train & test classifiers on extracted features
- [] Support for KNN, SVM, Decision Trees, CNN (Pretrained Models)
- [] Upload custom datasets for classification
- [] Evaluate models with accuracy, precision, recall
6. Face Detection & Recognition
- [] Detect faces using Haar Cascades, DNN (ResNet, MobileNet)
- [] Recognize faces using LBPH, Eigenfaces, Fisherfaces
- [] Live face recognition via webcam feed
7. Interactive Visualizations
- [] Show histograms, feature maps, contour plots
- [] Compare different image processing techniques side-by-side
- [] Display real-time classifier performance
8. API Integration & Deployment
- [] Allow image uploads via API for batch processing
- [] Deploy seamlessly on Streamlit Cloud
- [] Share app via public URL
## Setup (for devs)
```
python setup.py
```