https://github.com/hariprasath-v/lacuna_malaria_detection_challenge
classifying malaria parasites in blood slide images.
https://github.com/hariprasath-v/lacuna_malaria_detection_challenge
exploratory-data-analysis object-detection pandas python zindi
Last synced: 6 months ago
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classifying malaria parasites in blood slide images.
- Host: GitHub
- URL: https://github.com/hariprasath-v/lacuna_malaria_detection_challenge
- Owner: hariprasath-v
- License: mit
- Created: 2024-11-24T04:21:57.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-11-24T04:39:34.000Z (11 months ago)
- Last Synced: 2025-02-07T13:44:44.679Z (8 months ago)
- Topics: exploratory-data-analysis, object-detection, pandas, python, zindi
- Language: Jupyter Notebook
- Homepage:
- Size: 12 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Lacuna Malaria Detection Challenge
# About
The objective of this challenge is to develop a multiclass object detection and classification model that can accurately identify and classify malaria parasites in blood slide images, specifically addressing diagnostic needs in Africa. Participants are required to create a machine learning model that can detect the trophozoite stage of malaria, and differentiate between infected and uninfected blood cells.
Competition hosted on [Zindi](https://zindi.africa/competitions/lacuna-malaria-detection-challenge)
# My approach
### Exploratory Data Analysis
- Target analysis
- Bounding box center analysis
- Bounding box aspect ratio analysis
- Bounding box width & height
- Overlapping bounding box analysis
- Bounding box area analysis
- Bounding box anchor analysis
- Basic image information analysis
- Test data analysis
EDA Notebook[](https://www.kaggle.com/code/hari141v/lacuna-malaria-detection-challenge-eda)