Image Processing Desktop App Development
Budget: $10 – $30 USD
I'm looking for an experienced Python developer adept in creating Windows desktop applications. My project's primary focus is on image processing and the integration of a machine learning model.
Optiscan is a desktop application designed as a diagnostics assistant for eye care doctors. It facilitates the analysis of eye topography reports using machine learning models trained to recognize key values and patterns, determine normal and abnormal trends, and provide a printable final output. This document outlines the specific requirements for developing the Optiscan desktop application.
2. Functional Requirements
• Image Input: The application should allow the doctor to input up to 10 eye topography images at a time for analysis.
• Model Integration: The application should integrate with the pre-existing machine learning models coded in Python to analyse the input images and generate diagnostic results.
• Diagnostic Output: The application should display the diagnosis generated by the machine learning models in a user-friendly format on the interface.
• PDF Report Generation: The application should provide an option for the doctor to save the diagnostic report as a PDF file on their PC.
3. Non-functional Requirements
• Platform: The application should be developed to run on Windows operating systems.
• Performance: The application should be optimized for efficient processing of image analysis tasks.
• User Interface: The user interface should be intuitive and easy to navigate, catering to the specific needs of eye care professionals.
• Security: As the application will be deployed on the doctor's PC without server involvement, it should ensure data security and privacy.
4. Development Environment
Programming Language: The application must be coded in Python to integrate seamlessly with the existing machine-learning models.
Deployment: The application should be deployable directly on the doctor's PC without the need for server hosting.
Optiscan is a desktop application designed as a diagnostics assistant for eye care doctors. It facilitates the analysis of eye topography reports using machine learning models trained to recognize key values and patterns, determine normal and abnormal trends, and provide a printable final output. This document outlines the specific requirements for developing the Optiscan desktop application.
2. Functional Requirements
• Image Input: The application should allow the doctor to input up to 10 eye topography images at a time for analysis.
• Model Integration: The application should integrate with the pre-existing machine learning models coded in Python to analyse the input images and generate diagnostic results.
• Diagnostic Output: The application should display the diagnosis generated by the machine learning models in a user-friendly format on the interface.
• PDF Report Generation: The application should provide an option for the doctor to save the diagnostic report as a PDF file on their PC.
3. Non-functional Requirements
• Platform: The application should be developed to run on Windows operating systems.
• Performance: The application should be optimized for efficient processing of image analysis tasks.
• User Interface: The user interface should be intuitive and easy to navigate, catering to the specific needs of eye care professionals.
• Security: As the application will be deployed on the doctor's PC without server involvement, it should ensure data security and privacy.
4. Development Environment
Programming Language: The application must be coded in Python to integrate seamlessly with the existing machine-learning models.
Deployment: The application should be deployable directly on the doctor's PC without the need for server hosting.