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License: MIT License
This is the Saral community repo where docs, discussions, and issue tracker is enabled.
License: MIT License
Reduce Saral App bundle/APK size
Options to consider:
gradle.properties
android.enableR8=true
build.gradle
shrinkResources enableProguardInReleaseBuilds
zipAlignEnabled enableProguardInReleaseBuilds
useProguard enableProguardInReleaseBuilds
// resConfigs "en"
minifyEnabled enableProguardInReleaseBuilds
proguardFiles getDefaultProguardFile("proguard-android-optimize.txt"), "proguard-rules.pro"
As deployer/Maintainer maintain Unit Tests for Reference Backend
Multi-user support in reference backend as configured in u.p. Backend implementation
Locking the exams for scanning(recommendation from u.p implementation)
Tentative Dev Completion Date: 28th Nov 2022
Anganawadi beneficiary growth Monitoring Layout Design,ROI Generation,Testing
Upgrade deprecated packages and fix security vulnerabilities
Current status:
Originally posted by karsood August 19, 2022
Observation: With students filling out the OMR form, bringing the control on choice of pen will require extreme admin control.
Desire: Enhanced accuracy for blue ink + other colours
To Support Non-Black Pen,Pencil filled OMR Detection as experimental feature that can be enabled with flag in layout roi json
As a user, I should be able to review the scanned results for a student/layout.
Login API Auth token should have actual school or orgId as userId instead of mongo internal id .
when we are skipping a student id then same student id on next page should not show error message "ID Shouldn't be duplicated":
Tentative Dev Completion Date: 25th Nov 2022
Saral App global Cache clear functionality:
As deployer/Maintainer I should be able to improve Handwritten Digits Accuracy by experimenting with open and synthetic datasets - Iteration 3. Expected accuracy improvement is approximately 3% to 5%.
As a deployer/Maintainer, I should be able to improve the Handwritten Block letter Alphanumeric model Accuracy with production datasets - Iteration 3 :
Pre-requisite: Get handwritten layout sheets from the field with different users (considering demographics like gender, geography etc. of the users)
Block Letter English Alphabets Detection through Saral App
As a deployer/Maintainer, load test the reference backend APIs, fine-tune code and config, and publish the recommendations to scale.
Personal Details Layout generation , configuration, testing with Alphanumeric block letters support
As deployer/Maintainer experiment on a free English text extraction model that can be embedded into Saral SDK/Reference App.
Use a custom TensorFlow Lite model on Android support using the below approach. This will add a new deployment model to upgrade to a new version of ML models dynamically without changing the app.
https://firebase.google.com/docs/ml/android/use-custom-models
As a deployer/Maintainer profile the Reference Backend Code for production readiness
As deployer/Maintainer I should be able to improve the Handwritten Digits model Accuracy with production datasets - Iteration 4 :
As deployer/Maintainer I should be able to improve Handwritten Digits Accuracy by experimenting with open and synthetic datasets - Iteration 4.
Pre-requisite: Get handwritten layout sheets from the field with different users (considering demographics like gender, geography etc. of the users)
Document steps on how to replace the default saral app icon for a given implementation.
Once steps are reviewed, can be included in the below microsite link.
https://saral.sunbird.org/use/generate-aab-app-bundle-from-source-code
Conditional App building strategy based on the models/features to be supported.
Reduce size of assets
Clean up unwanted assets if any
As deployer/Maintainer profile reference backend code and finetune the code for production readiness:
As deployer/Maintainer performance tune Reference Backend MongoDB Layer
Anganawadi Benificiary Details Layout Design,ROI Generation and Verification
As a user, I should be able to review the saved results for a student/layout.
Tentative Dev Completion Date: 5th Dec
ExamId to be populated by Saral App while invoking saveMarks API
As deployer/Maintainer I should be able to improve the Handwritten Block letter Alphanumeric model Accuracy by experimenting with open and synthetic datasets - Iteration 2.
Note: Expected accuracy improvement is approximately 3% to 5%.
Originally posted by karsood September 22, 2022
As of today, there are three selections that are made after logging in: Class, Section, and Subject.
With some states going for repeated examination using different sets (set A, set B, set C, set D), can we have sets come up as a selection after the subject is selected?
Benefit: This will help reduce selection error by the teacher.
If there are no sets for a round of examination in a state, the default entry can be A, as we have it for section selection.
Upgrade Async storage version in Saral App
As deployer/Maintainer I should be able to have all Saral ML Data preparation, Training, and Inferencing pipelines as part of the Saral repository.
Back button to be added for Save Status and Scan Status Screens
Saral SDK demo app scan results screen
Student Absent/Present marking is to be done offline and synced with the backend during final marks upload using /saveMarks API
Tentative Dev Completion Date: 28th Nov 2022
To support Saral App in areas where internet coverage is limited, offline mode support is to be added:
SaralSDK demo app scan results screen
App force updates when a new version of the app is available in the play store.
Multi-student 11-digit 10 Question OMR sheet for Jharkhand requirement
Switch option between the minimal and regular mode in Saral App
Saral App share multiple student marks feature for troubleshooting
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