Asep Haryana Saputra
15c6be9e84
- Extend shared types for image classification, including PredictionProbability, UploaderMetadata, and ImageClassificationRecord. - Create image_classifications table in the database with necessary fields and foreign key constraints. - Implement disease mappers to convert database rows to shared disease records. - Develop uploader client to handle image uploads to external service. - Create image model service to load and classify images using TensorFlow.js. - Add API routes for image classification, including GET for history and POST for new classifications. - Implement frontend components for image classification form and display results. - Update dashboard to integrate image classification functionality and display results. - Document implementation plan for backend image classification.
47 lines
2.2 KiB
TypeScript
47 lines
2.2 KiB
TypeScript
import { pgTable, timestamp, uuid, varchar, text, integer, jsonb, real } from 'drizzle-orm/pg-core';
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export const appEvents = pgTable('app_events', {
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id: uuid('id').primaryKey().defaultRandom(),
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name: varchar('name', { length: 120 }).notNull(),
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createdAt: timestamp('created_at', { withTimezone: true }).notNull().defaultNow(),
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});
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export const diseaseCatalog = pgTable('disease_catalog', {
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slug: varchar('slug', { length: 80 }).primaryKey(),
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label: varchar('label', { length: 80 }).notNull(),
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commonName: varchar('common_name', { length: 120 }).notNull(),
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summary: text('summary').notNull(),
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description: text('description').notNull(),
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symptoms: text('symptoms').array().notNull(),
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recommendations: text('recommendations').array().notNull(),
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riskLevel: varchar('risk_level', { length: 20 }).notNull(),
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accentColor: varchar('accent_color', { length: 40 }).notNull(),
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displayOrder: integer('display_order').notNull(),
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createdAt: timestamp('created_at', { withTimezone: true }).notNull().defaultNow(),
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updatedAt: timestamp('updated_at', { withTimezone: true }).notNull().defaultNow(),
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});
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export const manualClassifications = pgTable('manual_classifications', {
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id: uuid('id').primaryKey().defaultRandom(),
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diseaseSlug: varchar('disease_slug', { length: 80 })
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.notNull()
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.references(() => diseaseCatalog.slug),
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observation: text('observation').notNull(),
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location: varchar('location', { length: 160 }).notNull(),
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createdAt: timestamp('created_at', { withTimezone: true }).notNull().defaultNow(),
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});
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export const imageClassifications = pgTable('image_classifications', {
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id: uuid('id').primaryKey().defaultRandom(),
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predictedDiseaseSlug: varchar('predicted_disease_slug', { length: 80 })
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.notNull()
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.references(() => diseaseCatalog.slug),
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confidence: real('confidence').notNull(),
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probabilities: jsonb('probabilities').notNull(),
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imageUrl: text('image_url').notNull(),
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originalFileName: varchar('original_file_name', { length: 240 }).notNull(),
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uploaderPublicId: varchar('uploader_public_id', { length: 160 }).notNull(),
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uploaderPayload: jsonb('uploader_payload').notNull(),
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createdAt: timestamp('created_at', { withTimezone: true }).notNull().defaultNow(),
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});
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