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Main API server for body measurement system\nimport { Hono } from \"https://esm.sh/hono@3.11.7\";\nimport { readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\nimport { PoseDetector } from \"./pose-detection.ts\";\nimport { BodyMeasurementCalculator } from \"./measurements.ts\";\nimport { validateImageData, validateReferenceHeight, calculateConfidenceScore, generateMeasurementReport } from \"./utils.ts\";\nimport type { MeasurementRequest, MeasurementResponse } from \"../shared/types.ts\";\n\nconst app = new Hono();\n\n// Unwrap Hono errors to see original error details\napp.onError((err, c) => {\n throw err;\n});\n\n// Initialize pose detector\nconst poseDetector = new PoseDetector();\n\n// Serve static files\napp.get(\"/frontend/*\", c => serveFile(c.req.path, import.meta.url));\napp.get(\"/shared/*\", c => serveFile(c.req.path, import.meta.url));\n\n// Serve main page\napp.get(\"/\", async c => {\n let html = await readFile(\"/frontend/index.html\", import.meta.url);\n \n // Inject initial data\n const dataScript = ``;\n \n html = html.replace(\"\", `${dataScript}`);\n return c.html(html);\n});\n\n// Main measurement endpoint\napp.post(\"/api/measure\", async c => {\n try {\n const body: MeasurementRequest = await c.req.json();\n \n // Validate input\n const imageValidation = validateImageData(body.imageData);\n if (!imageValidation.valid) {\n return c.json({\n success: false,\n error: imageValidation.error\n }, 400);\n }\n \n const heightValidation = validateReferenceHeight(body.referenceHeight);\n if (!heightValidation.valid) {\n return c.json({\n success: false,\n error: heightValidation.error\n }, 400);\n }\n \n // Detect pose landmarks\n const landmarks = await poseDetector.detectPose(body.imageData);\n if (!landmarks) {\n return c.json({\n success: false,\n error: \"Failed to detect pose in the image. Please ensure the person is clearly visible and standing upright.\"\n }, 400);\n }\n \n // Validate pose quality\n const poseValidation = PoseDetector.validatePose(landmarks);\n if (!poseValidation.valid) {\n return c.json({\n success: false,\n error: `Pose validation failed: ${poseValidation.issues.join(', ')}`\n }, 400);\n }\n \n // Calculate measurements\n const measurements = BodyMeasurementCalculator.calculateMeasurements(\n landmarks,\n body.referenceHeight,\n body.gender || 'male'\n );\n \n // Calculate confidence score\n const confidence = calculateConfidenceScore(landmarks);\n \n return c.json({\n success: true,\n measurements,\n landmarks,\n confidence\n });\n \n } catch (error) {\n console.error('Measurement calculation error:', error);\n return c.json({\n success: false,\n error: \"An error occurred while processing the image. Please try again.\"\n }, 500);\n }\n});\n\n// Get measurement report as text\napp.post(\"/api/report\", async c => {\n try {\n const body: MeasurementRequest = await c.req.json();\n \n // Validate input\n const imageValidation = validateImageData(body.imageData);\n if (!imageValidation.valid) {\n return c.text(imageValidation.error || \"Invalid image\", 400);\n }\n \n // Detect pose and calculate measurements\n const landmarks = await poseDetector.detectPose(body.imageData);\n if (!landmarks) {\n return c.text(\"Failed to detect pose in the image\", 400);\n }\n \n const measurements = BodyMeasurementCalculator.calculateMeasurements(\n landmarks,\n body.referenceHeight,\n body.gender || 'male'\n );\n \n const report = generateMeasurementReport(measurements);\n \n return c.text(report, 200, {\n 'Content-Type': 'text/plain; charset=utf-8',\n 'Content-Disposition': 'attachment; filename=\"body-measurements.txt\"'\n });\n \n } catch (error) {\n console.error('Report generation error:', error);\n return c.text(\"Failed to generate measurement report\", 500);\n }\n});\n\n// Health check endpoint\napp.get(\"/api/health\", c => {\n return c.json({\n status: \"healthy\",\n timestamp: new Date().toISOString(),\n version: \"1.0.0\"\n });\n});\n\n// API documentation\napp.get(\"/api/docs\", c => {\n const docs = {\n title: \"Body Measurement API\",\n version: \"1.0.0\",\n endpoints: {\n \"POST /api/measure\": {\n description: \"Calculate body measurements from an image\",\n body: {\n imageData: \"string (base64 encoded image)\",\n referenceHeight: \"number (optional, height in cm)\",\n gender: \"string (optional, 'male' or 'female')\"\n },\n response: {\n success: \"boolean\",\n measurements: \"object (body measurements in cm)\",\n landmarks: \"array (pose landmarks)\",\n confidence: \"number (confidence score 0-100)\",\n error: \"string (error message if failed)\"\n }\n },\n \"POST /api/report\": {\n description: \"Generate a text report of body measurements\",\n body: \"Same as /api/measure\",\n response: \"text/plain (measurement report)\"\n },\n \"GET /api/health\": {\n description: \"Health check endpoint\",\n response: {\n status: \"string\",\n timestamp: \"string\",\n version: \"string\"\n }\n }\n },\n notes: [\n \"Images should be clear, full-body photos with the person standing upright\",\n \"Supported formats: JPEG, PNG, WebP\",\n \"Maximum file size: 10MB\",\n \"Reference height improves measurement accuracy\",\n \"Measurements are estimates based on pose detection\"\n ]\n };\n \n return c.json(docs);\n});\n\nexport default app.fetch;","deleted","label",[169,152],"backend","permalink","https://www.val.town/x/vinod/Demo/code/backend/index.ts","extension","actionData","errors"]