Kamera ile Kalori Tahmini

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\n $\"Yemek$ \n

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Yemekler analiz ediliyor...

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Analiz Sonuçları

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Toplam Kalori:

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\n\n \n\n",[18,68],"pulls","branches",1,"forks","envVars",{"_198":26,"_200":26},"connections",{"_198":26,"_199":26},"count","unfilledCount","emptyCount",{"_37":177,"_13":18,"_66":105,"_47":-5,"_39":40,"_178":44,"_179":24,"_41":225,"_43":26,"_69":106,"_181":-5,"_70":30,"_182":-5,"_211":226,"_17":227},{"_37":185,"_13":68,"_66":67,"_47":105,"_39":40,"_178":99,"_179":24,"_41":222,"_43":187,"_69":21,"_181":188,"_70":30,"_182":-5,"_211":223,"_17":224},{"_37":214,"_13":215,"_66":216,"_47":-5,"_39":40,"_178":217,"_179":24,"_41":218,"_43":192,"_69":21,"_181":219,"_70":30,"_182":-5,"_211":220,"_17":221},{"_37":205,"_13":206,"_66":118,"_47":-5,"_39":40,"_178":142,"_179":24,"_41":207,"_43":208,"_69":209,"_181":210,"_70":30,"_182":-5,"_211":212,"_17":213},"9097cd06-3357-11f0-8acc-9e149126039e","index.ts",["D",1747511162946],3,"http","import { Hono } from \"https://esm.sh/hono@3.11.7\";\nimport { readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\n\nconst app = new Hono();\n\n// Unwrap Hono errors to see original error details\napp.onError((err, c) => {\n console.error(\"Application error:\", err);\n throw err;\n});\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// Main page\napp.get(\"/\", async c => {\n let html = await readFile(\"/frontend/index.html\", import.meta.url);\n return c.html(html);\n});\n\n// API endpoint to analyze food image\napp.post(\"/api/analyze-food\", async (c) => {\n try {\n console.log(\"Received analyze-food request\");\n \n const formData = await c.req.formData();\n const imageFile = formData.get(\"image\") as File;\n \n if (!imageFile) {\n console.error(\"No image provided in request\");\n return c.json({ error: \"No image provided\" }, 400);\n }\n \n console.log(\"Image received:\", imageFile.name, imageFile.type, imageFile.size);\n\n // Convert image to base64\n const arrayBuffer = await imageFile.arrayBuffer();\n const base64Image = btoa(\n new Uint8Array(arrayBuffer).reduce((data, byte) => data + String.fromCharCode(byte), '')\n );\n \n console.log(\"Image converted to base64, length:\", base64Image.length);\n\n // Call OpenAI to analyze the image\n console.log(\"Calling OpenAI API...\");\n const openai = new OpenAI();\n const response = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n {\n role: \"system\",\n content: \"You are a nutritionist specializing in identifying food items and their calorie content from images. For each food item visible in the image, provide the name and estimated calories in the following JSON format with an 'items' array: {\\\"items\\\": [{\\\"food\\\": \\\"name\\\", \\\"calories\\\": number}, ...]}. Be specific about portion sizes when estimating calories. If you can't identify something clearly, make your best guess.\"\n },\n {\n role: \"user\",\n content: [\n { type: \"text\", text: \"What food items are in this image? Provide the name and estimated calories for each item.\" },\n { type: \"image_url\", image_url: { url: `data:image/jpeg;base64,${base64Image}` } }\n ]\n }\n ],\n response_format: { type: \"json_object\" }\n });\n \n console.log(\"OpenAI response received\");\n\n // Parse the response\n const content = response.choices[0].message.content || \"{}\";\n console.log(\"OpenAI content:\", content);\n \n let result;\n try {\n result = JSON.parse(content);\n console.log(\"Parsed result:\", result);\n \n // Ensure we have the expected format\n if (!result.items && Array.isArray(result)) {\n console.log(\"Converting array to items format\");\n result = { items: result };\n } else if (!result.items) {\n console.log(\"No items found, creating empty array\");\n result = { items: [] };\n }\n } catch (parseError) {\n console.error(\"Error parsing OpenAI response:\", parseError);\n return c.json({ \n error: \"Failed to parse analysis result\",\n items: []\n }, 500);\n }\n\n // Return the analysis\n return c.json(result);\n } catch (error) {\n console.error(\"Error analyzing food:\", error);\n return c.json({ \n error: \"Failed to analyze image\", \n details: String(error),\n items: []\n }, 500);\n }\n});\n\nexport default app.fetch;","children",[],[206],"937ec82c-3356-11f0-a07d-9e149126039e","README.md","462b23cc-3356-11f0-b501-9e149126039e",6,["D",1747510738303],"# Kamera ile Kalori Tahmini\n\nBu uygulama, kamera kullanarak veya fotoğraf yükleyerek yemeklerin kalorilerini tahmin etmenizi sağlar. Yemeğinizin fotoğrafını çekin veya yükleyin, yapay zeka yemeği tanımlayıp kalorisini hesaplasın!\n\n## Özellikler\n\n- Kamera ile yemek fotoğrafı çekme\n- Galeriden fotoğraf yükleme\n- Yapay zeka ile yemek türlerini otomatik tanıma\n- Her yemek için kalori tahmini\n- Toplam kalori hesaplama\n\n## Nasıl Kullanılır\n\n### Kamera ile:\n1. \"Kamera Kullan\" düğmesine tıklayın\n2. Yemeğinizin fotoğrafını çekmek için \"Fotoğraf Çek\" düğmesine tıklayın\n3. Fotoğrafı analiz etmek için \"Analiz Et\" düğmesine tıklayın\n\n### Fotoğraf Yükleme ile:\n1. \"Fotoğraf Yükle\" düğmesine tıklayın\n2. Cihazınızdan bir yemek fotoğrafı seçin\n3. Fotoğrafı analiz etmek için \"Analiz Et\" düğmesine tıklayın\n\nSonuçlar bölümünde her yemek ve tahmini kalorisi listelenecektir. Toplam kalori miktarı sayfanın altında gösterilecektir.\n\n## Teknik Detaylar\n\nBu uygulama şunları kullanır:\n- OpenAI GPT-4o Vision API (yemek tanıma)\n- Web kamera API'si\n- Hono.js (backend framework)\n- TailwindCSS (styling)\n\n## Sınırlamalar\n\n- Kalori tahminleri yaklaşıktır ve gerçek değerlerden farklılık gösterebilir\n- Bazı yemekler doğru tanımlanamayabilir\n- Kamera erişimi için tarayıcı izinleri gereklidir",[],[215],["D",1747511143246],[],[18,68],["D",1747510595366],[202],[18],["D",1747510491093],{"_11":12,"_155":73},{"_11":12,"_151":-5,"_72":73,"_31":71,"_152":153,"_154":30},{"_43":142,"_13":16,"_37":40,"_143":108,"_144":-5,"_145":-5,"_146":-5,"_147":-5,"_148":-5,"_149":14,"_150":12},"ctx",{"_56":-5,"_174":265,"_266":267,"_268":269,"_270":30,"_271":30,"_272":30,"_273":24,"_274":-5,"_275":-7,"_276":-7,"_277":26,"_278":30,"_279":30,"_280":-5,"_281":30,"_282":30,"_283":30,"_284":-5},"ENV",{"_236":237,"_238":239,"_240":16,"_241":242,"_243":244,"_245":246,"_247":248,"_249":250,"_251":252,"_253":254,"_255":256,"_257":258,"_259":260,"_261":262,"_263":264},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e8c4b7030cb7600e4eb0736b15f422c8b8bd130f","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

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