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Kamera ile Kalori Tahmini

\n \n \n

\n \n \n \n

\n \n \n

\n \n

\n \n \n

\n $\"Yemek$ \n

\n \n

\n \n \n

Yemekler analiz ediliyor...

\n \n \n

Analiz Sonuçları

\n \n

Toplam Kalori:

\n 0\n

\n \n

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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",[],[67],"937ec82c-3356-11f0-a07d-9e149126039e","README.md","462b23cc-3356-11f0-b501-9e149126039e",6,["D",1747510738303],1,"# 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 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