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devlim commited on Jun 11, 2024

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efb95c5

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1 Parent(s): 5b09e83

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app.py +91 -0
requirements.txt +3 -0
templates/index.html +154 -0

app.py ADDED Viewed

	@@ -0,0 +1,91 @@

+from flask import Flask, request, jsonify, render_template, send_from_directory
+import base64
+import re
+import os
+from datetime import datetime
+import requests
+# OpenAI API Key
+api_key = "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"
+app = Flask(__name__)
+# Function to encode the image
+def encode_image(image_path):
+  with open(image_path, "rb") as image_file:
+    return base64.b64encode(image_file.read()).decode('utf-8')
+@app.route('/')
+def index():
+    return render_template('index.html')
+@app.route('/save_image', methods=['POST'])
+def save_image():
+    data = request.get_json()
+    image_data = data['image']
+    # Decode the base64 image data
+    image_data = re.sub('^data:image/.+;base64,', '', image_data)
+    image_data = base64.b64decode(image_data)
+    # Create a unique file name
+    timestamp = datetime.now().strftime('%Y%m%d%H%M%S')
+    file_path = f'captured_image_{timestamp}.png'
+    # Save the image to a file
+    with open(file_path, 'wb') as f:
+        f.write(image_data)
+    # Path to your image
+    image_path = file_path
+    # Getting the base64 string
+    base64_image = encode_image(image_path)
+    headers = {
+    "Content-Type": "application/json",
+    "Authorization": f"Bearer {api_key}"
+    }
+    payload = {
+    "model": "gpt-4o",
+    "messages": [
+        {
+        "role": "user",
+        "content": [
+            {
+            "type": "text",
+            "text": "이미지를 입력받으면 당류가 몇 g인지 예시와 같은 형식만 출력하시오.\n예) 당류 : 10g \n상품분석표가 아니라면 'error'를 출력하시오."
+            },
+            {
+            "type": "image_url",
+            "image_url": {
+                "url": f"data:image/jpeg;base64,{base64_image}"
+            }
+            }
+        ]
+        }
+    ],
+    "max_tokens": 300
+    }
+    response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
+    if response.status_code == 200:
+        result = response.json()
+        analysis_result = result['choices'][0]['message']['content']
+    else:
+        analysis_result = "Error: 당류를 찾을 수 없습니다."
+    return jsonify({'message': '분석이 완료되었습니다.', 'image_url': file_path, 'analysis_result': analysis_result})
+@app.route('/images/<filename>')
+def get_image(filename):
+    return send_from_directory('.', filename)
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=7860, debug=True)

requirements.txt ADDED Viewed

	@@ -0,0 +1,3 @@

+Flask
+requests
+openai

templates/index.html ADDED Viewed

	@@ -0,0 +1,154 @@

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>성분분석표</title>
+    <link href="https://fonts.googleapis.com/css2?family=Roboto:wght@400;700&display=swap" rel="stylesheet">
+    <style>
+        body {
+            font-family: 'Roboto', sans-serif;
+            background-color: #f0f2f5;
+            display: flex;
+            justify-content: center;
+            align-items: center;
+            height: 100vh;
+            margin: 0;
+        }
+        .container {
+            background: #fff;
+            padding: 20px;
+            border-radius: 8px;
+            box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+            text-align: center;
+            max-width: 700px;
+            width: 100%;
+        }
+        h1 {
+            color: #333;
+            margin-bottom: 20px;
+        }
+        video,
+        canvas,
+        img {
+            border-radius: 8px;
+            width: 100%;
+            max-width: 640px;
+            height: auto;
+            margin-bottom: 20px;
+        }
+        button {
+            background-color: #4CAF50;
+            color: white;
+            padding: 10px 20px;
+            border: none;
+            border-radius: 5px;
+            cursor: pointer;
+            font-size: 16px;
+            transition: background-color 0.3s, transform 0.3s;
+        }
+        button:hover {
+            background-color: #45a049;
+            transform: scale(1.05);
+        }
+        .result {
+            margin-top: 20px;
+            font-size: 18px;
+            font-weight: bold;
+        }
+        .good {
+            color: green;
+        }
+        .normal {
+            color: orange;
+        }
+        .dangerous {
+            color: red;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>성분분석표</h1>
+        <video id="video" autoplay></video>
+        <button id="snap">사진 찍기</button>
+        <canvas id="canvas"></canvas>
+        <p id="analysisResult" class="result"></p>
+    </div>
+    <script>
+        const video = document.getElementById('video');
+        const canvas = document.getElementById('canvas');
+        const snap = document.getElementById('snap');
+        const context = canvas.getContext('2d');
+        const analysisResult = document.getElementById('analysisResult');
+        navigator.mediaDevices.getUserMedia({ video: true })
+            .then(stream => {
+                video.srcObject = stream;
+            })
+            .catch(err => {
+                console.error("Error accessing webcam: " + err);
+            });
+        function processAnalysisResult(result) {
+            const match = result.match(/\d+/);
+            if (match) {
+                const sugarContent = parseInt(match[0], 10);
+                let message = '';
+                let className = '';
+                if (sugarContent >= 0 && sugarContent <= 20) {
+                    message = 'good';
+                    className = 'good';
+                } else if (sugarContent >= 21 && sugarContent <= 50) {
+                    message = 'normal';
+                    className = 'normal';
+                } else if (sugarContent >= 51) {
+                    message = 'dangerous';
+                    className = 'dangerous';
+                }
+                analysisResult.textContent = message;
+                analysisResult.className = className;
+            } else {
+                analysisResult.textContent = 'Error: Could not analyze image.';
+                analysisResult.className = '';
+            }
+        }
+        snap.addEventListener('click', () => {
+            context.drawImage(video, 0, 0, canvas.width, canvas.height);
+            const dataURL = canvas.toDataURL('image/png');
+            fetch('/save_image', {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify({ image: dataURL })
+            }).then(response => response.json())
+                .then(data => {
+                    if (data.analysis_result) {
+                        processAnalysisResult(data.analysis_result);
+                    } else {
+                        analysisResult.textContent = 'Error: 성분분석표를 확인할 수 없습니다.';
+                        analysisResult.className = '';
+                    }
+                    alert(data.message);
+                });
+        });
+    </script>
+</body>
+</html>