Create app.py

app.py

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+import gradio as gr
+import random
+from PIL import Image
+import numpy as np
+from datetime import datetime, timedelta
+import pandas as pd
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+
+# 食物營養資料庫
+food_nutrition = {
+    "米飯": {
+        "calories": 130, "protein": 2.7, "carbs": 28.7, "fat": 0.3, "fiber": 0.4,
+        "category": "主食", "glycemic_index": "高", "allergens": [],
+        "vitamins": {"B1": 0.02, "B2": 0.01, "B3": 0.4},
+        "minerals": {"鐵": 0.2, "鎂": 12, "鋅": 0.4}
+    },
+    "牛肉": {
+        "calories": 250, "protein": 26, "carbs": 0, "fat": 17, "fiber": 0,
+        "category": "蛋白質", "glycemic_index": "低", "allergens": [],
+        "vitamins": {"B12": 2.1, "B6": 0.3, "D": 0.1},
+        "minerals": {"鐵": 2.7, "鋅": 4.8, "硒": 33.2}
+    },
+    "麵包": {
+        "calories": 265, "protein": 9, "carbs": 49, "fat": 3.2, "fiber": 2.5,
+        "category": "主食", "glycemic_index": "高", "allergens": ["麩質"],
+        "vitamins": {"B1": 0.1, "B3": 1.3, "葉酸": 0.04},
+        "minerals": {"鎂": 26, "磷": 86, "鐵": 1.4}
+    },
+    "蔬菜": {
+        "calories": 25, "protein": 1.5, "carbs": 5, "fat": 0.2, "fiber": 2.5,
+        "category": "蔬菜", "glycemic_index": "低", "allergens": [],
+        "vitamins": {"A": 0.5, "C": 10, "K": 0.1},
+        "minerals": {"鉀": 290, "鈣": 40, "鎂": 15}
+    },
+    "番茄": {
+        "calories": 18, "protein": 0.9, "carbs": 3.9, "fat": 0.2, "fiber": 1.2,
+        "category": "蔬果", "glycemic_index": "低", "allergens": [],
+        "vitamins": {"C": 13.7, "A": 0.8, "K": 0.07},
+        "minerals": {"鉀": 237, "鎂": 11, "鈣": 10}
+    },
+    "雞蛋": {
+        "calories": 155, "protein": 13, "carbs": 0.6, "fat": 11, "fiber": 0,
+        "category": "蛋白質", "glycemic_index": "低", "allergens": ["蛋"],
+        "vitamins": {"D": 1.1, "B12": 0.6, "B2": 0.3},
+        "minerals": {"硒": 20, "鋅": 1.3, "鐵": 1.8}
+    },
+    "豬肉": {
+            "calories": 242, "protein": 22.5, "carbs": 0, "fat": 17, "fiber": 0,
+            "category": "蛋白質", "glycemic_index": "低", "allergens": [],
+            "vitamins": {"B1": 0.6, "B6": 0.4, "B12": 0.7},
+            "minerals": {"鋅": 4.5, "鐵": 1.2, "硒": 35.3}
+    },
+    "三文魚": {
+            "calories": 208, "protein": 22, "carbs": 0, "fat": 13, "fiber": 0,
+            "category": "蛋白質", "glycemic_index": "低", "allergens": ["魚"],
+            "vitamins": {"D": 9.5, "B12": 3.2, "B6": 0.6},
+            "minerals": {"硒": 40.2, "鋅": 0.5, "鐵": 0.5}
+    },
+    "青菜": {
+            "calories": 16, "protein": 1.3, "carbs": 2.9, "fat": 0.2, "fiber": 2.1,
+            "category": "蔬菜", "glycemic_index": "低", "allergens": [],
+            "vitamins": {"A": 0.3, "C": 35, "K": 0.2},
+            "minerals": {"鈣": 105, "鎂": 22, "鉀": 370}
+    },
+    "水果": {
+            "calories": 52, "protein": 0.5, "carbs": 14, "fat": 0.2, "fiber": 2.4,
+            "category": "蔬果", "glycemic_index": "中", "allergens": [],
+            "vitamins": {"C": 8.5, "A": 0.2, "葉酸": 0.02},
+            "minerals": {"鉀": 200, "鎂": 10, "鈣": 20}
+    },
+    "土豆": {
+            "calories": 77, "protein": 2, "carbs": 17, "fat": 0.1, "fiber": 2.2,
+            "category": "主食", "glycemic_index": "高", "allergens": [],
+            "vitamins": {"C": 10, "B6": 0.3, "葉酸": 0.01},
+            "minerals": {"鉀": 421, "鎂": 23, "磷": 57}
+    },
+    "豆腐": {
+            "calories": 84, "protein": 9, "carbs": 2, "fat": 5, "fiber": 0.5,
+            "category": "蛋白質", "glycemic_index": "低", "allergens": ["大豆"],
+            "vitamins": {"A": 0.1, "葉酸": 0.02, "K": 0.02},
+            "minerals": {"鈣": 350, "鐵": 2.1, "鎂": 37}
+    },
+    "花生": {
+            "calories": 567, "protein": 25.8, "carbs": 16.1, "fat": 49.2, "fiber": 8.5,
+            "category": "脂肪", "glycemic_index": "低", "allergens": ["花生"],
+            "vitamins": {"E": 8.3, "B3": 14.4, "葉酸": 0.24},
+            "minerals": {"鎂": 168, "磷": 376, "鋅": 3.3}
+    },
+    "牛奶": {
+            "calories": 42, "protein": 3.4, "carbs": 4.8, "fat": 1.0, "fiber": 0,
+            "category": "乳製品", "glycemic_index": "低", "allergens": ["乳製品"],
+            "vitamins": {"B12": 0.4, "B2": 0.2, "D": 0.1},
+            "minerals": {"鈣": 120, "磷": 93, "鉀": 150}
+    },
+    "香蕉": {
+            "calories": 89, "protein": 1.1, "carbs": 22.8, "fat": 0.3, "fiber": 2.6,
+            "category": "蔬果", "glycemic_index": "中", "allergens": [],
+            "vitamins": {"C": 8.7, "B6": 0.4, "A": 0.1},
+            "minerals": {"鉀": 358, "鎂": 27, "鐵": 0.3}
+    },
+    "雞肉": {
+            "calories": 239, "protein": 27, "carbs": 0, "fat": 14, "fiber": 0,
+            "category": "蛋白質", "glycemic_index": "低", "allergens": [],
+            "vitamins": {"B6": 0.5, "B12": 0.3, "A": 0.02},
+            "minerals": {"鋅": 2.7, "鐵": 0.9, "硒": 24.5}
+    }
+    
+    
+}
+
+class UserProfile:
+    # 初始化用戶資料
+    def __init__(self, age, gender, height, weight, activity_level):
+        # 身高與體重範圍檢查
+        if not (50 <= height <= 250):
+            raise ValueError("身高應在50到250公分之間")
+        if not (20 <= weight <= 300):
+            raise ValueError("體重應在20到300公斤之間")
+        
+        self.age = age
+        self.gender = gender
+        self.height = height
+        self.weight = weight
+        self.activity_level = activity_level
+
+    def calculate_bmr(self):
+        # 計算基礎代謢率（BMR）
+        if self.gender == "男":
+            return 88.362 + (13.397 * self.weight) + (4.799 * self.height) - (5.677 * self.age)
+        else:
+            return 447.593 + (9.247 * self.weight) + (3.098 * self.height) - (4.330 * self.age)
+
+    def calculate_tdee(self):
+        # 計算每日總能量消耗（TDEE）
+        activity_factors = {
+            "久坐": 1.2,
+            "輕度活動": 1.375,
+            "中度活動": 1.55,
+            "重度活動": 1.725,
+            "極重度活動": 1.9
+        }
+        return self.calculate_bmr() * activity_factors[self.activity_level]
+
+def create_nutrition_charts(total_nutrients, recommended_nutrients, total_calories):
+    """創建優化後的營養圖表"""
+    # 創建子圖布局
+    fig = make_subplots(
+        rows=2, cols=2,
+        specs=[
+            [{"colspan": 2}, None],
+            [{"type": "pie"}, {"type": "bar"}]
+        ],
+        subplot_titles=(
+            '每日營養素攝入比較',
+            '熱量來源分布',
+            '營養素達標率'
+        ),
+        vertical_spacing=0.12,
+        horizontal_spacing=0.1
+    )
+
+    # 1. 營養素對比條形圖（上方大圖）
+    nutrients = ['蛋白質', '碳水化合物', '脂肪', '膳食纖維']
+
+    fig.add_trace(
+        go.Bar(
+            name='實際攝入',
+            x=nutrients,
+            y=[total_nutrients[n] for n in nutrients],
+            marker_color='rgb(55, 83, 109)'
+        ),
+        row=1, col=1
+    )
+
+    fig.add_trace(
+        go.Bar(
+            name='建議攝入',
+            x=nutrients,
+            y=[recommended_nutrients[n] for n in nutrients],
+            marker_color='rgb(26, 118, 255)'
+        ),
+        row=1, col=1
+    )
+
+    # 2. 熱量來源分布圓餅圖（左下）
+    calorie_values = [
+        total_nutrients['蛋白質'] * 4,
+        total_nutrients['碳水化合物'] * 4,
+        total_nutrients['脂肪'] * 9
+    ]
+
+    fig.add_trace(
+        go.Pie(
+            labels=['蛋白質', '碳水化合物', '脂肪'],
+            values=calorie_values,
+            hole=0.4,
+            marker=dict(colors=['rgb(55, 83, 109)', 'rgb(26, 118, 255)', 'rgb(95, 70, 144)'])
+        ),
+        row=2, col=1
+    )
+
+    # 3. 營養素達標率（右下）
+    achievement_rates = [
+        (total_nutrients[n] / recommended_nutrients[n] * 100)
+        if recommended_nutrients[n] > 0 else 0
+        for n in nutrients
+    ]
+
+    fig.add_trace(
+        go.Bar(
+            x=nutrients,
+            y=achievement_rates,
+            marker_color='rgb(158, 202, 225)',
+            text=[f"{rate:.1f}%" for rate in achievement_rates],
+            textposition='auto',
+        ),
+        row=2, col=2
+    )
+
+    # 更新布局
+    fig.update_layout(
+        height=800,  # 增加圖表高度
+        width=900,   # 適當的寬度
+        showlegend=True,
+        legend=dict(
+            orientation="h",
+            yanchor="bottom",
+            y=1.02,
+            xanchor="right",
+            x=1
+        ),
+        title_text="營養分析總覽",
+        title_x=0.5,
+        font=dict(size=12),
+    )
+
+    # 更新y軸標題
+    fig.update_yaxes(title_text="克", row=1, col=1)
+    fig.update_yaxes(title_text="達標率(%)", row=2, col=2)
+
+    return fig
+
+def analyze_meals_advanced(
+    images, age, gender, height, weight,
+    activity_level, diet_preference, health_goal,
+    allergies, medical_conditions
+):
+    try:
+        # 新增的輸入驗證
+        if not all([age, gender, height, weight, activity_level]):
+            return "請填寫所有必要的個人信息", "", "", None, ""
+
+        # 檢查過敏原
+        if "無" in allergies and len(allergies) > 1:
+            return "過敏原不能同時選擇「無」和其他選項", "", "", None, ""
+
+        # 檢查醫療狀況
+        if "無" in medical_conditions and len(medical_conditions) > 1:
+            return "醫療狀況不能同時選擇「無」和其他選項", "", "", None, ""
+
+        # 嘗試建立UserProfile並檢查身高體重範圍
+        user = UserProfile(age, gender, height, weight, activity_level)
+        tdee = user.calculate_tdee()
+
+        # 模擬食物識別
+        recognized_foods = []
+        for img in images:
+            foods = random.sample(list(food_nutrition.keys()), k=random.randint(1, 3))
+            recognized_foods.extend(foods)
+
+        # 計算營養總量
+        total_nutrients = {
+            "蛋白質": sum(food_nutrition[food]["protein"] for food in recognized_foods),
+            "碳水化合物": sum(food_nutrition[food]["carbs"] for food in recognized_foods),
+            "脂肪": sum(food_nutrition[food]["fat"] for food in recognized_foods),
+            "膳食纖維": sum(food_nutrition[food]["fiber"] for food in recognized_foods)
+        }
+
+        # 計算建議攝入量
+        recommended_nutrients = {
+            "蛋白質": weight * 1.2,
+            "碳水化合物": tdee * 0.5 / 4,
+            "脂肪": tdee * 0.3 / 9,
+            "膳食纖維": 25
+        }
+
+        total_calories = sum(food_nutrition[food]["calories"] for food in recognized_foods)
+
+        # 創建優化後的圖表
+        charts = create_nutrition_charts(total_nutrients, recommended_nutrients, total_calories)
+
+        # 生成更簡潔的報告
+        report = f"""📊 營養攝入概要
+--------------------------------
+⚡ 每日能量需求：{tdee:.0f} 大卡
+🍽️ 實際攝入：{total_calories:.0f} 大卡
+🥩 蛋白質：{total_nutrients['蛋白質']:.1f}g
+🍚 碳水化合物：{total_nutrients['碳水化合物']:.1f}g
+🥑 脂肪：{total_nutrients['脂肪']:.1f}g
+🥬 膳食纖維：{total_nutrients['膳食纖維']:.1f}g"""
+
+        # 過敏警告
+        allergy_warnings = "⚠️ 過敏原警告：\n"
+        if allergies and "無" not in allergies:
+            found_allergens = []
+            for food in recognized_foods:
+                food_allergens = food_nutrition[food].get("allergens", [])
+                found_allergens.extend([a for a in allergies if a in food_allergens])
+
+            if found_allergens:
+                allergy_warnings += "\n".join(f"- 發現含有{allergen}的食物" for allergen in set(found_allergens))
+            else:
+                allergy_warnings += "未發現任何過敏原"
+        else:
+            allergy_warnings += "未設置過敏原信息"
+
+        # 醫療建議
+        medical_advice = "👨‍⚕️ 健康建議：\n"
+        if medical_conditions:
+            for condition in medical_conditions:
+                if condition == "糖尿病":
+                    if total_nutrients['碳水化合物'] > recommended_nutrients['碳水化合物']:
+                        medical_advice += "- 碳水化合物攝入偏高，建議調整\n"
+                elif condition == "高血壓":
+                    medical_advice += "- 建議選擇低鈉食物，控制鹽分攝入\n"
+        else:
+            medical_advice += "無特殊醫療注意事項"
+
+        return report, allergy_warnings, recognized_foods, charts, medical_advice
+
+    except ValueError as e:
+        return f"錯誤：{str(e)}", "", "", None, ""  # 返回錯誤訊息
+    except Exception as e:
+        return f"分析過程出錯：{str(e)}", "", "", None, ""
+
+def create_interface():
+    with gr.Blocks(theme=gr.themes.Soft()) as iface:
+        gr.Markdown("# 🥗 智能營養分析系統")
+
+        with gr.Row():
+            with gr.Column(scale=1):
+                images = gr.Gallery(label="上傳一日三餐的照片", height=200)
+
+                with gr.Row():
+                    with gr.Column(scale=1):
+                        age = gr.Number(label="年齡", minimum=1, maximum=120)
+                        height = gr.Number(label="身高(cm)", minimum=50, maximum=250)
+                    with gr.Column(scale=1):
+                        gender = gr.Radio(["男", "女"], label="性別")
+                        weight = gr.Number(label="體重(kg)", minimum=20, maximum=200)
+
+                activity_level = gr.Dropdown(
+                    ["久坐", "輕度活動", "中度活動", "重度活動", "極重度活動"],
+                    label="活動程度"
+                )
+
+                with gr.Row():
+                    with gr.Column(scale=1):
+                        diet_preference = gr.Radio(
+                            ["一般", "素食", "低碳", "高蛋白", "低脂", "無糖"],
+                            label="飲食偏好"
+                        )
+                        health_goal = gr.Radio(
+                            ["減肥", "增肌", "維持健康", "改善消化"],
+                            label="健康目標"
+                        )
+
+                    with gr.Column(scale=1):
+                        allergies = gr.Radio(
+                            ["無", "花生", "海鮮", "乳製品", "麩質", "蛋", "豆類"],
+                            label="過敏原",
+                            type="value"  # 新增這個參數
+                        )
+                        medical_conditions = gr.Radio(
+                            ["無", "糖尿病", "高血壓", "高血脂", "腎臟病"],
+                            label="醫療狀況",
+                            type="value"  # 新增這個參數
+                        )
+
+            with gr.Column(scale=1):
+                charts_output = gr.Plot(label="營養分析圖表")
+                report_output = gr.Textbox(label="營養分析報告", lines=6)
+                with gr.Row():
+                    allergy_warning_output = gr.Textbox(label="過敏警告", lines=3)
+                    medical_advice_output = gr.Textbox(label="醫療建議", lines=3)
+                suggestions_output = gr.Textbox(label="個人化建議", lines=8)
+
+        analyze_btn = gr.Button("開始分析", variant="primary")
+        analyze_btn.click(
+            fn=analyze_meals_advanced,
+            inputs=[images, age, gender, height, weight,
+                    activity_level, diet_preference, health_goal,
+                    allergies, medical_conditions],
+            outputs=[report_output, allergy_warning_output,
+                     medical_advice_output, charts_output, suggestions_output]
+        )
+
+    return iface
+
+if __name__ == "__main__":
+    iface = create_interface()
+    iface.launch()