PycharmProjects/.env

@@ -1,2 +0,0 @@
-OPENAI_API_KEY=MOONSHOT_API_KEY
-WEATHER_API_KEY=639ab98ac7710557eb8d9155d9a25e80

PycharmProjects/.idea/.gitignore

@@ -1,8 +0,0 @@
-# 默认忽略的文件
-/shelf/
-/workspace.xml
-# 基于编辑器的 HTTP 客户端请求
-/httpRequests/
-# Datasource local storage ignored files
-/dataSources/
-/dataSources.local.xml

PycharmProjects/.idea/PycharmProjects.iml

@@ -1,10 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="PYTHON_MODULE" version="4">
-  <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$">
-      <excludeFolder url="file://$MODULE_DIR$/.venv" />
-    </content>
-    <orderEntry type="jdk" jdkName="Python 3.12 (PycharmProjects)" jdkType="Python SDK" />
-    <orderEntry type="sourceFolder" forTests="false" />
-  </component>
-</module>

PycharmProjects/.idea/inspectionProfiles/profiles_settings.xml

@@ -1,6 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <settings>
-    <option name="USE_PROJECT_PROFILE" value="false" />
-    <version value="1.0" />
-  </settings>
-</component>

PycharmProjects/.idea/misc.xml

@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="Black">
-    <option name="sdkName" value="Python 3.12 (PycharmProjects)" />
-  </component>
-</project>

PycharmProjects/.idea/modules.xml

@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/PycharmProjects.iml" filepath="$PROJECT_DIR$/.idea/PycharmProjects.iml" />
-    </modules>
-  </component>
-</project>

PycharmProjects/app.py

@@ -1,32 +0,0 @@
-import streamlit as st
-from templates.user_info import show_user_info_form
-from templates.recommendations import show_recommendations_tab
-from templates.recommendations import show_virtual_tryon_tab
-
-
-# 页面设置
-st.set_page_config(page_title="智能穿搭助手", page_icon="👗", layout="wide")
-
-# 标题和介绍
-st.title("👗 智能穿搭助手")
-
-# 初始化session state
-if 'user_info' not in st.session_state:
-    st.session_state.user_info = {}
-if 'recommendations' not in st.session_state:
-    st.session_state.recommendations = None
-
-# 侧边栏 - 用户信息收集
-show_user_info_form()
-
-# 主界面
-tab1, tab2 = st.tabs(["穿搭推荐", "虚拟试衣"])
-
-with tab1:
-    show_recommendations_tab()
-
-with tab2:
-    show_virtual_tryon_tab()
-
-if __name__ == "__main__":
-    st.write("")

PycharmProjects/config.py

@@ -1,17 +0,0 @@
-import os
-from dotenv import load_dotenv
-
-
-
-# 中国主要城市中英文对照表
-CITY_NAME_MAPPING = {
-    # 直辖市
-    "beijing": "北京", "peking": "北京",
-    "shanghai": "上海",
-    # ... (保持原有的城市映射不变)
-}
-
-# 加载环境变量
-load_dotenv()
-MOONSHOT_API_KEY = os.getenv("MOONSHOT_API_KEY")
-WEATHER_API_KEY = os.getenv("WEATHER_API_KEY")

PycharmProjects/templates/recommendations.py

@@ -1,177 +0,0 @@
-import streamlit as st
-import requests
-from PIL import Image
-
-from utils.weather import get_weather_data
-from utils.outfits import generate_sample_outfits
-from utils.outfits import generate_fallback_outfits
-from utils.image_processing import process_image_for_try_on
-from config import MOONSHOT_API_KEY
-
-
-
-def show_recommendations_tab():
-    st.header("智能穿搭推荐")
-
-    with st.form("scene_form"):
-        col1, col2 = st.columns(2)
-        with col1:
-            scene_input = st.text_input("描述你的场景需求",
-                                        placeholder="例如: 今天要和朋友们去公园野餐")
-        with col2:
-            city_input = st.text_input("输入城市名称",
-                                       placeholder="例如: 北京",
-                                       value="北京")
-
-        use_weather = st.checkbox("获取当地天气信息", value=True)
-        submitted = st.form_submit_button("获取穿搭建议")
-
-        if submitted and scene_input:
-            with st.spinner("正在生成穿搭建议..."):
-                try:
-                    weather_info = ""
-                    if use_weather and city_input:
-                        weather_data = get_weather_data(city_input)
-                        if weather_data:
-                            weather_info = f"""
-                            ## 当前天气情况
-                            - 城市: {weather_data['city']}
-                            - 天气状况: {weather_data['description']}
-                            - 温度: {weather_data['temp']}°C
-                            - 湿度: {weather_data['humidity']}%
-                            """
-                            st.markdown(weather_info)
-
-                    prompt = build_prompt(scene_input, weather_info if use_weather else "")
-                    response = call_moonshot_api(prompt)
-
-                    if response:
-                        st.session_state.recommendations = response
-                        st.success("穿搭建议生成成功！")
-
-                        # 新增：根据建议生成图片
-                        outfit_image = generate_sample_outfits(response)
-                        if outfit_image:
-                            st.image(outfit_image, caption="推荐穿搭可视化", width=300)
-                            st.session_state.outfit_image = outfit_image
-                        else:
-                            st.warning("无法生成穿搭图片，但文字建议有效")
-                    else:
-                        st.error("获取穿搭建议失败")
-
-                except Exception as e:
-                    st.error(f"获取建议时出错: {str(e)}")
-
-    # recommendations.py 修改后的显示部分
-    if st.session_state.recommendations:
-        st.markdown("### 您的专属穿搭建议")
-        st.markdown(st.session_state.recommendations)
-
-        st.markdown("### 搭配示例")
-        try:
-            sample_images = generate_sample_outfits(
-                st.session_state.recommendations,
-                save_to_local=True
-            )
-
-            if sample_images:
-                # 确保只显示实际生成的图片数量
-                num_images = min(3, len(sample_images))
-                cols = st.columns(num_images)
-
-                for i in range(num_images):
-                    with cols[i]:
-                        st.image(
-                            sample_images[i],
-                            use_container_width=True,
-                            caption=f"穿搭方案 {i + 1}"
-                        )
-                        st.success(f"示例 {i + 1}")
-            else:
-                st.warning("无法生成任何穿搭示例图片")
-
-        except Exception as e:
-            st.error(f"生成穿搭示例时出错: {str(e)}")
-            # 显示回退方案
-            fallback_images = generate_fallback_outfits(save_to_local=True)
-            cols = st.columns(3)
-            for i, col in enumerate(cols):
-                col.image(
-                    fallback_images[i],
-                    use_container_width=True,
-                    caption=f"穿搭方案 {i + 1} (示例)"
-                )
-
-
-
-def build_prompt(scene_input, weather_info):
-    return f"""
-    你是一位专业的时尚穿搭助手，请根据以下信息为用户提供穿搭建议:
-
-    ### 用户信息
-    {st.session_state.user_info}
-
-    ### 场景描述
-    {scene_input}
-
-    ### 天气信息
-    {weather_info if weather_info else "用户未提供天气信息"}
-
-    ### 请提供以下内容:
-    1. 适合该场景的3套穿搭方案
-    2. 每套方案的风格特点和适用场合说明
-    3. 颜色搭配建议
-    4. 材质和面料选择建议
-    5. 购买建议和品牌推荐(可选)
-    """
-
-
-def call_moonshot_api(prompt):
-    headers = {
-        "Authorization": f"Bearer {MOONSHOT_API_KEY}",
-        "Content-Type": "application/json"
-    }
-
-    data = {
-        "model": "moonshot-v1-128k",
-        "messages": [
-            {
-                "role": "system",
-                "content": "你是一位专业的时尚顾问，擅长根据用户特征、场景和天气状况提供个性化的穿搭建议。"
-            },
-            {
-                "role": "user",
-                "content": prompt
-            }
-        ],
-        "temperature": 0.7,
-        "max_tokens": 2000
-    }
-
-    response = requests.post(
-        "https://api.moonshot.cn/v1/chat/completions",
-        headers=headers,
-        json=data
-    )
-
-    if response.status_code == 200:
-        result = response.json()
-        return result["choices"][0]["message"]["content"]
-    else:
-        st.error(f"API调用失败: {response.text}")
-        return None
-
-
-def show_virtual_tryon_tab():
-    st.header("虚拟试衣间")
-    st.info("此功能正在开发中，即将推出!")
-
-    uploaded_file = st.file_uploader("上传你的照片进行虚拟试衣", type=["jpg", "png", "jpeg"])
-    if uploaded_file is not None:
-        image = Image.open(uploaded_file)
-        st.image(image, caption="上传的照片", use_container_width=True)
-
-        gray, edges = process_image_for_try_on(image)
-        col1, col2 = st.columns(2)
-        col1.image(gray, caption="灰度处理", use_container_width=True, channels="GRAY")
-        col2.image(edges, caption="边缘检测", use_container_width=True, channels="GRAY")

PycharmProjects/templates/user_info.py

@@ -1,25 +0,0 @@
-import streamlit as st
-
-
-def show_user_info_form():
-    with st.sidebar:
-        st.header("个人信息")
-        with st.form("user_info_form"):
-            gender = st.selectbox("性别", ["女", "男", "其他"])
-            age = st.slider("年龄", 10, 80, 25)
-            height = st.number_input("身高(cm)", 100, 250, 165)
-            weight = st.number_input("体重(kg)", 30, 150, 55)
-            skin_tone = st.selectbox("肤色", ["白皙", "自然", "小麦色", "深色"])
-            style_preference = st.multiselect("风格偏好", ["休闲", "正式", "运动", "甜美", "复古", "街头", "商务"])
-            submitted = st.form_submit_button("保存信息")
-
-            if submitted:
-                st.session_state.user_info = {
-                    "gender": gender,
-                    "age": age,
-                    "height": height,
-                    "weight": weight,
-                    "skin_tone": skin_tone,
-                    "style_preference": style_preference
-                }
-                st.success("个人信息已保存!")

PycharmProjects/utils/__init__.py

@@ -1,3 +0,0 @@
-from .weather import get_weather_data
-from .outfits import generate_sample_outfits
-from .image_processing import process_image_for_try_on

PycharmProjects/utils/image_processing.py

@@ -1,11 +0,0 @@
-import cv2
-import numpy as np
-from PIL import Image
-
-
-def process_image_for_try_on(image):
-    """处理上传的试衣图片"""
-    img_array = np.array(image)
-    gray = cv2.cvtColor(img_array, cv2.COLOR_BGR2GRAY)
-    edges = cv2.Canny(gray, 100, 200)
-    return gray, edges

PycharmProjects/utils/outfits.py

@@ -1,160 +0,0 @@
-import numpy as np
-import matplotlib.pyplot as plt
-import cv2
-from io import BytesIO
-from PIL import Image
-import streamlit as st
-
-
-try:
-    import tensorflow as tf
-    from tensorflow.keras.datasets import fashion_mnist
-
-    HAS_TF = True
-except ImportError:
-    HAS_TF = False
-
-import os
-from datetime import datetime
-
-
-def map_keyword_to_indices(text, class_names):
-    """私有方法：从推荐文本解析服装类别索引"""
-    keyword_map = {
-        # 中文关键词映射
-        "t恤": 0, "衬衫": 6, "外套": 4, "套头衫": 2,
-        "裤子": 1, "牛仔裤": 1,
-        "连衣裙": 3, "裙子": 3,
-        "凉鞋": 5, "运动鞋": 7, "短靴": 9, "靴子": 9
-    }
-
-    matched_indices = []
-    text_lower = text.lower()
-    for keyword, idx in keyword_map.items():
-        if keyword in text_lower:
-            matched_indices.append(idx)
-    return list(set(matched_indices))  # 去重
-
-
-# outfits.py 修改后的代码
-def generate_sample_outfits(recommendation_text, save_to_local=False, output_dir="C:/Users/Administrator/Desktop"):
-    """生成示例穿搭图片（包含连衣裙选项）并可选保存到本地"""
-    outfits = []
-
-    # 创建输出目录
-    if save_to_local and not os.path.exists(output_dir):
-        os.makedirs(output_dir)
-
-    if HAS_TF:
-        try:
-            (train_images, train_labels), _ = fashion_mnist.load_data()
-            class_names = ['T恤', '裤子', '套头衫', '连衣裙', '外套',
-                           '凉鞋', '衬衫', '运动鞋', '包', '短靴']
-
-            # 从推荐文本中提取服装类别索引
-            matched_indices = map_keyword_to_indices(recommendation_text, class_names)
-
-            # 根据匹配结果生成图片
-            if not matched_indices:
-                st.warning("无法从推荐文本中识别有效服装类别")
-                return generate_fallback_outfits(save_to_local, output_dir)
-
-            # 生成3套穿搭方案
-            for i in range(3):
-                try:
-                    # 随机决定是生成连衣裙组合还是上下装组合
-                    use_dress = np.random.choice([True, False]) and (3 in matched_indices)
-
-                    if use_dress:
-                        # 连衣裙+鞋子组合
-                        shoes_indices = [i for i in matched_indices if i in [5, 7, 9]]
-                        if not shoes_indices:
-                            continue
-
-                        shoes_idx = np.random.choice(shoes_indices)
-                        dress_img = train_images[np.random.choice(np.where(train_labels == 3)[0])]
-                        shoes_img = train_images[np.random.choice(np.where(train_labels == shoes_idx)[0])]
-
-                        dress_img = cv2.resize(dress_img, (128, 256), interpolation=cv2.INTER_NEAREST)
-                        shoes_img = cv2.resize(shoes_img, (128, 128), interpolation=cv2.INTER_NEAREST)
-                        combined = np.vstack([dress_img, shoes_img])
-                        combined_rgb = np.stack([combined] * 3, axis=-1)
-
-                        title = f"{class_names[3]}+{class_names[shoes_idx]}"
-                    else:
-                        # 上下装+鞋子组合
-                        top_indices = [i for i in matched_indices if i in [0, 2, 4, 6]]
-                        bottom_indices = [i for i in matched_indices if i in [1]]
-                        shoes_indices = [i for i in matched_indices if i in [5, 7, 9]]
-
-                        if not top_indices or not bottom_indices or not shoes_indices:
-                            continue
-
-                        top_idx = np.random.choice(top_indices)
-                        bottom_idx = np.random.choice(bottom_indices)
-                        shoes_idx = np.random.choice(shoes_indices)
-
-                        top_img = train_images[np.random.choice(np.where(train_labels == top_idx)[0])]
-                        bottom_img = train_images[np.random.choice(np.where(train_labels == bottom_idx)[0])]
-                        shoes_img = train_images[np.random.choice(np.where(train_labels == shoes_idx)[0])]
-
-                        top_img = cv2.resize(top_img, (128, 128), interpolation=cv2.INTER_NEAREST)
-                        bottom_img = cv2.resize(bottom_img, (128, 128), interpolation=cv2.INTER_NEAREST)
-                        shoes_img = cv2.resize(shoes_img, (128, 128), interpolation=cv2.INTER_NEAREST)
-                        combined = np.vstack([top_img, bottom_img, shoes_img])
-                        combined_rgb = np.stack([combined] * 3, axis=-1)
-
-                        title = f"{class_names[top_idx]}+{class_names[bottom_idx]}+{class_names[shoes_idx]}"
-
-                    # 直接使用PIL保存图片，避免plt保存问题
-                    img = Image.fromarray(combined_rgb)
-
-                    if save_to_local:
-                        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-                        filename = f"{output_dir}/outfit_{timestamp}_{i}.png"
-                        img.save(filename, format='PNG', quality=95)
-
-                    outfits.append(img)
-
-                except Exception as e:
-                    st.warning(f"生成第{i + 1}套穿搭图片时出错: {str(e)}")
-                    outfits.append(generate_single_fallback_outfit(i + 1, save_to_local, output_dir))
-                    continue
-
-            return outfits if outfits else generate_fallback_outfits(save_to_local, output_dir)
-
-        except Exception as e:
-            st.warning(f"生成服装图片出错: {str(e)}，使用文字替代")
-            return generate_fallback_outfits(save_to_local, output_dir)
-
-    return generate_fallback_outfits(save_to_local, output_dir)
-
-
-def generate_single_fallback_outfit(index, save_to_local=False, output_dir=None):
-    """生成单个回退的文字穿搭方案"""
-    fig, ax = plt.subplots(figsize=(3, 4))
-    ax.set_facecolor('#f0f2f6')
-    ax.text(0.5, 0.5, f"穿搭方案 {index}\n(图片生成失败)",
-            ha='center', va='center', fontsize=10)
-    ax.axis('off')
-
-    buf = BytesIO()
-    fig.savefig(buf, format='png', bbox_inches='tight', pad_inches=0.1, dpi=100)
-    buf.seek(0)
-    img = Image.open(buf)
-    plt.close(fig)
-
-    if save_to_local and output_dir:
-        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-        filename = f"{output_dir}/outfit_{timestamp}_{index}_fallback.png"
-        img.save(filename)
-
-    return img
-
-
-def generate_fallback_outfits(save_to_local=False, output_dir="C:/Users/Administrator/Desktop"):
-    """生成回退的文字穿搭方案"""
-    outfits = []
-    for i in range(3):
-        outfits.append(generate_single_fallback_outfit(i + 1, save_to_local, output_dir))
-    return outfits

PycharmProjects/utils/weather.py

@@ -1,35 +0,0 @@
-import requests
-from config import CITY_NAME_MAPPING, WEATHER_API_KEY
-
-
-def get_weather_data(city, api_key=WEATHER_API_KEY):
-    """获取天气数据"""
-    base_url = "http://api.openweathermap.org/data/2.5/weather"
-    params = {
-        "q": city,
-        "appid": api_key,
-        "units": "metric",
-        "lang": "zh_cn"
-    }
-
-    try:
-        response = requests.get(base_url, params=params, timeout=10)
-        data = response.json()
-
-        if response.status_code == 200:
-            normalized_input = city.lower().replace(" ", "")
-            chinese_name = CITY_NAME_MAPPING.get(normalized_input, data.get("name", city))
-
-            return {
-                "city": chinese_name,
-                "temp": data["main"]["temp"],
-                "humidity": data["main"]["humidity"],
-                "description": data["weather"][0]["description"],
-                "icon": data["weather"][0]["icon"]
-            }
-        else:
-            return None
-
-    except Exception as e:
-        print(f"获取天气数据时出错: {str(e)}")
-        return None

README.md

@@ -1,2 +0,0 @@
-# cmRemote
-

demo.c

@@ -0,0 +1 @@
+print("hello");