import streamlit as st
import cv2
import tempfile
import torch
import numpy as np
from ultralytics import YOLO
from PIL import Image
from io import BytesIO
import requests

@st.cache_resource
def load_yolo_model():
    return YOLO("yolov8n.pt")

def analyze_with_deepseek(text):
    prompt = f"请分析学生的以下行为并提供教学建议：{text}"
    return f"分析：学生可能在积极参与小组讨论。建议教师鼓励团队合作，提升学习主动性。"

def process_video(uploaded_file, model):
    tfile = tempfile.NamedTemporaryFile(delete=False)
    tfile.write(uploaded_file.read())
    cap = cv2.VideoCapture(tfile.name)

    frames = []
    heatmap = np.zeros((480, 640))
    behavior_summary = []

    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            break

        frame = cv2.resize(frame, (640, 480))
        results = model(frame)
        boxes = results[0].boxes.xyxy.cpu().numpy() if results else []

        for box in boxes:
            x1, y1, x2, y2 = map(int, box[:4])
            cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
            cx, cy = int((x1+x2)/2), int((y1+y2)/2)
            heatmap[cy, cx] += 1

        frames.append(frame)
        behavior_summary.append("检测到学生行为")

    cap.release()
    return frames, heatmap, behavior_summary

def display_heatmap(heatmap):
    import matplotlib.pyplot as plt
    import seaborn as sns
    fig, ax = plt.subplots()
    sns.heatmap(heatmap, cmap="YlOrRd", ax=ax)
    st.pyplot(fig)

st.title("🎓 学生课堂行为自动识别与智能反馈系统")
st.markdown("---")

model = load_yolo_model()
uploaded_file = st.file_uploader("请上传课堂视频（mp4格式）", type=["mp4"])

if uploaded_file:
    st.video(uploaded_file)
    with st.spinner("正在分析视频..."):
        frames, heatmap, behavior_summary = process_video(uploaded_file, model)

    st.success("分析完成！")
    st.subheader("📌 注意力热力图")
    display_heatmap(heatmap)

    st.subheader("📊 行为语义分析")
    for idx, summary in enumerate(behavior_summary[:3]):
        text_analysis = analyze_with_deepseek(summary)
        st.info(f"帧 {idx+1}: {text_analysis}")

    st.subheader("📄 教学优化建议（示例）")
    st.markdown("- 增加互动提问频次")
    st.markdown("- 鼓励小组讨论与合作")
    st.markdown("- 适当调整教学节奏，吸引注意力")

    st.download_button("📥 导出教学分析报告", data="报告内容示例...", file_name="teaching_report.txt")