ocr_verify/ocr_validator_layout.py

#!/usr/bin/env python3
"""
OCR验证工具的布局管理模块
包含标准布局、滚动布局、紧凑布局的实现
"""

import streamlit as st
from pathlib import Path
from PIL import Image
from typing import Dict, List, Optional
import plotly.graph_objects as go
from typing import Tuple

from ocr_validator_utils import (
    convert_html_table_to_markdown, 
    parse_html_tables,
    draw_bbox_on_image,
    rotate_image_and_coordinates,
    get_ocr_tool_rotation_config,
    detect_image_orientation_by_opencv  # 新增导入
)


class OCRLayoutManager:
    """OCR布局管理器"""
    
    def __init__(self, validator):
        self.validator = validator
        self.config = validator.config
        self._rotated_image_cache = {}
        self._cache_max_size = 10
        self._orientation_cache = {}  # 缓存方向检测结果
        # self._auto_detected_angle = 0.0  # 自动检测的旋转角度缓存
    
    def clear_image_cache(self):
        """清理所有图像缓存"""
        self._rotated_image_cache.clear()
        
    def clear_cache_for_image(self, image_path: str):
        """清理指定图像的所有缓存"""
        keys_to_remove = [key for key in self._rotated_image_cache.keys() if key.startswith(image_path)]
        for key in keys_to_remove:
            del self._rotated_image_cache[key]
    
    def get_cache_info(self) -> dict:
        """获取缓存信息"""
        return {
            'cache_size': len(self._rotated_image_cache),
            'cached_images': list(self._rotated_image_cache.keys()),
            'max_size': self._cache_max_size
        }
    
    def _manage_cache_size(self):
        """管理缓存大小，超出限制时清理最旧的缓存"""
        if len(self._rotated_image_cache) > self._cache_max_size:
            # 删除最旧的缓存项（FIFO策略）
            oldest_key = next(iter(self._rotated_image_cache))
            del self._rotated_image_cache[oldest_key]
    
    def detect_and_suggest_rotation(self, image_path: str) -> Dict:
        """检测并建议图片旋转角度"""
        if image_path in self._orientation_cache:
            return self._orientation_cache[image_path]
        
        # 使用自动检测功能
        detection_result = detect_image_orientation_by_opencv(image_path)
        
        # 缓存结果
        self._orientation_cache[image_path] = detection_result
        return detection_result
    
    def get_rotation_angle(self) -> float:
        """获取旋转角度 - 增强版本支持自动检测"""
        # 首先尝试从OCR数据中获取（PPStructV3等）
        if self.validator.ocr_data:
            for item in self.validator.ocr_data:
                if isinstance(item, dict) and 'rotation_angle' in item:
                    return item['rotation_angle']
        
        # 如果没有预设角度，尝试自动检测
        if hasattr(self, '_auto_detected_angle'):
            return self._auto_detected_angle
        
        return 0.0
    
    def load_and_rotate_image(self, image_path: str) -> Optional[Image.Image]:
        """加载并根据需要旋转图像"""
        if not image_path or not Path(image_path).exists():
            return None
            
        # 检查缓存
        rotation_angle = self.get_rotation_angle()
        cache_key = f"{image_path}_{rotation_angle}"
        
        if cache_key in self._rotated_image_cache:
            return self._rotated_image_cache[cache_key]
        
        try:
            image = Image.open(image_path)
            
            # 如果需要旋转
            if rotation_angle != 0:
                # 获取OCR工具的旋转配置
                rotation_config = get_ocr_tool_rotation_config(self.validator.ocr_data, self.config)
                
                st.info(f"🔄 检测到文档旋转角度: {rotation_angle}°，正在处理图像和坐标...")
                st.info(f"📋 OCR工具配置: 坐标{'已预旋转' if rotation_config['coordinates_are_pre_rotated'] else '需要旋转'}")
                
                # 判断是否需要旋转坐标
                if rotation_config['coordinates_are_pre_rotated']:
                    # PPStructV3: 坐标已经是旋转后的，只旋转图像
                    if rotation_angle == 270:
                        rotated_image = image.rotate(-90, expand=True)  # 顺时针90度
                    elif rotation_angle == 90:
                        rotated_image = image.rotate(90, expand=True)   # 逆时针90度
                    elif rotation_angle == 180:
                        rotated_image = image.rotate(180, expand=True)  # 180度
                    else:
                        rotated_image = image.rotate(-rotation_angle, expand=True)
                    
                    # 坐标不需要变换，因为JSON中已经是正确的坐标
                    self._rotated_image_cache[cache_key] = rotated_image
                    self._manage_cache_size()
                    return rotated_image
                    
                else:
                    # Dots OCR: 需要同时旋转图像和坐标
                    # 收集所有bbox坐标
                    all_bboxes = []
                    text_to_bbox_map = {}  # 记录文本到bbox索引的映射
                    
                    bbox_index = 0
                    for text, info_list in self.validator.text_bbox_mapping.items():
                        text_to_bbox_map[text] = []
                        for info in info_list:
                            all_bboxes.append(info['bbox'])
                            text_to_bbox_map[text].append(bbox_index)
                            bbox_index += 1
                    
                    # 旋转图像和坐标
                    rotated_image, rotated_bboxes = rotate_image_and_coordinates(
                        image, rotation_angle, all_bboxes, 
                        rotate_coordinates=not rotation_config['coordinates_are_pre_rotated']
                    )
                    
                    # 更新bbox映射 - 使用映射关系确保正确对应
                    for text, bbox_indices in text_to_bbox_map.items():
                        for i, bbox_idx in enumerate(bbox_indices):
                            if bbox_idx < len(rotated_bboxes) and i < len(self.validator.text_bbox_mapping[text]):
                                self.validator.text_bbox_mapping[text][i]['bbox'] = rotated_bboxes[bbox_idx]
                    
                    # 缓存结果
                    self._rotated_image_cache[cache_key] = rotated_image
                    self._manage_cache_size()
                    return rotated_image
                    
            else:
                # 无需旋转，直接缓存原图
                self._rotated_image_cache[cache_key] = image
                self._manage_cache_size()  # 检查并管理缓存大小
                return image
                
        except Exception as e:
            st.error(f"❌ 图像加载失败: {e}")
            return None
    
    def render_content_section(self, layout_type: str = "standard"):
        """渲染内容区域 - 统一方法"""
        st.header("📄 OCR识别内容")
        
        # 显示旋转信息
        # rotation_angle = self.get_rotation_angle()
        # if rotation_angle != 0:
        #     st.info(f"📐 文档旋转角度: {rotation_angle}°")
        
        # 文本选择器
        if self.validator.text_bbox_mapping:
            text_options = ["请选择文本..."] + list(self.validator.text_bbox_mapping.keys())
            selected_index = st.selectbox(
                "选择要校验的文本",
                range(len(text_options)),
                format_func=lambda x: text_options[x][:50] + "..." if len(text_options[x]) > 50 else text_options[x],
                key=f"{layout_type}_text_selector"
            )
            
            if selected_index > 0:
                st.session_state.selected_text = text_options[selected_index]
        else:
            st.warning("没有找到可点击的文本")
    
    def render_md_content(self, layout_type: str):
        """渲染Markdown内容 - 统一方法"""
        if not self.validator.md_content:
            return None, None
            
        # 搜索功能
        search_term = st.text_input(
            "🔍 搜索文本内容", 
            placeholder="输入关键词搜索...", 
            key=f"{layout_type}_search"
        )
        
        display_content = self.validator.md_content
        if search_term:
            lines = display_content.split('\n')
            filtered_lines = [line for line in lines if search_term.lower() in line.lower()]
            display_content = '\n'.join(filtered_lines)
            if filtered_lines:
                st.success(f"找到 {len(filtered_lines)} 行包含 '{search_term}'")
            else:
                st.warning(f"未找到包含 '{search_term}' 的内容")
        
        # 渲染方式选择
        render_mode = st.radio(
            "选择渲染方式",
            ["HTML渲染", "Markdown渲染", "DataFrame表格", "原始文本"],
            horizontal=True,
            key=f"{layout_type}_render_mode"
        )
        
        return display_content, render_mode
    
    def render_content_by_mode(self, content: str, render_mode: str, font_size: int, layout_type: str):
        """根据渲染模式显示内容 - 增强版本"""
        if content is None or render_mode is None:
            return
            
        if render_mode == "HTML渲染":
            # 增强的HTML渲染样式，支持横向滚动
            content_style = f"""
            <style>
            .{layout_type}-content-display {{
                font-size: {font_size}px !important;
                line-height: 1.4;
                color: #333333 !important;
                background-color: #fafafa !important;
                padding: 10px;
                border-radius: 5px;
                border: 1px solid #ddd;
                overflow-x: auto;
                max-width: 100%;
            }}
            
            .{layout_type}-content-display table {{
                width: 100%;
                border-collapse: collapse;
                margin: 10px 0;
                white-space: nowrap;
            }}
            
            .{layout_type}-content-display th,
            .{layout_type}-content-display td {{
                border: 1px solid #ddd;
                padding: 8px;
                text-align: left;
                min-width: 100px;
            }}
            
            .{layout_type}-content-display th {{
                background-color: #f5f5f5;
                position: sticky;
                top: 0;
                z-index: 1;
            }}
            
            .{layout_type}-content-display img {{
                max-width: 100%;
                height: auto;
                border-radius: 4px;
                margin: 10px 0;
            }}
            </style>
            """
            st.markdown(content_style, unsafe_allow_html=True)
            st.markdown(f'<div class="{layout_type}-content-display">{content}</div>', unsafe_allow_html=True)
            
        elif render_mode == "Markdown渲染":
            converted_content = convert_html_table_to_markdown(content)
            st.markdown(converted_content, unsafe_allow_html=True)
            
        elif render_mode == "DataFrame表格":
            if '<table' in content.lower():
                self.validator.display_html_table_as_dataframe(content)
            else:
                st.info("当前内容中没有检测到HTML表格")
                st.markdown(content, unsafe_allow_html=True)
        else:  # 原始文本
            st.text_area(
                "MD内容预览",
                content,
                height=300,
                key=f"{layout_type}_text_area"
            )
    
    # 布局实现
    def create_standard_layout(self, font_size: int = 10, zoom_level: float = 1.0):
        """创建标准布局"""
        if zoom_level is None:
            zoom_level = self.config['styles']['layout']['default_zoom']
            
        # 主要内容区域
        layout = self.config['styles']['layout']
        left_col, right_col = st.columns([layout['content_width'], layout['sidebar_width']])
        
        with left_col:
            self.render_content_section("standard")
            
            # 显示内容
            if self.validator.md_content:
                display_content, render_mode = self.render_md_content("standard")
                self.render_content_by_mode(display_content, render_mode, font_size, "standard")
        
        with right_col:
            self.create_aligned_image_display(zoom_level, "compact")
    
    def create_compact_layout(self, font_size: int = 10, zoom_level: float = 1.0):
        """创建紧凑的对比布局"""
        # 主要内容区域
        layout = self.config['styles']['layout']
        left_col, right_col = st.columns([layout['content_width'], layout['sidebar_width']])                

        with left_col:
            self.render_content_section("compact")

            # 只保留一个内容区域高度选择
            container_height = st.selectbox(
                "选择内容区域高度", 
                [400, 600, 800, 1000, 1200], 
                index=2,
                key="compact_content_height"
            )
            
            # 快速定位文本选择器（使用不同的key）
            if self.validator.text_bbox_mapping:
                text_options = ["请选择文本..."] + list(self.validator.text_bbox_mapping.keys())
                selected_index = st.selectbox(
                    "快速定位文本",
                    range(len(text_options)),
                    format_func=lambda x: text_options[x][:30] + "..." if len(text_options[x]) > 30 else text_options[x],
                    key="compact_quick_text_selector"  # 使用不同的key
                )
                
                if selected_index > 0:
                    st.session_state.selected_text = text_options[selected_index]
            
            # 自定义CSS样式
            st.markdown(f"""
            <style>
            .compact-content {{
                height: {container_height}px;
                overflow-y: auto;
                font-size: {font_size}px !important;
                line-height: 1.4;
                border: 1px solid #ddd;
                padding: 10px;
                background-color: #fafafa !important;
                font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', monospace;
                color: #333333 !important;
            }}
            
            .highlight-text {{
                background-color: #ffeb3b !important;
                padding: 2px 4px;
                border-radius: 3px;
                cursor: pointer;
                color: #333333 !important;
            }}
            
            .selected-highlight {{
                background-color: #4caf50 !important;
                color: white !important;
            }}
            </style>
            """, unsafe_allow_html=True)
            
            # 处理并显示OCR内容
            if self.validator.md_content:
                # 高亮可点击文本
                highlighted_content = self.validator.md_content
                for text in self.validator.text_bbox_mapping.keys():
                    if len(text) > 2:  # 避免高亮过短的文本
                        css_class = "highlight-text selected-highlight" if text == st.session_state.selected_text else "highlight-text"
                        highlighted_content = highlighted_content.replace(
                            text, 
                            f'<span class="{css_class}" title="{text[:50]}...">{text}</span>'
                        )
                st.markdown(
                    f'<div class="compact-content">{highlighted_content}</div>', 
                    unsafe_allow_html=True
                )
        
        with right_col:
            # 修复的对齐图片显示
            self.create_aligned_image_display(zoom_level, "compact")
    
    def create_aligned_image_display(self, zoom_level: float = 1.0, layout_type: str = "aligned"):
        """创建与左侧对齐的图片显示 - 修复显示问题"""
        # 精确对齐CSS
        st.markdown(f"""
        <style>
        .aligned-image-container-{layout_type} {{
            margin-top: -70px;
            padding-top: 0px;
        }}
        .aligned-image-container-{layout_type} h1 {{
            margin-top: 0px !important;
            padding-top: 0px !important;
        }}
        /* 修复：确保Plotly图表容器没有额外边距 */
        .js-plotly-plot, .plotly {{
            margin: 0 !important;
            padding: 0 !important;
        }}
        </style>
        """, unsafe_allow_html=True)
        
        st.markdown(f'<div class="aligned-image-container-{layout_type}">', unsafe_allow_html=True)
        st.header("🖼️ 原图标注")
        
        # 方向检测控制面板
        with st.expander("🔄 图片方向检测", expanded=False):
            col1, col2, col3 = st.columns(3)
            
            with col1:
                if st.button("🔍 自动检测方向", key=f"{layout_type}_detect_orientation"):
                    if self.validator.image_path:
                        with st.spinner("正在检测图片方向..."):
                            detection_result = self.detect_and_suggest_rotation(self.validator.image_path)
                            st.session_state[f'{layout_type}_detection_result'] = detection_result
                        st.rerun()
            
            with col2:
                manual_angle = st.selectbox(
                    "手动设置角度",
                    [0, 90, 180, 270],
                    key=f"{layout_type}_manual_angle"
                )
                if st.button("应用手动角度", key=f"{layout_type}_apply_manual"):
                    self._auto_detected_angle = float(manual_angle)
                    st.success(f"已设置旋转角度为 {manual_angle}°")
                    # 需要清除图片缓存，以及text_bbox_mapping中的bbox
                    self.clear_image_cache()
                    self.validator.process_data()
                    st.rerun()
            
            with col3:
                if st.button("🔄 重置角度", key=f"{layout_type}_reset_angle"):
                    if hasattr(self, '_auto_detected_angle'):
                        delattr(self, '_auto_detected_angle')
                    st.success("已重置旋转角度")
                    # 需要清除图片缓存，以及text_bbox_mapping中的bbox
                    self.clear_image_cache()
                    self.validator.process_data()
                    st.rerun()
            
            # 显示检测结果
            if f'{layout_type}_detection_result' in st.session_state:
                result = st.session_state[f'{layout_type}_detection_result']
                
                st.markdown("### 🎯 检测结果")
                
                # 结果概览
                result_col1, result_col2, result_col3 = st.columns(3)
                with result_col1:
                    st.metric("建议角度", f"{result['detected_angle']}°")
                with result_col2:
                    st.metric("置信度", f"{result['confidence']:.2%}")
                with result_col3:
                    confidence_color = "🟢" if result['confidence'] > 0.7 else "🟡" if result['confidence'] > 0.4 else "🔴"
                    st.metric("可信度", f"{confidence_color}")
                
                # 详细信息
                st.write(f"**检测信息:** {result['message']}")
                
                if 'method_details' in result:
                    st.write("**方法详情:**")
                    for detail in result['method_details']:
                        st.write(f"• {detail}")
                
                # 应用建议角度
                if result['confidence'] > 0.3 and result['detected_angle'] != 0:
                    if st.button(f"✅ 应用建议角度 {result['detected_angle']}°", key=f"{layout_type}_apply_suggested"):
                        self._auto_detected_angle = result['detected_angle']
                        st.success(f"已应用建议角度 {result['detected_angle']}°")
                        # 需要清除图片缓存，以及text_bbox_mapping中的bbox
                        self.clear_image_cache()
                        self.validator.process_data()
                        st.rerun()
                
                # 显示个别方法的结果
                if 'individual_results' in result and len(result['individual_results']) > 1:
                    with st.expander("📊 各方法检测详情", expanded=False):
                        for i, individual in enumerate(result['individual_results']):
                            st.write(f"**方法 {i+1}: {individual['method']}**")
                            st.write(f"角度: {individual['detected_angle']}°, 置信度: {individual['confidence']:.2f}")
                            st.write(f"信息: {individual['message']}")
                            if 'error' in individual:
                                st.error(f"错误: {individual['error']}")
                            st.write("---")
        
        # 图片控制选项
        col1, col2, col3, col4 = st.columns(4)
        with col1:
            current_zoom = st.slider("图片缩放", 0.3, 2.0, zoom_level, 0.1, key=f"{layout_type}_zoom_level")
        with col2:
            show_all_boxes = st.checkbox("显示所有框", value=False, key=f"{layout_type}_show_all_boxes")
        with col3:
            fit_to_container = st.checkbox("适应容器", value=True, key=f"{layout_type}_fit_container")
        with col4:
            # 显示当前角度状态
            current_angle = self.get_rotation_angle()
            st.metric("当前角度", f"{current_angle}°")
        
        # 使用增强的图像加载方法
        image = self.load_and_rotate_image(self.validator.image_path)
        
        if image:
            try:
                # 根据缩放级别调整图片大小
                new_width = int(image.width * current_zoom)
                new_height = int(image.height * current_zoom)
                resized_image = image.resize((new_width, new_height), Image.Resampling.LANCZOS)
                
                # 计算选中的bbox
                selected_bbox = None
                if st.session_state.selected_text and st.session_state.selected_text in self.validator.text_bbox_mapping:
                    info = self.validator.text_bbox_mapping[st.session_state.selected_text][0]
                    bbox = info['bbox']
                    selected_bbox = [int(coord * current_zoom) for coord in bbox]

                # 收集所有框
                all_boxes = []
                if show_all_boxes:
                    for text, info_list in self.validator.text_bbox_mapping.items():
                        for info in info_list:
                            bbox = info['bbox']
                            if len(bbox) >= 4:
                                scaled_bbox = [coord * current_zoom for coord in bbox]
                                all_boxes.append(scaled_bbox)
                
                # 增强的调试信息
                with st.expander("🔍 图像和坐标调试信息", expanded=False):
                    rotation_angle = self.get_rotation_angle()
                    rotation_config = get_ocr_tool_rotation_config(self.validator.ocr_data, self.config)
                    
                    col_debug1, col_debug2, col_debug3 = st.columns(3)
                    with col_debug1:
                        st.write("**图像信息:**")
                        st.write(f"原始尺寸: {image.width} x {image.height}")
                        st.write(f"缩放后尺寸: {resized_image.width} x {resized_image.height}")
                        st.write(f"当前角度: {rotation_angle}°")
                        
                    with col_debug2:
                        st.write("**坐标信息:**")
                        if selected_bbox:
                            st.write(f"选中框: {selected_bbox}")
                        st.write(f"总框数: {len(all_boxes)}")
                        st.write(f"文本框数: {len(self.validator.text_bbox_mapping)}")
                        
                    with col_debug3:
                        st.write("**配置信息:**")
                        st.write(f"工具类型: {rotation_config.get('coordinates_are_pre_rotated', 'unknown')}")
                        st.write(f"缓存状态: {len(self._rotated_image_cache)} 项")
                        if hasattr(self, '_auto_detected_angle'):
                            st.write(f"自动检测角度: {self._auto_detected_angle}°")
                
                # 创建交互式图片
                fig = self.create_resized_interactive_plot(resized_image, selected_bbox, current_zoom, all_boxes)
                
                plot_config = {
                    'displayModeBar': True,
                    'modeBarButtonsToRemove': ['zoom2d', 'select2d', 'lasso2d', 'autoScale2d'],
                    'scrollZoom': True,
                    'doubleClick': 'reset'
                }
                
                st.plotly_chart(
                    fig, 
                    use_container_width=fit_to_container,
                    config=plot_config,
                    key=f"{layout_type}_plot"
                )
                
                # 显示选中文本的详细信息
                if st.session_state.selected_text and st.session_state.selected_text in self.validator.text_bbox_mapping:
                    st.subheader("📍 选中文本详情")
                    
                    info = self.validator.text_bbox_mapping[st.session_state.selected_text][0]
                    bbox = info['bbox']
                    
                    info_col1, info_col2 = st.columns(2)
                    with info_col1:
                        st.write(f"**文本内容:** {st.session_state.selected_text[:30]}...")
                        st.write(f"**类别:** {info['category']}")
                        # 显示旋转信息
                        rotation_angle = self.get_rotation_angle()
                        if rotation_angle != 0:
                            st.write(f"**旋转角度:** {rotation_angle}°")
                
                    with info_col2:
                        st.write(f"**位置:** [{', '.join(map(str, bbox))}]")
                        if len(bbox) >= 4:
                            st.write(f"**大小:** {bbox[2] - bbox[0]} x {bbox[3] - bbox[1]} px")
                
                # 错误标记功能
                col1, col2 = st.columns(2)
                with col1:
                    if st.button("❌ 标记为错误", key=f"{layout_type}_mark_error"):
                        st.session_state.marked_errors.add(st.session_state.selected_text)
                        st.rerun()
                
                with col2:
                    if st.button("✅ 取消错误标记", key=f"{layout_type}_unmark_error"):
                        st.session_state.marked_errors.discard(st.session_state.selected_text)
                        st.rerun()
                        
            except Exception as e:
                st.error(f"❌ 图片处理失败: {e}")
                st.exception(e)
        else:
            st.error("未找到对应的图片文件")
            if self.validator.image_path:
                st.write(f"期望路径: {self.validator.image_path}")

    st.markdown('</div>', unsafe_allow_html=True)
    
    def create_resized_interactive_plot(self, image: Image.Image, selected_bbox: Optional[List[int]], zoom_level: float, all_boxes: list[tuple]) -> go.Figure:
        """
        创建可调整大小的交互式图片 - 修复图像显示和bbox对齐问题
        图片，box坐标全部是已缩放，旋转后的坐标
        """
        fig = go.Figure()
        
        # 添加图片 - Plotly坐标系，原点在左下角
        fig.add_layout_image(
            dict(
                source=image,
                xref="x", yref="y",
                x=0, y=image.height,  # 图片左下角在Plotly坐标系中的位置
                sizex=image.width, 
                sizey=image.height,
                sizing="stretch", 
                opacity=1.0, 
                layer="below"
            )
        )
        
        # 显示所有bbox - 需要坐标转换
        if len(all_boxes) > 0:
            for bbox in all_boxes:
                if len(bbox) >= 4:
                    x1, y1, x2, y2 = bbox[:4]
                    
                    # 转换为Plotly坐标系（翻转Y轴）
                    plot_x1 = x1
                    plot_x2 = x2
                    plot_y1 = image.height - y2  # JSON的y2 -> Plotly的底部
                    plot_y2 = image.height - y1  # JSON的y1 -> Plotly的顶部
                    
                    color = "rgba(0, 100, 200, 0.2)"
                    
                    fig.add_shape(
                        type="rect",
                        x0=plot_x1, y0=plot_y1,
                        x1=plot_x2, y1=plot_y2,
                        line=dict(color="blue", width=1),
                        fillcolor=color,
                    )

        # 高亮显示选中的bbox
        if selected_bbox and len(selected_bbox) >= 4:
            x1, y1, x2, y2 = selected_bbox[:4]
            
            # 转换为Plotly坐标系
            plot_x1 = x1
            plot_x2 = x2
            plot_y1 = image.height - y2  # 翻转Y坐坐标
            plot_y2 = image.height - y1  # 翻转Y坐标
            
            fig.add_shape(
                type="rect",
                x0=plot_x1, y0=plot_y1,
                x1=plot_x2, y1=plot_y2,
                line=dict(color="red", width=3),
                fillcolor="rgba(255, 0, 0, 0.3)",
            )
    
        # 修复：优化显示尺寸计算
        max_display_width = 800
        max_display_height = 600
        
        # 计算合适的显示尺寸，保持宽高比
        aspect_ratio = image.width / image.height
        
        if aspect_ratio > 1:  # 宽图
            display_width = min(max_display_width, image.width)
            display_height = int(display_width / aspect_ratio)
        else:  # 高图
            display_height = min(max_display_height, image.height)
            display_width = int(display_height * aspect_ratio)
        
        # 修复：设置合理的布局参数
        fig.update_layout(
            width=display_width,
            height=display_height,
            margin=dict(l=0, r=0, t=0, b=0),  # 移除所有边距
            showlegend=False,
            plot_bgcolor='white',
            dragmode="pan",
            
            # 修复：X轴设置
            xaxis=dict(
                visible=False,
                range=[0, image.width],
                constrain="domain",
                fixedrange=False,
                autorange=False,
                showgrid=False,
                zeroline=False
            ),
            
            # 修复：Y轴设置，确保范围正确
            yaxis=dict(
                visible=False,
                range=[0, image.height],  # 确保Y轴范围从0到图片高度
                constrain="domain",
                scaleanchor="x",
                scaleratio=1,
                fixedrange=False,
                autorange=False,
                showgrid=False,
                zeroline=False
            )
        )
        
        return fig