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fix: 公式报告 4 项修复 — 通用章节+AI接口+图片路径+标题数字

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修复一: _generate_formula_report 封面后恢复
  _add_company_description_page/doc
  _add_data_acquisition_section/doc
  _add_data_processing_section/doc

修复二: _call_minimax_text / _call_minimax_vision
  URL 自动补齐 /chat/completions 后缀

修复三: _call_minimax_vision
  MIME 类型动态检测 (.png→image/png, 其他→image/jpeg)

修复四: _add_hyperspectral_images_section
  航线图搜索: 多路径 + rglob 递归查找
  去掉所有硬编码编号 (3.1/图3-2/3-3/3-4/3-5/3-6)
This commit is contained in:
duxin
2026-07-09 13:12:14 +08:00
parent fc6036efb7
commit b88bab57ee
1 changed files with 35 additions and 18 deletions
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51
src/postprocessing/report_word.py
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@ -368,6 +368,8 @@ class WaterQualityReportGenerator:
return "（Minimax API Key 未配置，请设置 MINIMAX_API_KEY 环境变量）" return "（Minimax API Key 未配置，请设置 MINIMAX_API_KEY 环境变量）"
url = self.minimax_base_url url = self.minimax_base_url
if not url.endswith("/chat/completions"):
url = f"{url.rstrip('/')}/chat/completions"
payload: Dict[str, Any] = { payload: Dict[str, Any] = {
"model": self.minimax_text_model, "model": self.minimax_text_model,
@ -433,6 +435,12 @@ class WaterQualityReportGenerator:
return f"（读取图片失败：{e}）" return f"（读取图片失败：{e}）"
url = self.minimax_base_url url = self.minimax_base_url
if not url.endswith("/chat/completions"):
url = f"{url.rstrip('/')}/chat/completions"
# 动态 MIME 类型：PNG 和 JPEG 分别处理，避免 API 400
ext = image_path.suffix.lower()
mime_type = "image/png" if ext == ".png" else "image/jpeg"
payload: Dict[str, Any] = { payload: Dict[str, Any] = {
"model": self.minimax_vision_model, "model": self.minimax_vision_model,
@ -444,7 +452,7 @@ class WaterQualityReportGenerator:
{"type": "text", "text": user_prompt}, {"type": "text", "text": user_prompt},
{ {
"type": "image_url", "type": "image_url",
"image_url": {"url": f"data:image/jpeg;base64,{img_b64}"}, "image_url": {"url": f"data:{mime_type};base64,{img_b64}"},
}, },
], ],
} }
@ -961,6 +969,11 @@ class WaterQualityReportGenerator:
try: progress.update(1) try: progress.update(1)
except Exception: pass except Exception: pass
# ── 通用章节：单位介绍 / 数据采集 / 工作流程 ──
self._add_company_description_page(doc)
self._add_data_acquisition_section(doc)
self._add_data_processing_section(doc)
# ── 1. 项目背景 ── # ── 1. 项目背景 ──
h1 = doc.add_heading("1 项目背景", level=1) h1 = doc.add_heading("1 项目背景", level=1)
self._style_heading(h1, 1) self._style_heading(h1, 1)
@ -1422,29 +1435,33 @@ class WaterQualityReportGenerator:
def _add_hyperspectral_images_section(self, doc): def _add_hyperspectral_images_section(self, doc):
"""添加高光谱图像、耀斑区域和去耀斑图像展示""" """添加高光谱图像、耀斑区域和去耀斑图像展示"""
h = doc.add_heading("3.1 高光谱图像处理过程", level=2) h = doc.add_heading("高光谱图像处理过程", level=2)
self._style_heading(h, level=2) self._style_heading(h, level=2)
work_dir_path = self.work_dir work_dir_path = self.work_dir
vis_dir = self.visualization_dir vis_dir = self.visualization_dir
# 0. 航线规划图 # 0. 航线规划图（鲁棒搜索：多路径 + rglob）
flight_path_img_path = work_dir_path / "12_visualization" / "flight_paths"
h3 = doc.add_heading("航线规划：", level=3) h3 = doc.add_heading("航线规划：", level=3)
self._style_heading(h3, level=3) self._style_heading(h3, level=3)
# 查找航线图文件
flight_map_files = [] flight_map_files = []
if flight_path_img_path.exists(): flight_search_dirs = [
flight_map_files = list(flight_path_img_path.glob("*.png")) + list(flight_path_img_path.glob("*.jpg")) work_dir_path / "12_visualization" / "flight_paths",
vis_dir / "flight_paths",
vis_dir,
]
for search_dir in flight_search_dirs:
if search_dir.exists():
flight_map_files = list(search_dir.rglob("*.png")) + list(search_dir.rglob("*.jpg"))
if flight_map_files:
break
if flight_map_files: if flight_map_files:
# 使用最新的航线图文件
latest_flight_map = max(flight_map_files, key=lambda p: p.stat().st_mtime) latest_flight_map = max(flight_map_files, key=lambda p: p.stat().st_mtime)
success = self._add_image_with_caption(doc, str(latest_flight_map), "图3-1 航线规划", width=Inches(5.5)) success = self._add_image_with_caption(doc, str(latest_flight_map), "航线规划", width=Inches(5.5))
if success: if success:
# AI 分析航线规划图
flight_analysis = self._analyze_flight_path_image(str(latest_flight_map)) flight_analysis = self._analyze_flight_path_image(str(latest_flight_map))
self._add_ai_analysis_paragraph(doc, flight_analysis) self._add_ai_analysis_paragraph(doc, flight_analysis)
else: else:
@ -1455,7 +1472,7 @@ class WaterQualityReportGenerator:
h3 = doc.add_heading("高光谱原始影像：", level=3) h3 = doc.add_heading("高光谱原始影像：", level=3)
self._style_heading(h3, level=3) self._style_heading(h3, level=3)
if hyperspectral_img_path.exists(): if hyperspectral_img_path.exists():
self._add_image_with_caption(doc, str(hyperspectral_img_path), "图3-2 高光谱原始影像", width=Inches(5.5)) self._add_image_with_caption(doc, str(hyperspectral_img_path), "高光谱原始影像", width=Inches(5.5))
else: else:
doc.add_paragraph("[高光谱原始影像 - 文件未找到]") doc.add_paragraph("[高光谱原始影像 - 文件未找到]")
@ -1465,7 +1482,7 @@ class WaterQualityReportGenerator:
self._style_heading(h3, level=3) self._style_heading(h3, level=3)
if water_mask_overlay_path.exists(): if water_mask_overlay_path.exists():
success = self._add_image_with_caption(doc, str(water_mask_overlay_path), success = self._add_image_with_caption(doc, str(water_mask_overlay_path),
"图3-3 水体区域识别（蓝色半透明区域为水域）", "水体区域识别（蓝色半透明区域为水域）",
width=Inches(5.5)) width=Inches(5.5))
if success: if success:
water_analysis = self._analyze_water_mask_overlay(str(water_mask_overlay_path)) water_analysis = self._analyze_water_mask_overlay(str(water_mask_overlay_path))
@ -1480,13 +1497,13 @@ class WaterQualityReportGenerator:
h3 = doc.add_heading("耀斑区域识别结果：", level=3) h3 = doc.add_heading("耀斑区域识别结果：", level=3)
self._style_heading(h3, level=3) self._style_heading(h3, level=3)
if glint_img_path.exists(): if glint_img_path.exists():
self._add_image_with_caption(doc, str(glint_img_path), "图3-4 耀斑区域识别结果", width=Inches(5.5)) self._add_image_with_caption(doc, str(glint_img_path), "耀斑区域识别结果", width=Inches(5.5))
else: else:
# 尝试查找其他可能的耀斑预览图 # 尝试查找其他可能的耀斑预览图
glint_files = list(vis_dir.glob("glint_deglint_previews/*glint*.png")) glint_files = list(vis_dir.glob("glint_deglint_previews/*glint*.png"))
if glint_files: if glint_files:
glint_img_path = glint_files[0] glint_img_path = glint_files[0]
self._add_image_with_caption(doc, str(glint_img_path), "图3-4 耀斑区域识别结果", width=Inches(5.5)) self._add_image_with_caption(doc, str(glint_img_path), "耀斑区域识别结果", width=Inches(5.5))
else: else:
doc.add_paragraph("[耀斑区域识别结果 - 文件未找到]") doc.add_paragraph("[耀斑区域识别结果 - 文件未找到]")
@ -1497,13 +1514,13 @@ class WaterQualityReportGenerator:
h3 = doc.add_heading("去除耀斑后的影像：", level=3) h3 = doc.add_heading("去除耀斑后的影像：", level=3)
self._style_heading(h3, level=3) self._style_heading(h3, level=3)
if deglint_img_path.exists(): if deglint_img_path.exists():
self._add_image_with_caption(doc, str(deglint_img_path), "图3-5 去除耀斑后的高光谱影像", width=Inches(5.5)) self._add_image_with_caption(doc, str(deglint_img_path), "去除耀斑后的高光谱影像", width=Inches(5.5))
else: else:
# 尝试查找其他去耀斑预览图 # 尝试查找其他去耀斑预览图
deglint_files = list(vis_dir.glob("glint_deglint_previews/*deglint*.png")) deglint_files = list(vis_dir.glob("glint_deglint_previews/*deglint*.png"))
if deglint_files: if deglint_files:
deglint_img_path = deglint_files[0] deglint_img_path = deglint_files[0]
self._add_image_with_caption(doc, str(deglint_img_path), "图3-5 去除耀斑后的影像", width=Inches(5.5)) self._add_image_with_caption(doc, str(deglint_img_path), "去除耀斑后的影像", width=Inches(5.5))
else: else:
doc.add_paragraph("[去除耀斑后的影像 - 文件未找到]") doc.add_paragraph("[去除耀斑后的影像 - 文件未找到]")
@ -1531,7 +1548,7 @@ class WaterQualityReportGenerator:
if sampling_map_files: if sampling_map_files:
# 使用最新的采样点分布图文件 # 使用最新的采样点分布图文件
latest_sampling_map = max(sampling_map_files, key=lambda p: p.stat().st_mtime) latest_sampling_map = max(sampling_map_files, key=lambda p: p.stat().st_mtime)
success = self._add_image_with_caption(doc, str(latest_sampling_map), "图3-6 采样点分布图", width=Inches(5.5)) success = self._add_image_with_caption(doc, str(latest_sampling_map), "采样点分布图", width=Inches(5.5))
if success: if success:
# AI 分析采样点分布图 # AI 分析采样点分布图