保存评估结果可视化图 Args: context: 处理上下文 bad_regions: 问题区域列表 output_path: 输出路径
(self,
context: ProcessingContext,
bad_regions: List[Dict],
output_path: str)
| 1293 | self._log(f"保存评估结果: {output_path}") |
| 1294 | |
| 1295 | def save_visualization(self, |
| 1296 | context: ProcessingContext, |
| 1297 | bad_regions: List[Dict], |
| 1298 | output_path: str): |
| 1299 | """ |
| 1300 | 保存评估结果可视化图 |
| 1301 | |
| 1302 | Args: |
| 1303 | context: 处理上下文 |
| 1304 | bad_regions: 问题区域列表 |
| 1305 | output_path: 输出路径 |
| 1306 | """ |
| 1307 | if not context.image_path or not os.path.exists(context.image_path): |
| 1308 | return |
| 1309 | |
| 1310 | img = cv2.imread(context.image_path) |
| 1311 | if img is None: |
| 1312 | return |
| 1313 | |
| 1314 | h, w = img.shape[:2] |
| 1315 | |
| 1316 | # 1. 画已检测元素（蓝色） |
| 1317 | for elem in context.elements: |
| 1318 | x1 = max(0, min(w, elem.bbox.x1)) |
| 1319 | y1 = max(0, min(h, elem.bbox.y1)) |
| 1320 | x2 = max(0, min(w, elem.bbox.x2)) |
| 1321 | y2 = max(0, min(h, elem.bbox.y2)) |
| 1322 | cv2.rectangle(img, (x1, y1), (x2, y2), (255, 100, 0), 2) |
| 1323 | |
| 1324 | # 2. 画问题区域（红色=粗粒度，绿色=细粒度） |
| 1325 | for region in bad_regions: |
| 1326 | x1, y1, x2, y2 = region['bbox'] |
| 1327 | color = (0, 0, 255) if region.get('channel') == 'coarse' else (0, 255, 0) |
| 1328 | cv2.rectangle(img, (x1, y1), (x2, y2), color, 3) |
| 1329 | # 标注 |
| 1330 | text = f"{region['area_ratio']*100:.1f}%" |
| 1331 | cv2.putText(img, text, (x1, y1-10), |
| 1332 | cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 1) |
| 1333 | |
| 1334 | # 3. 图例 |
| 1335 | cv2.putText(img, "Blue: Detected", (10, 30), |
| 1336 | cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 100, 0), 2) |
| 1337 | cv2.putText(img, "Red: Missing (coarse)", (10, 60), |
| 1338 | cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2) |
| 1339 | cv2.putText(img, "Green: Missing (fine)", (10, 90), |
| 1340 | cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2) |
| 1341 | |
| 1342 | cv2.imwrite(output_path, img) |
| 1343 | self._log(f"保存可视化结果: {output_path}") |
| 1344 | |
| 1345 | def save_uncovered_mask(self, |
| 1346 | context: ProcessingContext, |