训练体系整合与标注单阶段化

- 标注：AI 预标注直写 labels_json（去候选确认两阶段）；重叠去重（minIoU）；全量标注按钮 - 训练：脚本迁移入 server/training/（Go 化 prepare_yolo/analyze_rfdetr，保留 train_server.py）；tflite 产物自检并入训练流程（check_tflite） - 数据目录/权重不进 git；.gitignore 迁移至仓库根
2026-08-26 18:22:56 +08:00
parent 4f39e85882
commit a0b115d954
108 changed files with 10877 additions and 798 deletions
@@ -0,0 +1,141 @@
+import 'dart:convert';
+import 'dart:io';
+
+import 'package:crypto/crypto.dart' show sha256;
+import 'package:flutter_test/flutter_test.dart';
+import 'package:http/http.dart' as http;
+import 'package:http/testing.dart';
+import 'package:observer/models/model_manager.dart';
+
+const _modelBytes = [1, 2, 3, 4, 5, 6, 7, 8];
+
+String _shaHex(List<int> bytes) => sha256.convert(bytes).toString();
+
+Map<String, dynamic> _catalog(List<Map<String, dynamic>> models) =>
+    {'code': 0, 'message': 'ok', 'data': {'version': '0.0.2', 'notes': '', 'models': models}};
+
+Map<String, dynamic> _item({String version = 'v1.0.0', String sha = ''}) => {
+      'datasetId': 7,
+      'datasetName': '野鸡数据集',
+      'version': version,
+      'labels': ['pheasant', 'suspect'],
+      'sizeBytes': _modelBytes.length,
+      'sha256': sha.isEmpty ? _shaHex(_modelBytes) : sha,
+      'downloadUrl': '/download/models/野鸡数据集/latest.tflite',
+    };
+
+void main() {
+  late Directory root;
+  late int downloadHits;
+
+  setUp(() async {
+    root = await Directory.systemTemp.createTemp('model-manager-test');
+    downloadHits = 0;
+  });
+
+  tearDown(() => root.delete(recursive: true));
+
+  ModelManager manager(MockClient client) => ModelManager(
+        baseUrl: 'http://test.local',
+        client: client,
+        rootDir: () async => root,
+      );
+
+  MockClient client(List<Map<String, dynamic>> models) => MockClient((req) async {
+        if (req.url.path == '/api/v1/app/update') {
+          // Response(String) 默认 latin1 编码，中文数据集名会抛异常 → 用 bytes
+          return http.Response.bytes(utf8.encode(jsonEncode(_catalog(models))), 200);
+        }
+        if (req.url.path.startsWith('/download/models/')) {
+          downloadHits++;
+          return http.Response.bytes(_modelBytes, 200);
+        }
+        return http.Response('not found', 404);
+      });
+
+  test('首次拉取：下载模型并落盘（model/labels/meta）', () async {
+    final m = manager(client([_item()]));
+    await m.refresh();
+
+    expect(m.ready, isTrue);
+    expect(m.error, isNull);
+    expect(m.models.length, 1);
+    expect(m.models.first.datasetName, '野鸡数据集');
+    expect(m.models.first.bytes, _modelBytes);
+    expect(downloadHits, 1);
+
+    final dir = Directory('${root.path}/7');
+    expect(await File('${dir.path}/model.tflite').exists(), isTrue);
+    expect(await File('${dir.path}/labels.json').exists(), isTrue);
+    expect(await File('${dir.path}/meta.json').exists(), isTrue);
+  });
+
+  test('版本未变不重复下载（meta 命中直接跳过）', () async {
+    final m = manager(client([_item()]));
+    await m.refresh();
+    expect(downloadHits, 1);
+
+    await m.refresh();
+    expect(downloadHits, 1, reason: 'meta 匹配应跳过下载');
+    expect(m.models.length, 1);
+  });
+
+  test('版本更新触发重新下载', () async {
+    final m = manager(client([_item()]));
+    await m.refresh();
+    expect(downloadHits, 1);
+
+    await m.refresh();
+    expect(downloadHits, 1);
+
+    // 发布新版本：再次刷新应重下
+    await m.refresh();
+    expect(downloadHits, 1);
+    // 上面三次同一版本，重新构造带新版本的 manager（同一 root）
+    final m2 = manager(client([_item(version: 'v2.0.0')]));
+    await m2.refresh();
+    expect(downloadHits, 2);
+    expect(m2.models.first.version, 'v2.0.0');
+  });
+
+  test('sha256 不匹配：重试后失败，保留旧模型并报错', () async {
+    // 第一次下载成功（sha 匹配）
+    final m1 = manager(client([_item()]));
+    await m1.refresh();
+    expect(m1.models.length, 1);
+
+    // 服务器 sha 与文件不符（被篡改/损坏）→ 下载校验失败
+    final bad = _item(version: 'v3.0.0');
+    bad['sha256'] = _shaHex([9, 9, 9]);
+    final m2 = manager(client([bad]));
+    await m2.refresh();
+
+    expect(m2.models.length, 0, reason: '校验失败的模型不应加载');
+    expect(m2.error, isNotNull);
+    expect(m2.error, contains('野鸡数据集'));
+  });
+
+  test('目录下线：清理本地并清空模型', () async {
+    final m = manager(client([_item()]));
+    await m.refresh();
+    expect(m.models.length, 1);
+    expect(await Directory('${root.path}/7').exists(), isTrue);
+
+    final m2 = manager(client([]));
+    await m2.refresh();
+    expect(m2.models, isEmpty);
+    expect(await Directory('${root.path}/7').exists(), isFalse,
+        reason: '下线的数据集模型目录应被清理');
+  });
+
+  test('目录接口异常：不覆盖已有就绪状态', () async {
+    final m = manager(client([_item()]));
+    await m.refresh();
+    expect(m.ready, isTrue);
+
+    final broken = manager(MockClient((_) async => http.Response('boom', 500)));
+    await broken.refresh();
+    expect(broken.ready, isFalse);
+    expect(broken.error, isNotNull);
+  });
+}
@@ -0,0 +1,55 @@
+import 'package:observer/detection/detection_result.dart';
+import 'package:observer/detection/detector_worker.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+DetectionResult box(String label, double score, double x, double y,
+        {int modelId = -1, String modelName = ''}) =>
+    DetectionResult(
+      label: label,
+      score: score,
+      left: x,
+      top: y,
+      right: x + 0.1,
+      bottom: y + 0.1,
+      modelId: modelId,
+      modelName: modelName,
+    );
+
+void main() {
+  test('不同模型同标签重复框：NMS 去重取高分', () {
+    // 野鸡模型与野兔模型都检出了同一只"野鸡"（不同模型对同一目标的重复框）
+    final all = [
+      box('pheasant', 0.18, 0.3, 0.3, modelId: 1, modelName: '野鸡模型'),
+      box('pheasant', 0.55, 0.31, 0.3, modelId: 2, modelName: '野兔模型'),
+    ];
+    final merged = mergeAcrossModels(all, 0.45);
+    expect(merged.length, 1);
+    expect(merged.first.score, 0.55);
+    expect(merged.first.modelName, '野兔模型');
+  });
+
+  test('不同类别互不压制', () {
+    final all = [
+      box('pheasant', 0.3, 0.5, 0.5, modelId: 1),
+      box('hare', 0.7, 0.5, 0.5, modelId: 2), // 同位置但不同类别
+    ];
+    final merged = mergeAcrossModels(all, 0.45);
+    expect(merged.length, 2);
+  });
+
+  test('同模型内部与跨模型合并一致：远处不重叠保留', () {
+    final all = [
+      box('pheasant', 0.2, 0.1, 0.1, modelId: 1, modelName: '野鸡模型'),
+      box('pheasant', 0.3, 0.8, 0.8, modelId: 1, modelName: '野鸡模型'),
+    ];
+    final merged = mergeAcrossModels(all, 0.45);
+    expect(merged.length, 2);
+    expect(merged.first.score, 0.3); // 按分排序
+  });
+
+  test('单条结果原样返回', () {
+    final single = [box('suspect', 0.11, 0.2, 0.2)];
+    final merged = mergeAcrossModels(single, 0.45);
+    expect(identical(merged, single), isTrue);
+  });
+}