新模块功能：蚕茧视频识别

bbit_ai/app/app.py

@@ -15,7 +15,6 @@ from routers.RabbitMQ import rqRouter
 from routers.Report import reportRouter
 from routers.Service import serviceRouter
 from routers.Vision import visionRouter
-from service.Analyze import mq_pull_analysis_async
 
 
 async def ai_lab():
@@ -47,7 +46,7 @@ async def ai_lab():
         app.include_router(r, prefix="/llm", tags=["llm"])
     app.include_router(visionRouter, prefix="/cv", tags=["cv"])
     app.include_router(publicRouter, prefix="/api/public", tags=["api"])
-    config = Config(app=app, host="0.0.0.0", port=13011, log_level="info")
+    config = Config(app=app, host="0.0.0.0", port=13011, log_level="debug")
     server = Server(config)
     await server.serve()
 
@@ -59,7 +58,7 @@ async def main():
     task_api = asyncio.create_task(ai_lab())
 
     # MCP服务-ailab
-    endpoint_url_ai_lab = "wss://ai.ronsunny.cn:8090/aimcp/mcp_endpoint/mcp/?token=TsSP9lBq6Oa1WMkachHoS2TtNt4GKV/Gli24pk5Rjpk%3D"
+    # endpoint_url_ai_lab = "wss://ai.ronsunny.cn:8090/aimcp/mcp_endpoint/mcp/?token=TsSP9lBq6Oa1WMkachHoS2TtNt4GKV/Gli24pk5Rjpk%3D"
     # endpoint_url_ai_lab = "ws://ce_bot_mcp:8004/mcp_endpoint/mcp/?token=TsSP9lBq6Oa1WMkachHoS2TtNt4GKV/Gli24pk5Rjpk%3D"
     # task_mcp1 = asyncio.create_task(init_mcp_server(endpoint_url_ai_lab))
 
@@ -68,10 +67,10 @@ async def main():
     task_mcp2 = asyncio.create_task(init_mcp_server(endpoint_url_ql))
 
     # RabbitMQ服务
-    task_mq = asyncio.create_task(mq_pull_analysis_async())
+    # task_mq = asyncio.create_task(mq_pull_analysis_async())
 
     # await asyncio.gather(task_api, task_mcp1, task_mcp2, task_mq)
-    await asyncio.gather(task_api, task_mcp2, task_mq)
+    await asyncio.gather(task_api, task_mcp2)
 
 
 if __name__ == "__main__":

bbit_ai/app/config/minIO.py

@@ -22,11 +22,10 @@ def push_file(bucket_name, object_name, file_bytes, contents, content_type):
     )
 
 
-def get_upload_token(bucket_name, object_name, xpires=timedelta(hours=1)):
-    upload_url = minio_client.presigned_put_object(
+def get_upload_token(user_id, bucket_name, object_name, xpires=timedelta(minutes=15)):
+    return minio_client.presigned_put_object(
         bucket_name=bucket_name, object_name=object_name, expires=xpires
     )
-    return {"upload_url": upload_url, "object_name": object_name}
 
 
 def get_temp_url(bucket_name, object_name):

bbit_ai/app/db/postgres.py

@@ -753,3 +753,97 @@ def get_sca_image_list(user_id, name, page=1, page_size=10):
                 )
 
     return total, result
+
+
+def get_sca_video_list(name, page=1, page_size=10):
+    """
+    获取用户已分析视频列表，带分页
+    """
+    offset = (page - 1) * page_size
+
+    with pg_pool.getConn() as conn:
+        with conn.cursor() as cursor:
+            # 1️⃣ 查询总条数
+            cursor.execute(
+                """
+                SELECT COUNT(*)
+                FROM sca_videos
+                WHERE (%s = '' OR name LIKE '%%' || %s || '%%')
+                """,
+                (name, name),
+            )
+            total = cursor.fetchone()[0]
+
+            # 2️⃣ 查询当前页数据
+            cursor.execute(
+                """
+                SELECT id, name, raw_object_name, ai_object_name, duration, size, video_codec, audio_codec,
+                       overall_bit_rate, resolution, sc_analysis_time, sc_analysis_total_count, sc_analysis_max_count,
+                       sc_analysis_primary_type, sc_analysis_secondary_type, other_info, created_at
+                FROM sca_videos
+                WHERE (%s = '' OR name LIKE '%%' || %s || '%%')
+                ORDER BY created_at DESC
+                LIMIT %s OFFSET %s
+                """,
+                (name, name, page_size, offset),
+            )
+
+            rows = cursor.fetchall()
+
+            result = []
+            for row in rows:
+                result.append(
+                    {
+                        "id": row[0],
+                        "name": row[1],
+                        "raw_video_url": get_temp_url("video-sca", "raw/" + row[2]),
+                        "ai_video_url": get_temp_url("video-sca", "ai/" + row[3]),
+                        "duration": MyUtils.safe_round(row[4], 2),
+                        "size_kb": MyUtils.safe_round(row[5] / 1024, 2),
+                        "video_codec": row[6],
+                        "audio_codec": row[7],
+                        "overall_bit_rate": row[8],
+                        "resolution": row[9],
+                        "sc_analysis_time": MyUtils.safe_round(row[10], 2),
+                        "sc_analysis_total_count": row[11],
+                        "sc_analysis_max_count": row[12],
+                        "sc_analysis_primary_type": row[13],
+                        "sc_analysis_secondary_type": row[14],
+                        "other_info": json.loads(row[15]),
+                        "created_at": MyUtils.format_datetime(row[16]),
+                    }
+                )
+
+    return total, result
+
+
+def get_sca_video_details(v_id):
+    """
+    获取指定视频的分析明细列表
+    """
+    with pg_pool.getConn() as conn:
+        with conn.cursor() as cursor:
+            cursor.execute(
+                """
+                SELECT id, v_id, time_stamp, other_info
+                FROM sca_video_details
+                WHERE v_id = %s
+                ORDER BY time_stamp ASC
+                """,
+                (v_id,),
+            )
+
+            rows = cursor.fetchall()
+            result = []
+            for row in rows:
+                # other_info 从 JSON 字符串解析回字典
+                result.append(
+                    {
+                        "id": row[0],
+                        "v_id": row[1],
+                        "time_stamp": row[2],
+                        "other_info": row[3],
+                    }
+                )
+
+    return result

bbit_ai/app/routers/Vision.py

@@ -153,8 +153,41 @@ def getSilkwormCocoonAnalysisTasks(
     )
 
 
-@visionRouter.post("/getIVASCUploadToken")
-def getIVASCUploadToken():
+# ————————————————————————————————蚕茧视频识别任务————————————————————————————————————————————————
+
+
+@visionRouter.get("/getIVASCUploadToken")
+def getIVASCUploadToken(
+    user_id: UUID = Depends(get_user_id_from_token),
+):
     # 生成唯一文件名，避免覆盖
     object_name = f"raw/{uuid.uuid4()}"
-    return get_upload_token("video-sca", object_name)
+    return BaseResponse(data=get_upload_token(user_id, "video-sca", object_name))
+
+
+@visionRouter.get("/getScVideoList")
+def getScVideoList(
+    user_id: UUID = Depends(get_user_id_from_token),
+    name: str = "",
+    page: int = Query(1, ge=1),
+    page_size: int = Query(10, ge=1, le=100),
+):
+    if not user_id:
+        return {"error": "userId is required"}
+    total, items = pg.get_sca_video_list(name, page=page, page_size=page_size)
+    return BaseResponse(
+        data={
+            "total": total,
+            "items": items,
+        }
+    )
+
+
+@visionRouter.get("/getAnalyticsDetailBySCVideoId")
+def getAnalyticsDetailBySCVideoId(
+    user_id: UUID = Depends(get_user_id_from_token),
+    vId: str = "",
+):
+    if not user_id:
+        return {"error": "userId is required"}
+    return BaseResponse(data=pg.get_sca_video_details(vId))

bbit_ai/app/service/vision.py

@@ -132,18 +132,6 @@ def process_silkworm_cocoon_image(
     # YOLO检测
     img_bytes_out, results_json = YOLOSingleton.detect(img_bytes)
 
-    # results_json = {
-    #     "total_objects": "",
-    #     "max_confidence": "",
-    #     "min_confidence": "",
-    #     "avg_confidence": "",
-    #     "class_counts": "",
-    #     "speed_ms": {
-    #         "preprocess": "",
-    #         "inference": "",
-    #         "postprocess": "",
-    #     },
-    # }
     speed_json = results_json.get("speed_ms")
 
     file_bytes_out = BytesIO(img_bytes_out)