我在基于【SDK案例系列 10】基于 Live555 + MindX SDK + Pytorch YoLoV5的视频检测 https://blog.csdn.net/hiascend/article/details/128588487?spm=1001.2014.3001.5502
修改了pipeline同时拿到序列化数据以及检测的视频,但是我想获取某一帧的图片该如何实现?
pipeline如下:
{
"classification": {
"stream_config": {
"deviceId": "0"
},
"mxpi_rtspsrc0": {
"factory": "mxpi_rtspsrc",
"props": {
"rtspUrl": "rtsp://127.0.0.1:8554/zhanyong",
"channelId": "0"
},
"next": "mxpi_videodecoder0"
},
"mxpi_videodecoder0": {
"factory": "mxpi_videodecoder",
"props": {
"inputVideoFormat": "H264",
"outputImageFormat": "YUV420SP_NV12",
"vdecChannelId": "0"
},
"next": "tee0"
},
"tee0": {
"factory": "tee",
"next": [
"queue1",
"queue2"
]
},
"queue1": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "mxpi_imageresize0"
},
"queue2": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "mxpi_opencvosd_plugin:0"
},
"mxpi_imageresize0": {
"props": {
"dataSource": "mxpi_videodecoder0",
"resizeHeight": "640",
"resizeWidth": "640",
"resizeType": "Resizer_KeepAspectRatio_Fit"
},
"factory": "mxpi_imageresize",
"next": "queue3"
},
"queue3": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "mxpi_modelinfer0"
},
"mxpi_modelinfer0": {
"props": {
"dataSource": "mxpi_imageresize0",
"modelPath": "data/models/yolov5/yolov5l.om",
"postProcessConfigPath": "data/models/yolov5/yolov5.cfg",
"labelPath": "data/models/yolov5/coco2014.names",
"postProcessLibPath": "libMpYOLOv5PostProcessor.so"
},
"factory": "mxpi_modelinfer",
"next": "queue4"
},
"queue4": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "tee1"
},
"tee1": {
"factory": "tee",
"next": ["mxpi_dataserialize0","mxpi_object2osdinstances0"]
},
"mxpi_dataserialize0": {
"props": {
"outputDataKeys": "mxpi_modelinfer0"
},
"factory": "mxpi_dataserialize",
"next": "appsink1"
},
"mxpi_object2osdinstances0": {
"props": {
"dataSource": "mxpi_modelinfer0",
"colorMap":"100,100,100|200,200,200|0,128,255|255,128,0",
"fontFace":"16",
"fontScale":"0.5",
"fontThickness":"2",
"fontLineType":"16",
"rectThickness":"2",
"rectLineType":"16"
},
"factory":"mxpi_object2osdinstances",
"next": "queue5"
},
"queue5": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "mxpi_opencvosd_plugin:1"
},
"mxpi_opencvosd_plugin":{
"factory":"mxpi_opencvosd",
"next":"queue6"
},
"queue6": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "mxpi_videoencoder0"
},
"mxpi_videoencoder0": {
"props": {
"imageHeight": "1080",
"imageWidth": "1920",
"inputFormat": "YUV420SP_NV12",
"outputFormat": "H264",
"fps": "1",
"maxBitRate":"20000",
"iFrameInterval": "50"
},
"factory": "mxpi_videoencoder",
"next": "queue7"
},
"queue7": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "appsink0"
},
"appsink0": {
"factory": "appsink"
},
"appsink1": {
"factory": "appsink"
}
}
}
这种方式存储的图片显示格式有问题,请问有大佬帮忙解决吗
我在基于【SDK案例系列 10】基于 Live555 + MindX SDK + Pytorch YoLoV5的视频检测 https://blog.csdn.net/hiascend/article/details/128588487?spm=1001.2014.3001.5502
修改了pipeline同时拿到序列化数据以及检测的视频,但是我想获取某一帧的图片该如何实现?
pipeline如下:
{
"classification": {
"stream_config": {
"deviceId": "0"
},
"mxpi_rtspsrc0": {
"factory": "mxpi_rtspsrc",
"props": {
"rtspUrl": "rtsp://127.0.0.1:8554/zhanyong",
"channelId": "0"
},
"next": "mxpi_videodecoder0"
},
"mxpi_videodecoder0": {
"factory": "mxpi_videodecoder",
"props": {
"inputVideoFormat": "H264",
"outputImageFormat": "YUV420SP_NV12",
"vdecChannelId": "0"
},
"next": "tee0"
},
"tee0": {
"factory": "tee",
"next": [
"queue1",
"queue2"
]
},
"queue1": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "mxpi_imageresize0"
},
"queue2": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "mxpi_opencvosd_plugin:0"
},
"mxpi_imageresize0": {
"props": {
"dataSource": "mxpi_videodecoder0",
"resizeHeight": "640",
"resizeWidth": "640",
"resizeType": "Resizer_KeepAspectRatio_Fit"
},
"factory": "mxpi_imageresize",
"next": "queue3"
},
"queue3": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "mxpi_modelinfer0"
},
"mxpi_modelinfer0": {
"props": {
"dataSource": "mxpi_imageresize0",
"modelPath": "data/models/yolov5/yolov5l.om",
"postProcessConfigPath": "data/models/yolov5/yolov5.cfg",
"labelPath": "data/models/yolov5/coco2014.names",
"postProcessLibPath": "libMpYOLOv5PostProcessor.so"
},
"factory": "mxpi_modelinfer",
"next": "queue4"
},
"queue4": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "tee1"
},
"tee1": {
"factory": "tee",
"next": ["mxpi_dataserialize0","mxpi_object2osdinstances0"]
},
"mxpi_dataserialize0": {
"props": {
"outputDataKeys": "mxpi_modelinfer0"
},
"factory": "mxpi_dataserialize",
"next": "appsink1"
},
"mxpi_object2osdinstances0": {
"props": {
"dataSource": "mxpi_modelinfer0",
"colorMap":"100,100,100|200,200,200|0,128,255|255,128,0",
"fontFace":"16",
"fontScale":"0.5",
"fontThickness":"2",
"fontLineType":"16",
"rectThickness":"2",
"rectLineType":"16"
},
"factory":"mxpi_object2osdinstances",
"next": "queue5"
},
"queue5": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "mxpi_opencvosd_plugin:1"
},
"mxpi_opencvosd_plugin":{
"factory":"mxpi_opencvosd",
"next":"queue6"
},
"queue6": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "mxpi_videoencoder0"
},
"mxpi_videoencoder0": {
"props": {
"imageHeight": "1080",
"imageWidth": "1920",
"inputFormat": "YUV420SP_NV12",
"outputFormat": "H264",
"fps": "1",
"maxBitRate":"20000",
"iFrameInterval": "50"
},
"factory": "mxpi_videoencoder",
"next": "queue7"
},
"queue7": {
"props": {
"max-size-buffers": "100"
},
"factory": "queue",
"next": "appsink0"
},
"appsink0": {
"factory": "appsink"
},
"appsink1": {
"factory": "appsink"
}
}
}
这种方式存储的图片显示格式有问题,请问有大佬帮忙解决吗