After I run ./deepstream-segmentation-analytics -c dstest_segmentation_config_industrial.txt -i usr_input.txt. It said fail to load the config file.
Get CPU profile_start()
Get the line: batch_size=2
Get the line: width=512
Get the line: height=512
Get the line: stream0=/opt/nvidia/deepstream/deepstream/sources/apps/sample_apps/deepstream-segmentation-analytics/image
stream0
Get the line: stream1=images1
stream1
Get the line: stream2=images2
stream2
Get the line: pro_per_sec=40
Get the line: no_streams=1
Get the line: production=1
batchSize = 2, width = 512, height = 512
no_streams = 1, pro_per_sec = 40
production = 1
Get the batchSize = 2
Get the num_sources = 1
Get the infer_config_file = dstest_segmentation_config_industrial.txt
Get the MUXER_OUTPUT_WIDTH = 512
Get the MUXER_OUTPUT_HEIGHT = 512
Get CPU profile_end()
For frame = 1, CPU time accumulated 40.0066
Loading the image file: /opt/nvidia/deepstream/deepstream/sources/apps/sample_apps/deepstream-segmentation-analytics/image/0599.jpg
Failed to load config file: No such file or directory
** ERROR: <gst_nvinfer_parse_config_file:1260>: failed
Now playing: /opt/nvidia/deepstream/deepstream/sources/apps/sample_apps/deepstream-segmentation-analytics/image/0599.jpg,
Opening in BLOCKING MODE
Opening in BLOCKING MODE
0:00:00.235565280 15770 0x5597210930 WARN nvinfer gstnvinfer.cpp:769:gst_nvinfer_start:<primary-nvinference-engine> error: Configuration file parsing failed
0:00:00.235627680 15770 0x5597210930 WARN nvinfer gstnvinfer.cpp:769:gst_nvinfer_start:<primary-nvinference-engine> error: Config file path: jpg
Running...
ERROR from element primary-nvinference-engine: Configuration file parsing failed
Error details: /dvs/git/dirty/git-master_linux/deepstream/sdk/src/gst-plugins/gst-nvinfer/gstnvinfer.cpp(769): gst_nvinfer_start (): /GstPipeline:dstest-image-decode-pipeline/GstNvInfer:primary-nvinference-engine:
Config file path: jpg
Returned, stopping playback
Deleting pifile_outpeline
Move the file: out_rgba_0599.jpg into the mask directory
Delete the file: /opt/nvidia/deepstream/deepstream/sources/apps/sample_apps/deepstream-segmentation-analytics/image/0599.jpg
Any assistance you can provide would be greatly appreciated.
I tried deepstream-segmentation-test but also had some issue. One of your colleages recommand me the deepstream-segmentation-analytics… So which one could help me to output the binary mask(black&white mask) from maskrcnn model?
Sorry I mixed them up. It was deepstream-mrcnn-test I got some issue on getting the inference masks. The issue is still remain…
I’m ok with deepstream-segmentation-test. But the questions are:
The output masks have 4 colors in deepstream-segementation-test, how could I change the color to white masks and black background?
How could I save the content on display to image files?
Maskrcnn model has 3 layers but the segematation model in deepstream-segementation-test only has 2 layers. Is it the same way to output maskrcnn masks?
Thanks!~
The output masks have 4 colors in deepstream-segementation-test, how could I change the color to white masks and black background?
[amycao] nvsegvisual overlay the mask color pixel by pixel, you can add one probe on nvsegvisual src pad, segmentation model output information NvDsInferSegmentationMeta stored as NvDsUserMeta to the frame_user_meta_list of the corresponding frame_meta or object_user_meta_list of the corresponding object with the meta_type set to NVDSINFER_SEGMENTATION_META. you can base on NvDsInferSegmentationMeta field class_map to change class mask color pixel by pixel as you want.
How could I save the content on display to image files?
[amycao] you can refer to sources/apps/apps-common/src/deepstream_sink_bin.c function create_encode_file_bin for how to save output to file.
Maskrcnn model has 3 layers but the segematation model in deepstream-segementation-test only has 2 layers. Is it the same way to output maskrcnn masks?
