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ml6team / deepstream-python

NVIDIA Deepstream 6.1 Python boilerplate
MIT License
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Runing issue while setup config file and put models in Data folder #13

Closed faridelya closed 1 year ago

faridelya commented 1 year ago

Hi hope you doing good. First and foremost i am kinda new to gstream please give me a road map where i can master in gstream like by watching tutorials yeah for python based gstream or any other good stuff for learning it could help me alot thanks .

Goal

so now i am coming towards the problem.

  1. I put config file for yolov4 in this path == > deepstream-python/deepstream/configs/pgies/ yolov4_saftey.txt
  2. I put all models and related filelike engine file etlt and labels and cache file in ==> /app/data/pgies/yolov4/my_folder/ all-files
  3. I made some changes in core.py 
    
def run_pipeline(video_uri: str):
pipeline = Pipeline(
    video_uri=video_uri,
    pgie_config_path=os.path.join(CONFIGS_DIR, "pgies/yolov4_saftey.txt"),  # here i made changes  <--------------
    tracker_config_path=os.path.join(CONFIGS_DIR, "trackers/nvdcf.txt"),
    output_format="mp4",
)
pipeline.run()

 4.  build docker image successfully
 5.  when i run  this command  it gave the following error.

docker run -it --gpus all -v ~/deepstream-python/output:/app/output deepstream python3 run.py 'file:///app/data/videos/sample_720p.h264'

**Error**

/Desktop/farid/deepstream-python/deepstream$ docker run -it --gpus all -v ~/deepstream-python/output:/app/output deepstream python3 run.py 'file:///app/data/videos/sample_720p.h264' INFO:app.pipeline.Pipeline:Playing from URI file:///app/data/videos/sample_720p.h264

(gst-plugin-scanner:7): GStreamer-WARNING **: 05:11:46.981: Failed to load plugin '/usr/lib/x86_64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_inferserver.so': libtritonserver.so: cannot open shared object file: No such file or directory

(gst-plugin-scanner:7): GStreamer-WARNING **: 05:11:46.983: Failed to load plugin '/usr/lib/x86_64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_udp.so': librivermax.so.0: cannot open shared object file: No such file or directory INFO:app.pipeline.Pipeline:Creating Pipeline INFO:app.pipeline.Pipeline:Creating Source bin INFO:app.pipeline.Pipeline:Creating URI decode bin INFO:app.pipeline.Pipeline:Creating Stream mux INFO:app.pipeline.Pipeline:Creating PGIE INFO:app.pipeline.Pipeline:Creating Tracker INFO:app.pipeline.Pipeline:Creating Converter 1 INFO:app.pipeline.Pipeline:Creating Caps filter 1 INFO:app.pipeline.Pipeline:Creating Tiler INFO:app.pipeline.Pipeline:Creating Converter 2 INFO:app.pipeline.Pipeline:Creating OSD INFO:app.pipeline.Pipeline:Creating Queue 1 INFO:app.pipeline.Pipeline:Creating Converter 3 INFO:app.pipeline.Pipeline:Creating Caps filter 2 INFO:app.pipeline.Pipeline:Creating Encoder INFO:app.pipeline.Pipeline:Creating Parser INFO:app.pipeline.Pipeline:Creating Container INFO:app.pipeline.Pipeline:Creating Sink INFO:app.pipeline.Pipeline:Linking elements in the Pipeline: source-bin-00 -> stream-muxer -> primary-inference -> tracker -> convertor1 -> capsfilter1 -> nvtiler -> convertor2 -> onscreendisplay -> queue1 -> mp4-sink-bin INFO:app.pipeline.Pipeline:Starting pipeline gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream/lib/libnvds_nvmultiobjecttracker.so gstnvtracker: Batch processing is ON gstnvtracker: Past frame output is OFF [NvMultiObjectTracker] Initialized ERROR: ../nvdsinfer/nvdsinfer_func_utils.cpp:30 Could not open lib: /app/data, error string: /app/data: cannot open shared object file: No such file or directory [NvMultiObjectTracker] De-initialized Error: gst-resource-error-quark: Failed to create NvDsInferContext instance (1): gstnvinfer.cpp(846): gst_nvinfer_start (): /GstPipeline:pipeline0/GstNvInfer:primary-inference: Config file path: /app/app/../configs/pgies/yolov4_saftey.txt, NvDsInfer Error: NVDSINFER_CUSTOM_LIB_FAILED INFO:app.pipeline.Pipeline:Exiting pipeline

my config file  **yolov4_saftey.txt**

[property] gpu-id=0 net-scale-factor=1.0 offsets=103.939;116.779;123.68 model-color-format=1

labelfile-path=/app/data/pgies/yolov4/export_retrain/labels.txt model-engine-file=/app/data/pgies/yolov4/export_retrain/trt.engine int8-calib-file=/app/data/pgies/yolov4/export_retrain/cal.bin tlt-encoded-model = /app/data/pgies/yolov4/yolov4_resnet18_epoch_080.etlt tlt-model-key=NGpmbHN0ZTNrZHFkOGRxNnFsbW9rbXNxbnU6Yzc5NWM5MjQtZDE1YS00NTYxLTg3YzgtNTU2MWVhNDg1M2M3

infer-dims=3;384;1248 force-implicit-batch-dim=1 maintain-aspect-ratio=1 batch-size=1 network-mode=0 uff-input-order=0 uff-input-blob-name=Input num-detected-classes=6 interval=0 gie-unique-id=1 network-type=0 cluster-mode=3 process-mode=1 output-blob-names=BatchedNMS parse-bbox-func-name=NvDsInferParseCustomBatchedNMSTLT custom-lib-path=/app/data/pgies/libnvds_infercustomparser_tao.so

[class-attrs-all] pre-cluster-threshold=0.3 roi-top-offset=0 roi-bottom-offset=0 detected-min-w=0 detected-min-h=0 detected-max-w=0 detected-max-h=0

faridelya commented 1 year ago

Please @Joxis

faridelya commented 1 year ago

HI @cuongh712 and @Joxis please have a look .i need only to use my custom trained yolov4 in this app for object detection. so which pipline i should use you can check above settings i have done for my models. please check this out . Thanks alot

julestalloen commented 1 year ago

Hi @faridelya, the error indicates that it fails to find the custom inference library, required for yolov4: Config file path: /app/app/../configs/pgies/yolov4_saftey.txt, NvDsInfer Error: NVDSINFER_CUSTOM_LIB_FAILED. Are you sure this file is present inside your container (custom-lib-path=/app/data/pgies/libnvds_infercustomparser_tao.so)?

faridelya commented 1 year ago

Thank you @Joxis for you kind response. I solve this problem and i build and run the docker image but i cannot see the inference video when i run docker image .it show output in terminal but with no display.

which pipline we can use for simple object detecion ( yolov4 ) not for bluring object so we can easily modified config and models path ?

One more question : Can we access this app on remote local computer with rstp://localhost-jetson-ip:port/ds-test on VLC.?

again thanks alot for you time.

julestalloen commented 1 year ago

You can set the output_format to rtsp. This will create an RTSP sink for your output. The URL where you can access the stream will be logged to the console (https://github.com/ml6team/deepstream-python/blob/master/deepstream/app/pipeline.py#L537).

faridelya commented 1 year ago

Thank you very much @Joxis .