wget https://nvidia.box.com/shared/static/veuuimq6pwvd62p9fresqhrrmfqz0e2f.mp4 -O pedestrians.mp4
–2024-01-15 09:46:42-- https://nvidia.box.com/shared/static/veuuimq6pwvd62p9fresqhrrmfqz0e2f.mp4
Resolving nvidia.box.com (nvidia.box.com)… 74.112.186.144
Connecting to nvidia.box.com (nvidia.box.com)|74.112.186.144|:443… connected.
HTTP request sent, awaiting response… 301 Moved Permanently
Location: /public/static/veuuimq6pwvd62p9fresqhrrmfqz0e2f.mp4 [following]
–2024-01-15 09:46:42-- https://nvidia.box.com/public/static/veuuimq6pwvd62p9fresqhrrmfqz0e2f.mp4
Reusing existing connection to nvidia.box.com:443.
HTTP request sent, awaiting response… 301 Moved Permanently
Location: https://nvidia.app.box.com/public/static/veuuimq6pwvd62p9fresqhrrmfqz0e2f.mp4 [following]
–2024-01-15 09:46:42-- https://nvidia.app.box.com/public/static/veuuimq6pwvd62p9fresqhrrmfqz0e2f.mp4
Resolving nvidia.app.box.com (nvidia.app.box.com)… 74.112.186.144
Connecting to nvidia.app.box.com (nvidia.app.box.com)|74.112.186.144|:443… connected.
HTTP request sent, awaiting response… 302 Found
Location: https://public.boxcloud.com/d/1/b1!nvTmlE-8447a-KPdw9VnyGXDPJJsV45lTPKjUbS_GLRVd2GjfOiINF4ilL7AEDWeu-TZAd9A1uwqa0ZnhTwcxdREzdOUzt5xmFkMcrCan71iFbcKk8QoWpsp410qWmywFXtfiGcp05nNtcZsI8aCfBILEupPsPLXb5gcbQIL0nzIjM_khXYD0Wh62Garz_e2POfIe3fLD6YyW0Q41em5E6Eljs6c6nwwEV_zYYYeVJ7d9Y5a5TxCmkLt27O8UqUKnfCd2gMMhax4kLS_Fo41vOvUhNWRy1HJ-U5mmsiUiZLGzbP-sCUWnihyz7LJsXfbxzSpZUJ1MuTUnA0S7Iuj9LxbGc4TtK8X2Gs9HkMxqQA2iQx3OuADyGKefOQkc_9OwiW_FA8TkLEfGLLnW_keIWuhBNTG6l1oGAEvjMIXyO3BaBL1MohRqneIwO6xkn2jGRPNwf0dv5kaO4VXJbAVuOuAckb4QYR7fMGMx19Xnnslu_hzKP7NQ7zJchw3CqxO-QEOJajjhWCbVj4-_aCmSu-Re5HkuDC1TCupdtQZrVWeeK4H76ZapKhiFq8OMnD1W5s8M3vfF7nfpu9r_icysBS-C1au-JZ5NxCYFdFSTGBf_4HrFMh2rGevC_oYW0zUoM96g2-THPRTAsCMOCtvQdNS6f3oqb-cD2m1oHcApCeKIeX8uU5au4jQTf6Dtt3wtz7Fg4lYQDtvRebH5xD2GviXxCEqfr2xI4jGGYST9ZA92D8bmTmwpf3tWMlydvJa03hcgZ6SqMp9c5XFLOZZHB3q3oM9KOjf9SdMGfTh3oZZuc8_FNzj2w1xu0eePqNCMtQm-semy_eSUWYsweOD_pmnOsqtXt2lJKScRMQvgcmb5iOCAa2W676q0chmczJ0XVEKljIX_Uy6d2lXTQG0_B48q-Gj1_7iJSA98SPjMcx-yDlp65CfRyY9BxqCdZ1NTWZpC51VwZ0JNIyw33Yzr3xzskd8kJI0gmEFyua0wKg1wi5cYE4cWJByfXCOLnAFN2QUUJ0mpuIsq6_4PPbBAVbmaUkzxAv86uitp61f2yXxxc6_sOhPj3TpajUYH7be39XvbsPt3XTAMbznYGn45AWofMNBfamu2smt4Qg1Icrdr7ojfNfAwE9IWX4D6rCup3v25KwrqzG1LQfFryNlQv_hIhhJobLi5qVZzEO7LshHJjfXXRyiBgQ69_Tt1s5PhA2O-bce01_8_zw9YnB8z1pSwcFDyPM4Ckz6_KfZyVNUsU4Fgmry0fXCKL3A4HKv3WiZiW9fZP0e2RiIaDyR9MEmnDy9tFUhAympgY6EGzc_QR8dsTHvPYYVyaCwOuWWohdG5UFOmqGR23QLfqCVQqBp6DWIFw../download [following]
–2024-01-15 09:46:42-- https://public.boxcloud.com/d/1/b1!nvTmlE-8447a-KPdw9VnyGXDPJJsV45lTPKjUbS_GLRVd2GjfOiINF4ilL7AEDWeu-TZAd9A1uwqa0ZnhTwcxdREzdOUzt5xmFkMcrCan71iFbcKk8QoWpsp410qWmywFXtfiGcp05nNtcZsI8aCfBILEupPsPLXb5gcbQIL0nzIjM_khXYD0Wh62Garz_e2POfIe3fLD6YyW0Q41em5E6Eljs6c6nwwEV_zYYYeVJ7d9Y5a5TxCmkLt27O8UqUKnfCd2gMMhax4kLS_Fo41vOvUhNWRy1HJ-U5mmsiUiZLGzbP-sCUWnihyz7LJsXfbxzSpZUJ1MuTUnA0S7Iuj9LxbGc4TtK8X2Gs9HkMxqQA2iQx3OuADyGKefOQkc_9OwiW_FA8TkLEfGLLnW_keIWuhBNTG6l1oGAEvjMIXyO3BaBL1MohRqneIwO6xkn2jGRPNwf0dv5kaO4VXJbAVuOuAckb4QYR7fMGMx19Xnnslu_hzKP7NQ7zJchw3CqxO-QEOJajjhWCbVj4-_aCmSu-Re5HkuDC1TCupdtQZrVWeeK4H76ZapKhiFq8OMnD1W5s8M3vfF7nfpu9r_icysBS-C1au-JZ5NxCYFdFSTGBf_4HrFMh2rGevC_oYW0zUoM96g2-THPRTAsCMOCtvQdNS6f3oqb-cD2m1oHcApCeKIeX8uU5au4jQTf6Dtt3wtz7Fg4lYQDtvRebH5xD2GviXxCEqfr2xI4jGGYST9ZA92D8bmTmwpf3tWMlydvJa03hcgZ6SqMp9c5XFLOZZHB3q3oM9KOjf9SdMGfTh3oZZuc8_FNzj2w1xu0eePqNCMtQm-semy_eSUWYsweOD_pmnOsqtXt2lJKScRMQvgcmb5iOCAa2W676q0chmczJ0XVEKljIX_Uy6d2lXTQG0_B48q-Gj1_7iJSA98SPjMcx-yDlp65CfRyY9BxqCdZ1NTWZpC51VwZ0JNIyw33Yzr3xzskd8kJI0gmEFyua0wKg1wi5cYE4cWJByfXCOLnAFN2QUUJ0mpuIsq6_4PPbBAVbmaUkzxAv86uitp61f2yXxxc6_sOhPj3TpajUYH7be39XvbsPt3XTAMbznYGn45AWofMNBfamu2smt4Qg1Icrdr7ojfNfAwE9IWX4D6rCup3v25KwrqzG1LQfFryNlQv_hIhhJobLi5qVZzEO7LshHJjfXXRyiBgQ69_Tt1s5PhA2O-bce01_8_zw9YnB8z1pSwcFDyPM4Ckz6_KfZyVNUsU4Fgmry0fXCKL3A4HKv3WiZiW9fZP0e2RiIaDyR9MEmnDy9tFUhAympgY6EGzc_QR8dsTHvPYYVyaCwOuWWohdG5UFOmqGR23QLfqCVQqBp6DWIFw../download
Resolving public.boxcloud.com (public.boxcloud.com)… 74.112.186.128
Connecting to public.boxcloud.com (public.boxcloud.com)|74.112.186.128|:443… connected.
HTTP request sent, awaiting response… 200 OK
Length: 1264869 (1.2M) [video/mp4]
Saving to: ‘pedestrians.mp4’
pedestrians.mp4 100%[============================================================================================>] 1.21M --.-KB/s in 0.06s
2024-01-15 09:46:43 (19.4 MB/s) - ‘pedestrians.mp4’ saved [1264869/1264869]
sai@sai-desktop:~/jetson-inference/build/aarch64/bin$ detectnet.py --model=peoplenet pedestrians.mp4 pedestrians_peoplenet.mp4
[gstreamer] initialized gstreamer, version 1.20.3.0
[gstreamer] gstDecoder – creating decoder for pedestrians.mp4
Opening in BLOCKING MODE
NvMMLiteOpen : Block : BlockType = 261
NvMMLiteBlockCreate : Block : BlockType = 261
(python3:9433): GStreamer-CRITICAL **: 09:46:56.715: gst_debug_log_valist: assertion ‘category != NULL’ failed
(python3:9433): GStreamer-CRITICAL **: 09:46:56.715: gst_debug_log_valist: assertion ‘category != NULL’ failed
(python3:9433): GStreamer-CRITICAL **: 09:46:56.716: gst_debug_log_valist: assertion ‘category != NULL’ failed
(python3:9433): GStreamer-CRITICAL **: 09:46:56.716: gst_debug_log_valist: assertion ‘category != NULL’ failed
[gstreamer] gstDecoder – discovered video resolution: 960x540 (framerate 29.970030 Hz)
[gstreamer] gstDecoder – discovered video caps: video/x-h264, stream-format=(string)byte-stream, alignment=(string)au, level=(string)3.1, profile=(string)high, width=(int)960, height=(int)540, framerate=(fraction)30000/1001, pixel-aspect-ratio=(fraction)1/1, chroma-format=(string)4:2:0, bit-depth-luma=(uint)8, bit-depth-chroma=(uint)8, parsed=(boolean)true
[gstreamer] gstDecoder – pipeline string:
[gstreamer] filesrc location=pedestrians.mp4 ! qtdemux ! queue ! h264parse ! nvv4l2decoder name=decoder enable-max-performance=1 ! video/x-raw(memory:NVMM) ! nvvidconv name=vidconv ! video/x-raw ! appsink name=mysink
[video] created gstDecoder from file:///home/sai/jetson-inference/build/aarch64/bin/pedestrians.mp4
gstDecoder video options:
– URI: file:///home/sai/jetson-inference/build/aarch64/bin/pedestrians.mp4
- protocol: file
- location: pedestrians.mp4
- extension: mp4
– deviceType: file
– ioType: input
– codec: H264
– codecType: v4l2
– width: 960
– height: 540
– frameRate: 29.97
– numBuffers: 4
– zeroCopy: true
– flipMethod: none
– loop: 0
[gstreamer] gstEncoder – codec not specified, defaulting to H.264
[gstreamer] gstEncoder – detected board ‘NVIDIA Jetson Orin Nano Developer Kit’
[gstreamer] gstEncoder – hardware encoder not detected, reverting to CPU encoder
[gstreamer] gstEncoder – pipeline launch string:
[gstreamer] appsrc name=mysource is-live=true do-timestamp=true format=3 ! x264enc name=encoder bitrate=4000 speed-preset=ultrafast tune=zerolatency ! video/x-h264 ! h264parse ! qtmux ! filesink location=pedestrians_peoplenet.mp4
[video] created gstEncoder from file:///home/sai/jetson-inference/build/aarch64/bin/pedestrians_peoplenet.mp4
gstEncoder video options:
– URI: file:///home/sai/jetson-inference/build/aarch64/bin/pedestrians_peoplenet.mp4
- protocol: file
- location: pedestrians_peoplenet.mp4
- extension: mp4
– deviceType: file
– ioType: output
– codec: H264
– codecType: cpu
– frameRate: 30
– bitRate: 4000000
– numBuffers: 4
– zeroCopy: true
[OpenGL] glDisplay – X screen 0 resolution: 2560x1440
[OpenGL] glDisplay – X window resolution: 2560x1440
[OpenGL] glDisplay – display device initialized (2560x1440)
[video] created glDisplay from display://0
glDisplay video options:
– URI: display://0
- protocol: display
- location: 0
– deviceType: display
– ioType: output
– width: 2560
– height: 1440
– frameRate: 0
– numBuffers: 4
– zeroCopy: true
[TRT] running model command: tao-model-downloader.sh peoplenet_deployable_quantized_v2.6.1
ARCH: aarch64
reading L4T version from /etc/nv_tegra_release
L4T BSP Version: L4T R36.2.0
[TRT] downloading peoplenet_deployable_quantized_v2.6.1
resnet34_peoplenet_int8.etlt 100%[============================================================================================>] 85.02M 27.8MB/s in 3.4s
resnet34_peoplenet_int8.txt 100%[============================================================================================>] 9.20K --.-KB/s in 0s
labels.txt 100%[============================================================================================>] 17 --.-KB/s in 0s
colors.txt 100%[============================================================================================>] 27 --.-KB/s in 0s
[TRT] downloading tao-converter from https://api.ngc.nvidia.com/v2/resources/nvidia/tao/tao-converter/versions/v3.22.05_trt8.4_aarch64/files/tao-converter
tao-converter 100%[============================================================================================>] 128.62K --.-KB/s in 0.1s
detectNet – converting TAO model to TensorRT engine:
– input resnet34_peoplenet_int8.etlt
– output resnet34_peoplenet_int8.etlt.engine
– calibration resnet34_peoplenet_int8.txt
– encryption_key tlt_encode
– input_dims 3,544,960
– output_layers output_bbox/BiasAdd,output_cov/Sigmoid
– max_batch_size 1
– workspace_size 4294967296
– precision int8
./tao-converter: error while loading shared libraries: libcrypto.so.1.1: cannot open shared object file: No such file or directory
[TRT] failed to convert model ‘resnet34_peoplenet_int8.etlt’ to TensorRT…
[TRT] failed to download model after 2 retries
[TRT] if this error keeps occuring, see here for a mirror to download the models from:
[TRT] Releases · dusty-nv/jetson-inference · GitHub
[TRT] failed to download built-in detection model ‘peoplenet’
Traceback (most recent call last):
File “/usr/local/bin/detectnet.py”, line 53, in
net = detectNet(args.network, sys.argv, args.threshold)
Exception: jetson.inference – detectNet failed to load network
The same command runs fine with default ssd-mobilenetv2 model but when it comes to peoplenet network receiving this error. It was all good until i flashed my nano with latest jetpack through Jetson SDK from host