OpenVINO GStreamer gvadetect is not applying model - gstreamer

Question

I am super new to OpenVINO and GStreamer. I am trying to apply a pipeline in GStreamer plugin using OpenVINO. I downloaded the model as well it's proc files. I am trying to apply the model and it's proc to a video. For some reason I am not getting any output in the video.
I don't know how to debug the GStreamer pipeline. I added one text overlay for debugging and found out every step is working but the final output is not having any results. I get the same input video as output (with text overlay). Could anyone help me out here?
# Model is downloaded from model downloader's downloader.py
# Model-proc is downloaded from
# https://github.com/openvinotoolkit/dlstreamer_gst/blob/master/samples/model_proc/intel/human_pose_estimation/human-pose-estimation-0001.json
VIDEO_FILE = 'HumanPoseEstimation/Sample_Video/face-demographics-walking.mp4'
ESTIMATION_MODEL = "HumanPoseEstimation/Models/intel/human-pose-estimation-0001/FP32/human-pose-estimation-0001.xml"
ESTIMATION_MODEL_PROC = "HumanPoseEstimation/Models/intel/human-pose-estimation-0001/human-post-estimation-0001-proc.json"
SINK_LOCATION = "HumanPoseEstimation/output.mp4"
# GStreamer pipeline
GST_PIPELINE = f'''
filesrc location={VIDEO_FILE}
! decodebin
! videoconvert
! queue
! gvaclassify model={ESTIMATION_MODEL} model-proc={ESTIMATION_MODEL_PROC} device=CPU
! queue
! textoverlay text="Human Pose Estimation"
! gvawatermark
! x264enc
! filesink location={SINK_LOCATION}
'''

Answer 1

You may be missing some part at the end of the pipeline for muxing into a mp4-compliant file container. You may try:
...
! x264enc
! h264parse
! qtmux
! filesink location={SINK_LOCATION}

Answer 2

You can use the Human Pose Estimation Sample to run with human-pose-estimation-0001 model.
Refer to human_pose_estimation.sh for the pipeline elements used in the Human Pose Estimation Sample.

Answer 3

Looks like you need to add "inference-region=full-frame" to your gvaclassify, like:
! gvaclassify model={ESTIMATION_MODEL} model-proc={ESTIMATION_MODEL_PROC} device=CPU inference-region=full-frame
The use of classification (gvaclassify) without a prior "detection" (resulting in at least one region-of-interest) is unusual...
That's why you would need to specify to use the full-frame for doing the classification (instead of typically only to classify a previously detected "object").