[EXAMPLE] tensor_crop example

[Harshj20]

Example for Tensor_crop plugin which crops the input video from v4l2src and renders the cropped video using autovideosink. Use a video source with an aspect ratio of 1:1 to avoid distortion.

It uses the following pipeline:

gst-launch-1.0 v4l2src ! decodebin ! videoconvert ! videoscale ! video/x-raw, width=640, height=480, framerate=30/1, format=RGB ! videocrop left=170 right=170 top=90 bottom=90 ! tee name=t t. ! queue leaky=2 max-size-buffers=2 ! tensor_converter ! crop.raw t. ! queue leaky=2 max-size-buffers=10 ! tensor_converter ! tensor_transform mode=arithmetic option=typecast:float32,add:-127.5,div:127.5 ! tensor_filter framework=tensorflow2-lite model=tflite_model/ssd_mobilenet_v2_coco.tflite ! tensor_decoder mode=tensor_region option1=1 option2=tflite_model/coco_labels_list.txt option3=tflite_model/box_priors.txt option4=300:300 ! crop.info tensor_crop name=crop ! other/tensors,format=flexible ! tensor_converter ! tensor_decoder mode=direct_video ! videoconvert ! videoscale ! video/x-raw,format=RGB ! videoconvert ! autovideosink name=cropped t. ! queue ! autovideosink name=original

The second autovideosink element is to view the original video.

[taos-ci]

:memo: TAOS-CI Version: 1.5.20200925. Thank you for submitting PR #307. Please a submit 1commit/1PR (one commit per one PR) policy to get comments quickly from reviewers. Your PR must pass all verificiation processes of cibot before starting a review process from reviewers. If you are new member to join this project, please read manuals in documentation folder and wiki page. In order to monitor a progress status of your PR in more detail, visit http://ci.nnstreamer.ai/.

[gichan-jang]

This is a good example to understand tensor_crop. Thanks. How about the example below to show that we can crop multiple areas?

gst-launch-1.0 v4l2src ! videoconvert ! videoscale ! video/x-raw, width=640, height=480, framerate=30/1, format=RGB ! \
  videocrop left=170 right=170 top=90 bottom=90 ! tee name=t  t. ! queue leaky=2 max-size-buffers=2 ! tensor_converter ! crop.raw \
  t. ! queue leaky=2 max-size-buffers=10 ! tensor_converter ! tensor_transform mode=arithmetic option=typecast:float32,add:-127.5,div:127.5 ! \
    tensor_filter framework=tensorflow2-lite model=tflite_model/ssd_mobilenet_v2_coco.tflite ! \
    tensor_decoder mode=tensor_region option1=2 option2=tflite_model/coco_labels_list.txt option3=tflite_model/box_priors.txt option4=300:300 ! \
      crop.info tensor_crop name=crop ! other/tensors,format=flexible ! tensor_demux name=demux \
        demux.src_0 ! queue ! tensor_converter ! tensor_decoder mode=direct_video ! \
        videoconvert ! videoscale ! video/x-raw,format=RGB ,height=300,width=300 ! videoconvert ! xvimagesink \
        demux.src_1 ! queue ! tensor_converter ! tensor_decoder mode=direct_video ! \
        videoconvert ! videoscale ! video/x-raw,format=RGB ,height=300,width=300 ! videoconvert ! xvimagesink \
  t. ! queue ! videoconvert ! xvimagesink name=original

[Harshj20]

This is a good example to understand tensor_crop. Thanks. How about the example below to show that we can crop multiple areas?

gst-launch-1.0 v4l2src ! videoconvert ! videoscale ! video/x-raw, width=640, height=480, framerate=30/1, format=RGB ! \
  videocrop left=170 right=170 top=90 bottom=90 ! tee name=t  t. ! queue leaky=2 max-size-buffers=2 ! tensor_converter ! crop.raw \
  t. ! queue leaky=2 max-size-buffers=10 ! tensor_converter ! tensor_transform mode=arithmetic option=typecast:float32,add:-127.5,div:127.5 ! \
    tensor_filter framework=tensorflow2-lite model=tflite_model/ssd_mobilenet_v2_coco.tflite ! \
    tensor_decoder mode=tensor_region option1=2 option2=tflite_model/coco_labels_list.txt option3=tflite_model/box_priors.txt option4=300:300 ! \
      crop.info tensor_crop name=crop ! other/tensors,format=flexible ! tensor_demux name=demux \
        demux.src_0 ! queue ! tensor_converter ! tensor_decoder mode=direct_video ! \
        videoconvert ! videoscale ! video/x-raw,format=RGB ,height=300,width=300 ! videoconvert ! xvimagesink \
        demux.src_1 ! queue ! tensor_converter ! tensor_decoder mode=direct_video ! \
        videoconvert ! videoscale ! video/x-raw,format=RGB ,height=300,width=300 ! videoconvert ! xvimagesink \
  t. ! queue ! videoconvert ! xvimagesink name=original

I have been trying to test-run this pipeline. I will update the code as soon as I can generate the desired results.

[gichan-jang]

This is a good example to understand tensor_crop. Thanks. How about the example below to show that we can crop multiple areas?

gst-launch-1.0 v4l2src ! videoconvert ! videoscale ! video/x-raw, width=640, height=480, framerate=30/1, format=RGB ! \
  videocrop left=170 right=170 top=90 bottom=90 ! tee name=t  t. ! queue leaky=2 max-size-buffers=2 ! tensor_converter ! crop.raw \
  t. ! queue leaky=2 max-size-buffers=10 ! tensor_converter ! tensor_transform mode=arithmetic option=typecast:float32,add:-127.5,div:127.5 ! \
    tensor_filter framework=tensorflow2-lite model=tflite_model/ssd_mobilenet_v2_coco.tflite ! \
    tensor_decoder mode=tensor_region option1=2 option2=tflite_model/coco_labels_list.txt option3=tflite_model/box_priors.txt option4=300:300 ! \
      crop.info tensor_crop name=crop ! other/tensors,format=flexible ! tensor_demux name=demux \
        demux.src_0 ! queue ! tensor_converter ! tensor_decoder mode=direct_video ! \
        videoconvert ! videoscale ! video/x-raw,format=RGB ,height=300,width=300 ! videoconvert ! xvimagesink \
        demux.src_1 ! queue ! tensor_converter ! tensor_decoder mode=direct_video ! \
        videoconvert ! videoscale ! video/x-raw,format=RGB ,height=300,width=300 ! videoconvert ! xvimagesink \
  t. ! queue ! videoconvert ! xvimagesink name=original

I have been trying to test-run this pipeline. I will update the code as soon as I can generate the desired results.

Let's update this in next PR. LGTM.