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| ] | | ] |
| } | | } |
| </syntaxhighlight>
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| ==== Visualization with detection crop ====
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| * Get the graph used on this example from [https://shop.ridgerun.com/products/tinyyolov2-for-tensorflow this link]
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| * You will need a v4l2 compatible camera
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| * Pipeline
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| ===== Example with aspect-ratio property =====
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| <syntaxhighlight lang=bash>
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| CAMERA='/dev/video0'
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| MODEL_LOCATION='graph_tinyyolov2_tensorflow.pb'
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| INPUT_LAYER='input/Placeholder'
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| OUTPUT_LAYER='add_8'
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| LABELS='labels.txt'
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| gst-launch-1.0 \
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| v4l2src device=$CAMERA ! "video/x-raw, width=1280, height=720" ! videoconvert ! tee name=t \
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| t. ! videoscale ! queue ! net.sink_model \
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| t. ! queue ! net.sink_bypass \
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| tinyyolov2 name=net model-location=$MODEL_LOCATION backend=tensorflow backend::input-layer=$INPUT_LAYER backend::output-layer=$OUTPUT_LAYER \
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| net.src_bypass ! detectioncrop aspect-ratio=1/1 ! videoscale ! ximagesink sync=false
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| </syntaxhighlight>
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|
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| ===== Example with crop-index property =====
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| <syntaxhighlight lang=bash>
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| CAMERA='/dev/video0'
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| MODEL_LOCATION='graph_tinyyolov2_tensorflow.pb'
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| INPUT_LAYER='input/Placeholder'
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| OUTPUT_LAYER='add_8'
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| LABELS='labels.txt'
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| gst-launch-1.0 \
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| v4l2src device=$CAMERA ! "video/x-raw, width=1280, height=720" ! videoconvert ! tee name=t \
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| t. ! videoscale ! queue ! net.sink_model \
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| t. ! queue ! net.sink_bypass \
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| tinyyolov2 name=net model-location=$MODEL_LOCATION backend=tensorflow backend::input-layer=$INPUT_LAYER backend::output-layer=$OUTPUT_LAYER \
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| net.src_bypass ! detectioncrop crop-index=1 ! videoscale ! ximagesink sync=false
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| </syntaxhighlight>
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|
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| ===== Example with crop-class property =====
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| <syntaxhighlight lang=bash>
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| CAMERA='/dev/video0'
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| MODEL_LOCATION='graph_tinyyolov2_tensorflow.pb'
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| INPUT_LAYER='input/Placeholder'
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| OUTPUT_LAYER='add_8'
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| LABELS='labels.txt'
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| gst-launch-1.0 \
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| v4l2src device=$CAMERA ! "video/x-raw, width=1280, height=720" ! videoconvert ! tee name=t \
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| t. ! videoscale ! queue ! net.sink_model \
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| t. ! queue ! net.sink_bypass \
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| tinyyolov2 name=net model-location=$MODEL_LOCATION backend=tensorflow backend::input-layer=$INPUT_LAYER backend::output-layer=$OUTPUT_LAYER \
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| net.src_bypass ! detectioncrop crop-class=4 ! videoscale ! ximagesink sync=false
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| </syntaxhighlight> | | </syntaxhighlight> |