Follow Along! ============== .. raw:: html

Follow along: Dashcam Detection Example

The program launching process along with parameter settings are all simplified and set up on the Jupyter Notebook Environment.
(The Jetson Board used for these examples are => Jetson Nano)
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- 02_10-1. tao_facedetect.ipynb - | Running the cell code | `Ctrl + Enter` .. thumbnail:: /_images/ai_tao/face.png - Initialize your output stream, and your path, and import in the Image library .. code-block:: python from IPython.display import Image %env DISPLAY=:0 %env PROGRAM_PATH=/home/zeta/jetson-inference/build/aarch64/bin %env INPUT_PATH=/home/zeta/jetson-inference/build/aarch64/bin/images %env OUTPUT_PATH=/home/zeta/jetson-inference/build/aarch64/bin/images/test input_path='/home/zeta/jetson-inference/build/aarch64/bin/images' output_path='/home/zeta/jetson-inference/build/aarch64/bin/images/test' - Check all the available human pictures within the system .. code-block:: python !ls $INPUT_PATH/human_* .. thumbnail:: /_images/ai_tao/face_list.png | - Pick one of the image with human(s) and initialize the image/ output name. .. code-block:: python image_name = 'ChangeMe' output_name = 'face_result.jpg' %env IMAGE_NAME = $image_name %env OUTPUT_NAME = $output_name Image(filename=input_path+'/'+image_name) - Guess the pose! .. code-block:: python %%capture !python3 $PROGRAM_PATH/detectnet.py --network=facedetect $INPUT_PATH/$IMAGE_NAME $OUTPUT_PATH/$OUTPUT_NAME | - Show the resulting image .. code-block:: python Image(filename=output_path+'/face_result.jpg') .. thumbnail:: /_images/ai_tao/face_result.png