TensorFlow Lite

Demo Video

Installation

Run the install_tensorflow function in configure. BerryNet dev team is making this to be easier and clearer.

Test TFLite Engine Manually

Use TFLite detector service and mobilenet-ssd-coco-tflite model package as example.

1. Start detector service

   $ python3 tflite_service.py \
       --service detector \
       --model /usr/share/dlmodels/mobilenet-ssd-coco-tflite-2.0.0/model.tflite \
       --label /usr/share/dlmodels/mobilenet-ssd-coco-tflite-2.0.0/labels.txt \
       --service_name tfdetector \
       --num_threads 4 \
       --draw \
       --debug
   /usr/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.7
     return f(*args, **kwds)
   [D 190711 11:50:17 tflite_service:174] model filepath: /usr/share/dlmodels/mobilenet-ssd-coco-tflite-2.0.0/model.tflite
   [D 190711 11:50:17 tflite_service:175] label filepath: /usr/share/dlmodels/mobilenet-ssd-coco-tflite-2.0.0/labels.txt
   INFO: Initialized TensorFlow Lite runtime.
   [D 190711 11:50:17 __init__:11] Connected with result code 0
   [D 190711 11:50:17 __init__:13] Subscribe topic berrynet/data/rgbimage
   

2. Send image to service by camera client

   $ bn_camera --mode file --filepath <image-filepath>
   

   Example image: wget https://github.com/pjreddie/darknet/raw/master/data/dog.jpg

3. You should see the inference results on detector's terminal

   [D 190705 15:39:20 __init__:20] Receive message from topic berrynet/data/rgbimage
   [D 190705 15:39:20 tflite_service:46] payload size: 161232
   [D 190705 15:39:20 tflite_service:47] payload type: <class 'bytes'>
   [D 190705 15:39:20 tflite_service:50] destringify_jpg: 4.505 ms
   [D 190705 15:39:20 tflite_service:54] jpg2bgr: 10.444 ms
   [D 190705 15:39:21 tflite_service:60] Result: {'annotations': [{'label': 'person', 'confidence': 0.9751802682876587, 'left': 187, 'top': 99, 'right': 273, 'bottom': 384}, {'label': 'sheep', 'confidence': 0.9385143518447876, 'left': 401, 'top': 135, 'right': 600, 'bottom': 339}, {'label': 'dog', 'confidence': 0.7179926037788391, 'left': 68, 'top': 263, 'right': 200, 'bottom': 349}]}
   [D 190705 15:39:21 tflite_service:61] Detection takes 527.504 ms
   [D 190705 15:39:21 tflite_service:66] draw = True
   [D 190705 15:39:21 tflite_service:77] result_hook, annotations: [{'label': 'person', 'confidence': 0.9751802682876587, 'left': 187, 'top': 99, 'right': 273, 'bottom': 384}, {'label': 'sheep', 'confidence': 0.9385143518447876, 'left': 401, 'top': 135, 'right': 600, 'bottom': 339}, {'label': 'dog', 'confidence': 0.7179926037788391, 'left': 68, 'top': 263, 'right': 200, 'bottom': 349}]
   [D 190705 15:39:21 __init__:50] Send message to topic berrynet/engine/tflitedetector/result
   

4. To visualize the received inference result

   $ bn_dashboard --no-decoration --no-full-screen --topic berrynet/engine/tflitedetector/result --debug