- Move tensorflow object detection api in this project. for this project, simply add nets, deployment and object_detection these three directory into this project.
- Download a model and modify the path to your model
def load_model():
# load the pre-trained Keras model (here we are using a model
# pre-trained on ImageNet and provided by Keras, but you can
# substitute in your own networks just as easily)
PATH_TO_CKPT = 'model/faster_rcnn_resnet101_coco_2018_01_28/frozen_inference_graph.pb'
# List of the strings that is used to add correct label for each box.
# PATH_TO_LABELS = os.path.join('data', 'mscoco_label_map.pbtxt')
- run the object_detection_rest.py
python object_detection_rest.py
- Use curl to post your image to your server and get the result.