FlaskObjectDetection - TensorFlow

Installation

Run the requirements.txt if you are in a new enviroment. For Ubuntu with Anaconda:

$ pip install -r requirements

Install tensorflow 1.11 for raspberry pi3

Install tensorflow for raspberry with:

$ wget -O tensorflow-1.11.0-cp35-cp35m-linux_armv7l.whl https://github.com/PINTO0309/Tensorflow-bin/raw/master/tensorflow-1.11.#0-cp35-cp35m-linux_armv7l_jemalloc.whl
$ pip3 install tensorflow-1.11.0-cp35-cp35m-linux_armv7l.whl

for raspberry pi3:

$ pip3 install -r requirements

USE

Serser side.

Run the script:

$ python app.py

for start the server, the server will be available in http://localhost:5000/predict waiting for the POST requests.

Client side.

Use the client.py

# import the necessary packages
import requests

# initialize the Keras REST API endpoint URL along with the input
# image path
KERAS_REST_API_URL = "http://localhost:5000/predict"
IMAGE_PATH = "car.jpg"

# load the input image and construct the payload for the request
image = open(IMAGE_PATH, "rb").read()
payload = {"image": image}

# submit the request
r = requests.post(KERAS_REST_API_URL, files=payload).json()

# ensure the request was successful
if r["success"]:
    # loop over the predictions and display them
    print(r)

# otherwise, the request failed
else:
    print("Request failed")

...or from the terminal with curl:

$ curl -X POST -F image=@car.jpg 'http://localhost:5000/predict'