marvinhoxha

FROM python:3.8

EXPOSE 8502

WORKDIR /app

ARG  CONFIG
ENV CONFIG ${CONFIG}

ARG ENV

marvinhoxha

FROM python:3.8


RUN apt-get update && DEBIAN_FRONTEND=noninteractive && apt-get install -y \
   curl \
   python3-setuptools && \
apt-get clean && apt-get autoremove -y && rm -rf /var/lib/apt/lists/*


RUN mkdir /models

marvinhoxha

version: "3.9"

services:
  tfserve:
    image: tensorflow/serving
    ports: 
      - 8501:8501
    environment:
      MODEL_NAME: dog_model
    volumes:

marvinhoxha

repositories:
  - name: datawire
    url: https://www.getambassador.io
  - name: seldon
    url: https://storage.googleapis.com/seldon-charts

releases:
  - name: ambassador
    namespace: ambassador
    createNamespace: true

marvinhoxha

FROM python:3.8


RUN apt-get update && DEBIAN_FRONTEND=noninteractive && \
    apt-get install -y curl python3-setuptools && \
    apt-get clean && apt-get autoremove -y && rm -rf /var/lib/apt/lists/*

RUN mkdir /models

WORKDIR /app

marvinhoxha

resnet_body = tf.keras.applications.ResNet50V2(
    weights="imagenet",
    include_top=False,
    input_shape=(int(IMG_SIZE), int(IMG_SIZE), 3),
)
resnet_body.trainable = False
inputs = tf.keras.layers.Input(shape=(int(IMG_SIZE), int(IMG_SIZE), 3))
x = resnet_body(inputs, training=False)
x = tf.keras.layers.Flatten()(x)
outputs = tf.keras.layers.Dense(133, activation="softmax")(x)

marvinhoxha

def send_client_request(seldon_client, image):
    client_prediction = seldon_client.predict(
        data=image,
        deployment_name="seldon-dogbreed",
        payload_type="ndarray",
    )
    return client_prediction


if env == "COMPOSE":

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def consumer():
    consumer = KafkaConsumer('dogtopic')
    for message in consumer:
        with open("foo.png","wb") as f:
            f.write(decodebytes(message.value))
        img = tf.keras.utils.load_img(
            "foo.png",
            target_size=(224,224)
        )
        input_arr = tf.keras.utils.img_to_array(img)

marvinhoxha

from kafka import KafkaProducer
import base64

def image_producer():
    producer = KafkaProducer(bootstrap_servers='localhost:9092')
    with open("./dogImages/test/002.Afghan_hound/Afghan_hound_00116.jpg", "rb") as imageFile:
        str1 = base64.b64encode(imageFile.read())
    
    producer.send('dogtopic', str1)

marvinhoxha

def send_photo_to_slack(result):
    image = open("foo.png", 'rb').read()
    client = WebClient("Slack_Bot_User_OAuth_Token") #input OAuth token
    client.files_upload(
        channels = "Slack_channel_id", #input channel id
        initial_comment = f"{result}",
        filename = "dog photo",
        content = image
    )