diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 9cc2f38a7ab14ca45a8b0afc47a9d6d1bdef9f6e..dee6d44d4c47aec8dec18603bd41738db512804b 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -28,7 +28,7 @@ image: python:3.9
stages:
- - build
+ - install
- test
- deploy
@@ -51,21 +51,16 @@ cache:
#### ####
#######################################################################################################################################
-install-virtualenv:
- stage: build
- script:
- - python3 -m venv venv/
- - source venv/bin/activate
- - pip install --upgrade pip && pip install pip-tools
- - pip install -r ./backend/requirements.txt
-
-
install-npm-packages:
image: node:14.6.0
- stage: build
+ stage: install
script:
- cd ./frontend
- npm ci
+ artifacts:
+ paths:
+ - frontend/node_modules/
+ expire_in: 30 mins
#######################################################################################################################################
#### ####
@@ -77,12 +72,11 @@ lint-back:
stage: test
allow_failure: true
before_script:
+ - python3 -m venv venv/
- source venv/bin/activate
- - pip install pycodestyle
script:
+ - pip install pycodestyle
- pycodestyle --config=./backend/setup.cnf ./backend
- dependencies:
- - install-virtualenv
lint-front:
diff --git a/backend/.env.template b/backend/.env.template
index 8b2bf74be297c91d26ba76eaa54e1b1c534bfd03..56399b0772f6dc796624a789ce13d1b9f8d58e76 100644
--- a/backend/.env.template
+++ b/backend/.env.template
@@ -6,28 +6,13 @@ MYSQL_ROOT_PASSWORD=
DB_HOST=localhost
DB_PORT=3306
+MODEL_HOST=localhost
+MODEL_PORT=8501
+MODEL_NAME=model
+
CLIENT_ID=
CLIENT_SECRET=
API_ROOT=http://localhost:3001/api
WEB_ROOT=http://localhost:3000
AUTH_ROOT=https://auth.viarezo.fr
-
-CAM_NUMBER=1
-
-CAM_0_PLACE=local
-CAM_0_IP=
-CAM_0_USER=
-CAM_0_PASSWORD=
-CAM_0_STREAM=stream1
-CAM_0_A_FACTOR=30
-CAM_0_B_FACTOR=120
-CAM_0_FRAMEGAP=150
-CAM_0_POINTS_NB=7
-CAM_0_POINT_0=70, 370
-CAM_0_POINT_1=420, 720
-CAM_0_POINT_2=1280, 720
-CAM_0_POINT_3=1280, 250
-CAM_0_POINT_4=930, 215
-CAM_0_POINT_5=450, 550
-CAM_0_POINT_6=130, 350
\ No newline at end of file
diff --git a/backend/Dockerfile b/backend/Dockerfile-app
similarity index 100%
rename from backend/Dockerfile
rename to backend/Dockerfile-app
diff --git a/backend/Dockerfile-model b/backend/Dockerfile-model
new file mode 100644
index 0000000000000000000000000000000000000000..c7fd5a8cd4b8b33b19644b1546326ebde5150ec8
--- /dev/null
+++ b/backend/Dockerfile-model
@@ -0,0 +1,5 @@
+FROM tensorflow/serving:latest as runtime
+
+EXPOSE 8501
+
+COPY ./model ./models/model/1/
\ No newline at end of file
diff --git a/backend/docker-compose.yml b/backend/docker-compose.yml
index 72494bd9d8628ccbe572d903be41568ff37a7c80..1586f7782289457a8512593613ec9714aeadde19 100644
--- a/backend/docker-compose.yml
+++ b/backend/docker-compose.yml
@@ -13,12 +13,14 @@ services:
timeout: 1s
retries: 3
ports:
- - "3306:3306"
+ - 3306:3306
volumes:
- mysql-db:/var/lib/mysql
app:
- build: .
+ build:
+ context: .
+ dockerfile: Dockerfile-app
container_name: "app"
depends_on:
db:
@@ -29,8 +31,21 @@ services:
env_file: .env
environment:
DB_HOST: db
+ MODEL_HOST: model
links:
+ - model
- db
+ model:
+ build:
+ context: .
+ dockerfile: Dockerfile-model
+ container_name: "model"
+ restart: always
+ ports:
+ - 8501:8501
+ environment:
+ MODEL_NAME: "model"
+
volumes:
mysql-db:
\ No newline at end of file
diff --git a/backend/assets/keras_metadata.pb b/backend/model/keras_metadata.pb
similarity index 100%
rename from backend/assets/keras_metadata.pb
rename to backend/model/keras_metadata.pb
diff --git a/backend/assets/saved_model.pb b/backend/model/saved_model.pb
similarity index 100%
rename from backend/assets/saved_model.pb
rename to backend/model/saved_model.pb
diff --git a/backend/assets/variables/variables.data-00000-of-00001 b/backend/model/variables/variables.data-00000-of-00001
similarity index 100%
rename from backend/assets/variables/variables.data-00000-of-00001
rename to backend/model/variables/variables.data-00000-of-00001
diff --git a/backend/assets/variables/variables.index b/backend/model/variables/variables.index
similarity index 100%
rename from backend/assets/variables/variables.index
rename to backend/model/variables/variables.index
diff --git a/backend/requirements.txt b/backend/requirements.txt
index 035fe7337313c207f6398081f48c0735aa730ecb..8b39d9a9c42f8341d06d24d63702902c92d87029 100644
--- a/backend/requirements.txt
+++ b/backend/requirements.txt
@@ -1,20 +1,10 @@
-anyio==3.6.1
-asgiref==3.5.2
-click==8.1.3
fastapi==0.78.0
-h11==0.13.0
-idna==2.8
-keras==2.9.0
numpy==1.23.0
opencv-python==4.6.0.66
pydantic==1.9.1
-sniffio==1.2.0
-starlette==0.19.1
-typing-extensions==4.2.0
uvicorn==0.17.6
SQLAlchemy==1.4.19
python-dotenv==0.18.0
PyMySQL==1.0.2
pytz==2022.1
requests==2.25.1
-tensorflow==2.9.1
diff --git a/backend/video_capture.py b/backend/video_capture.py
index 9e9e1cca1e72e91826c536070f36082f6aabd567..66eafc8c784c757f3df2b2aaf1fc90101d763376 100644
--- a/backend/video_capture.py
+++ b/backend/video_capture.py
@@ -1,19 +1,38 @@
import cv2
from datetime import datetime, timedelta
-import numpy as np
-import keras
from utils.preprocessing import fix_singular_shape, norm_by_imagenet
+from dotenv import load_dotenv
+import numpy as np
+import requests
import json
import time
+import os
from cameras import restaurants
from db import models
from db.database import SessionLocal
from routers.websocket import manager
+load_dotenv()
+host = os.getenv('MODEL_HOST')
+port = os.getenv('MODEL_PORT')
+model = os.getenv('MODEL_NAME')
+
+
+def make_prediction(instances):
+ url = f"http://{host}:{port}/v1/models/{model}:predict"
+ data = json.dumps({"signature_name": "serving_default", "instances": instances.tolist()})
+ headers = {"content-type": "application/json"}
+ json_response = requests.post(url, data=data, headers=headers)
+ try:
+ predictions = json.loads(json_response.text)['predictions']
+ except BaseException:
+ print("prediction failed")
+ return predictions
+
async def handle_cameras():
- model = keras.models.load_model('assets', compile=False)
+
db = SessionLocal()
for restaurant in restaurants:
for camera in restaurant["cameras"]:
@@ -58,7 +77,7 @@ async def handle_cameras():
[treated_img]))),
axis=0)
# getting the density map from the model and the number of people
- pred_map = np.squeeze(model.predict(input_image, verbose=0))
+ pred_map = np.squeeze(make_prediction(input_image))
count_prediction += np.sum(pred_map)
for checkout in camera["checkouts"]:
# we check whether or not the density in the checkout area is high enough to determine if it is open or not