edit

Pipfile

@@ -17,6 +17,7 @@ tf-keras = "*"
 numpy = "*"
 pillow = "*"
 jinja2 = "*"
+coverage = "*"
 
 
 [dev-packages]

machine-learning-client/client.py

@@ -2,10 +2,10 @@
 Machine learning client for detecting emotions in images.
 This client connects to a MongoDB Atlas database, retrieves images.
 It then processes the images to detect emotions for target faces, and updates db with the results.
-OS: to set environment variable for ffmpeg
-Time: to sleep for a second
-Pymongo: to connect to MongoDB
-FER: to detect emotions in images
+Time: sleep for a second
+Pymongo: connect to MongoDB
+Deepface: to detect emotions in images
+Numpy: numerical operations
 ...
 """
 import base64

machine-learning-client/test_client.py

@@ -1,7 +1,7 @@
 from unittest.mock import patch, MagicMock
 import pytest, os
-from client import get_emotion, connect_db, FER
-#from PIL import Image
+from client import connect_db, get_emotion
+from PIL import Image
 
 os.environ["IMAGEIO_FFMPEG_EXE"] = "/usr/bin/ffmpeg"
 

web-app/main.py

@@ -1,13 +1,11 @@
 """
 Pymongo: Connecting to MongoDB via Python
 Flask: Python web framework
-Werkzeug: WSGI utility library for Python
 Base64: Encode and decode images
 """
 import base64
 from flask import Flask, render_template, request, jsonify
 from pymongo import MongoClient
-#from werkzeug.utils import secure_filename
 
 
 app = Flask(__name__)

web-app/test_main.py

@@ -3,7 +3,7 @@
 io: work with file-like objects
 """
 from io import BytesIO
-from app import app as flask_app
+from main import app as flask_app
 from flask import url_for
 import pytest