app_test.py

import pytest
import re
import numpy as np
import json
from flask import Flask, render_template, request
from werkzeug.datastructures import FileStorage
from PIL import Image
from app import prepare_image, predict

@pytest.fixture
def app():
    app = Flask(__name__)
    @app.route("/")
    def home():
        return render_template("view.html")
    return app

def test_home_endpoint(app):
    with app.test_client() as client:
        response = client.get("/")

        assert response.status_code == 200
        assert response.mimetype == "text/html"
        content = response.data.decode("utf-8")
        # Check that the correct template is being used        
        assert content is not None


def test_home_content(app):
    with app.test_client() as client:
        response = client.get("/")
        # Extract the HTML content
        content = response.data.decode("utf-8")
        # Verify that the form contains the expected elements
        assert "<input type=" in content

def test_prepare_image_with_valid_image_path():
    # Set up
    image_path = "images/test/image.jpg"

    # Call the function
    img_array = prepare_image(image_path)

    # Check the shape of the image array
    expected_shape = (1, 224, 224, 3)
    assert img_array.shape == expected_shape

    # Check the type of the image array
    expected_type = np.float32
    
    assert img_array.dtype == expected_type
    
    # Check the values of the image array
    assert -2.0 <= img_array.min() <= 2.0
    # assert img_array.max() == 1.0

def test_prepare_image_with_invalid_image_path():
    # Set up
    invalid_image_path = "images/invalid_image_path.jpg"

    # Call the function
    with pytest.raises(FileNotFoundError):
        img_array = prepare_image(invalid_image_path)



def test_predict_endpoint(app):

    # You may need to adjust the following based on your actual file path and image file
    image_file_path = "images/test/image.jpg"
    # Send a POST request to the /predict endpoint
    with open(image_file_path, "rb") as image_file:
        response = app.test_client().post("/predict", data={"image": (image_file, "image.jpg")})
        # Check if the response status code is 200 (OK)
        #assert response.status_code == 200
        assert response.headers["Content-Type"] == "text/html; charset=utf-8"
        print(response)
        # assert b"Processing image..." in response
        # assert b"Calling to model..." in response
        # assert b"result.html" in response
        # assert b"label" in response
        # assert b"probability" in response