example.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import cv2

from fer import FER

detector = FER(mtcnn=True) # or with mtcnn=False for Haar Cascade Classifier

image = cv2.imread("justin.jpg")
result = detector.detect_emotions(image)

# Result is an array with all the bounding boxes detected. We know that for 'justin.jpg' there is only one.
bounding_box = result[0]["box"]
emotions = result[0]["emotions"]

cv2.rectangle(
    image,
    (bounding_box[0], bounding_box[1]),
    (bounding_box[0] + bounding_box[2], bounding_box[1] + bounding_box[3]),
    (0, 155, 255),
    2,
)

for idx, (emotion, score) in enumerate(emotions.items()):
    color = (211, 211, 211) if score < 0.01 else (0, 255, 0)
    emotion_score = "{}: {}".format(
        emotion, "{:.2f}".format(score) if score > 0.01 else ""
    )
    cv2.putText(
        image,
        emotion_score,
        (bounding_box[0], bounding_box[1] + bounding_box[3] + 30 + idx * 15),
        cv2.FONT_HERSHEY_SIMPLEX,
        0.5,
        color,
        1,
        cv2.LINE_AA,
    )
cv2.imwrite("justin_drawn.jpg", image)

print(result)