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def emotions_generator(self, video_path):
        video_capture = cv2.VideoCapture(video_path)
        fps = video_capture.get(cv2.CAP_PROP_FPS)
        frame_interval = math.ceil(fps / self.fps_desired)
        frame_counter = 0
        while video_capture.isOpened():
            ret, frame = video_capture.read()
            if not ret:
                break

            if frame_counter % frame_interval == 0:
                img_path = "./temp_frame.jpg"
                cv2.imwrite(img_path, frame, [cv2.IMWRITE_JPEG_QUALITY, 75])
                #cv2.imwrite(img_path, frame)

                detections = DeepFace.analyze(img_path=img_path, actions=['emotion'], enforce_detection=False, silent= True)
                emotions = detections[0]['emotion']

                emotions = {self.emotions_mapping.get(emotion, emotion): value for emotion, value in emotions.items()}

                second = frame_counter / fps
                yield second, emotions

                os.remove(img_path)

            frame_counter += 1

            logging.info(f"\n========= Frame processed: {frame_counter} ==========")
        video_capture.release()