Exception has occurred: TypeError argument of type 'NoneType' is not iterable - When importing whisper

Question

I am trying to generate subtitles in Python so I used the code of a creator and pasted it in. I installed all the requirements but I keep getting the error:

Exception has occurred:
TypeError argument of type 'NoneType' is not iterable
   File "D:\Python\Subtitle Generator\main.py", line 1, in <module>
     import whisper
TypeError: argument of type 'NoneType' is not iterable

It only happens on this line when importing whisper. I tried to remove it and didn't get this error only errors of whisper being missing.

import whisper
import os
import cv2
from moviepy.editor import ImageSequenceClip, AudioFileClip, VideoFileClip
from tqdm import tqdm

class VideoTranscriber:
    def __init__(self, model_path, video_path):
        self.model = whisper.load_model(model_path)
        self.video_path = video_path
        self.audio_path = ''
        self.text_array = []
        self.fps = 0
        self.char_width = 0

    def transcribe_video(self):
        print('Transcribing video')
        result = self.model.transcribe(self.audio_path)
        text = result["segments"][0]["text"]
        textsize = cv2.getTextSize(text, cv2.FONT_HERSHEY_SIMPLEX, 0.8, 2)[0]
        cap = cv2.VideoCapture(self.video_path)
        width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
        height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
        asp = 16/9
        ret, frame = cap.read()
        width = frame[:, int(int(width - 1 / asp * height) / 2):width - int((width - 1 / asp * height) / 2)].shape[1]
        width = width - (width * 0.1)
        self.fps = cap.get(cv2.CAP_PROP_FPS)
        self.char_width = int(textsize[0] / len(text))
        
        for j in tqdm(result["segments"]):
            lines = []
            text = j["text"]
            end = j["end"]
            start = j["start"]
            total_frames = int((end - start) * self.fps)
            start = start * self.fps
            total_chars = len(text)
            words = text.split(" ")
            i = 0
            
            while i < len(words):
                words[i] = words[i].strip()
                if words[i] == "":
                    i += 1
                    continue
                length_in_pixels = len(words[i]) * self.char_width
                remaining_pixels = width - length_in_pixels
                line = words[i] 
                
                while remaining_pixels > 0:
                    i += 1 
                    if i >= len(words):
                        break
                    length_in_pixels = len(words[i]) * self.char_width
                    remaining_pixels -= length_in_pixels
                    if remaining_pixels < 0:
                        continue
                    else:
                        line += " " + words[i]
                
                line_array = [line, int(start) + 15, int(len(line) / total_chars * total_frames) + int(start) + 15]
                start = int(len(line) / total_chars * total_frames) + int(start)
                lines.append(line_array)
                self.text_array.append(line_array)
        
        cap.release()
        print('Transcription complete')
    
    def extract_audio(self, output_audio_path='test_videos/audio.mp3'):
        print('Extracting audio')
        video = VideoFileClip(self.video_path)
        audio = video.audio 
        audio.write_audiofile(output_audio_path)
        self.audio_path = output_audio_path
        print('Audio extracted')
    
    def extract_frames(self, output_folder):
        print('Extracting frames')
        cap = cv2.VideoCapture(self.video_path)
        width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
        height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
        asp = width / height
        N_frames = 0
        
        while True:
            ret, frame = cap.read()
            if not ret:
                break
            
            frame = frame[:, int(int(width - 1 / asp * height) / 2):width - int((width - 1 / asp * height) / 2)]
            
            for i in self.text_array:
                if N_frames >= i[1] and N_frames <= i[2]:
                    text = i[0]
                    text_size, _ = cv2.getTextSize(text, cv2.FONT_HERSHEY_SIMPLEX, 0.8, 2)
                    text_x = int((frame.shape[1] - text_size[0]) / 2)
                    text_y = int(height/2)
                    cv2.putText(frame, text, (text_x, text_y), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 0, 255), 2)
                    break
            
            cv2.imwrite(os.path.join(output_folder, str(N_frames) + ".jpg"), frame)
            N_frames += 1
        
        cap.release()
        print('Frames extracted')

    def create_video(self, output_video_path):
        print('Creating video')
        image_folder = os.path.join(os.path.dirname(self.video_path), "frames")
        if not os.path.exists(image_folder):
            os.makedirs(image_folder)
        
        self.extract_frames(image_folder)
        
        print("Video saved at:", output_video_path)
        images = [img for img in os.listdir(image_folder) if img.endswith(".jpg")]
        images.sort(key=lambda x: int(x.split(".")[0]))
        
        frame = cv2.imread(os.path.join(image_folder, images[0]))
        height, width, layers = frame.shape
        
        clip = ImageSequenceClip([os.path.join(image_folder, image) for image in images], fps=self.fps)
        audio = AudioFileClip(self.audio_path)
        clip = clip.set_audio(audio)
        clip.write_videofile(output_video_path)

# Example usage
model_path = "base"
video_path = "Videos/video.mov"
output_video_path = "Videos/result.mov"

transcriber = VideoTranscriber(model_path, video_path)
transcriber.extract_audio()
transcriber.transcribe_video()
transcriber.create_video(output_video_path)