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Runtime error
| import os | |
| import cv2 | |
| import numpy as np | |
| import ffmpeg | |
| from math import ceil | |
| from segmindapi import SD2_1, Kadinsky | |
| import gradio as gr | |
| from .TextPreprocessor import TextPreprocessor | |
| from .AVCombiner import AVCombiner | |
| class Videobook: | |
| def __init__(self): | |
| self.preprocessor = TextPreprocessor() | |
| self.combiner = AVCombiner() | |
| def get_sentences(self, story): | |
| return self.preprocessor(story) | |
| def generate_imgs(self, sentences, steps): | |
| imgs = [] | |
| for sentence in sentences: | |
| sentence['pos'] = self.style + ' of ' + str(sentence['pos']) + ', ' + self.tags | |
| imgs.append(self.pipe.generate(prompt = sentence['pos'], negative_prompt = str(sentence['neg']) + " ,nude, disfigured, blurry", num_inference_steps = steps)) | |
| return imgs | |
| def generate(self, story, api_key, style, tags, model, steps): | |
| self.style = style | |
| self.tags = tags | |
| if model == "Stable Diffusion v2.1": | |
| self.pipe = SD2_1(api_key) | |
| else: | |
| self.pipe = Kadinsky(api_key) | |
| processed_sentences, sentences = self.get_sentences(story) | |
| return AVCombiner()(self.generate_imgs(processed_sentences, steps), sentences, os.getcwd()) |