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| # coding=utf-8 | |
| # judge voice-over | |
| from third_party.VideoLLaMA2.videollama2 import model_init, mm_infer | |
| import logging | |
| class Step2: | |
| def __init__(self, model_path, step2_mode, modal_type="av"): | |
| self.log = logging.getLogger(self.__class__.__name__) | |
| self.log.setLevel(logging.INFO) | |
| self.model, self.processor, self.tokenizer = model_init(model_path) | |
| self.modal_type=modal_type | |
| if modal_type == "a": | |
| self.model.model.vision_tower = None | |
| elif modal_type == "v": | |
| self.model.model.audio_tower = None | |
| elif modal_type == "av": | |
| pass | |
| else: | |
| raise NotImplementedError | |
| self.modal = 'audio' if modal_type == "a" else "video" | |
| self.question = f"Given a video and its corresponding audio, determine whether the audio contains voice-over? Options: A. Yes, B. No. Choose A or B." | |
| self.preprocess = self.processor[self.modal] | |
| self.step2_mode = step2_mode | |
| def run(self, video_audio_path): | |
| # self.log.info("Step2: Given a video and its generated audio, determine whether the audio contains voice-over.") | |
| audio_video_tensor = self.preprocess(video_audio_path, va=True) | |
| output = mm_infer( | |
| audio_video_tensor, | |
| self.question, | |
| model=self.model, | |
| tokenizer=self.tokenizer, | |
| modal=self.modal, | |
| do_sample=False, | |
| ) | |
| # print("oooooooooooooooooooooo: ", output) | |
| if self.step2_mode == "cot": | |
| output = output.split("<CONCLUSION>")[-1][1] | |
| print("1111111111111111111111111: ", output) | |
| output = (output == "A") | |
| if output: | |
| self.log.info(f"The video generated by Step1 ({video_audio_path}) contains voice-over.") | |
| else: | |
| self.log.info(f"The video generated by Step1 ({video_audio_path}) does not contain voice-over.") | |
| self.log.info("Finish Step2 successfully.\n") | |
| return output | |