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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
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