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README.md
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@@ -70,12 +70,12 @@ The best in MantisScore series is in bold and the best in baselines is underline
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## Usage
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### Installation
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```
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git clone https://github.com/TIGER-AI-Lab/MantisScore.git
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```
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### Inference
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```
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cd MantisScore/examples
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```
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import av
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import numpy as np
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from typing import List
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import torch
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from transformers import AutoProcessor
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from models.idefics2 import Idefics2ForSequenceClassification
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all the frames of video are as follows:
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"""
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video_path="video1.mp4"
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video_prompt="Near the Elephant Gate village, they approach the haunted house at night. Rajiv feels anxious, but Bhavesh encourages him. As they reach the house, a mysterious sound in the air adds to the suspense."
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processor = AutoProcessor.from_pretrained(
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model = Idefics2ForSequenceClassification.from_pretrained(
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model.to(device)
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## Usage
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### Installation
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```
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git clone https://github.com/TIGER-AI-Lab/MantisScore.git
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```
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### Inference
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```
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cd MantisScore/examples
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```
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import av
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import numpy as np
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from typing import List
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from PIL import Image
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import torch
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from transformers import AutoProcessor
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from models.idefics2 import Idefics2ForSequenceClassification
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all the frames of video are as follows:
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"""
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model_name="TIGER-Lab/MantisScore"
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video_path="video1.mp4"
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video_prompt="Near the Elephant Gate village, they approach the haunted house at night. Rajiv feels anxious, but Bhavesh encourages him. As they reach the house, a mysterious sound in the air adds to the suspense."
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processor = AutoProcessor.from_pretrained(model_name,torch_dtype=torch.bfloat16)
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model = Idefics2ForSequenceClassification.from_pretrained(model_name,torch_dtype=torch.bfloat16).eval()
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model.to(device)
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