DongfuJiang commited on
Commit
cb5c689
1 Parent(s): 03b5d97
Files changed (1) hide show
  1. app_regression.py +14 -16
app_regression.py CHANGED
@@ -37,26 +37,24 @@ for item in hd_examples:
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  examples = hd_examples + examples
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  VIDEO_EVAL_PROMPT = """
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- Suppose you are an expert in judging and evaluating the quality of AI-generated videos,
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- please watch the following frames of a given video and see the text prompt for generating the video,
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- then give scores from 7 different dimensions:
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  (1) visual quality: the quality of the video in terms of clearness, resolution, brightness, and color
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- (2) object consistency, the consistency of objects or humans in video
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  (3) dynamic degree, the degree of dynamic changes
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- (4) motion smoothness, the smoothness of motion or movements
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- (5) text-to-video alignment, the alignment between the text prompt and the video content
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- (6) factual consistency, the consistency of the video content with the common-sense and factual knowledge
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- for each dimension, output a float number from 1.0 to 4.0,
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- the higher the number is, the better the video performs in that sub-score,
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- the lowest 1.0 means Bad, the highest 4.0 means Perfect/Real (the video is like a real video)
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  Here is an output example:
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- visual quality: 3.2
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- object consistency: 2.7
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- dynamic degree: 4.0
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- motion smoothness: 1.6
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- text-to-video alignment: 2.3
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- factual consistency: 1.8
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  For this video, the text prompt is "{text_prompt}",
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  all the frames of video are as follows:
 
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  examples = hd_examples + examples
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  VIDEO_EVAL_PROMPT = """
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+ Suppose you are an expert in judging and evaluating the quality of AI-generated videos,
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+ please watch the following frames of a given video and see the text prompt for generating the video,
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+ then give scores from 5 different dimensions:
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  (1) visual quality: the quality of the video in terms of clearness, resolution, brightness, and color
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+ (2) temporal consistency, the consistency of objects or humans in video
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  (3) dynamic degree, the degree of dynamic changes
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+ (4) text-to-video alignment, the alignment between the text prompt and the video content
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+ (5) factual consistency, the consistency of the video content with the common-sense and factual knowledge
 
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+ For each dimension, output a number from [1,2,3,4],
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+ in which ‘1’ means ‘Bad’, ‘2’ means ‘Average’, ‘3’ means ‘Good’,
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+ '4' means ‘Real’ or Perfect (the video is like a real video)
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  Here is an output example:
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+ visual quality: 4
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+ temporal consistency: 4
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+ dynamic degree: 3
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+ text-to-video alignment: 1
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+ factual consistency: 2
 
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  For this video, the text prompt is "{text_prompt}",
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  all the frames of video are as follows: