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import os
from .utils import get_prompt_from_filename, init_submodules, save_json, load_json
import importlib
from itertools import chain
from pathlib import Path
class VBench(object):
def __init__(self, device, full_info_dir, output_path):
self.device = device # cuda or cpu
self.full_info_dir = full_info_dir # full json file that VBench originally provides
self.output_path = output_path # output directory to save VBench results
os.makedirs(self.output_path, exist_ok=True)
def build_full_dimension_list(self, ):
return ["subject_consistency", "background_consistency", "aesthetic_quality", "imaging_quality", "object_class", "multiple_objects", "color", "spatial_relationship", "scene", "temporal_style", 'overall_consistency', "human_action", "temporal_flickering", "motion_smoothness", "dynamic_degree", "appearance_style"]
def check_dimension_requires_extra_info(self, dimension_list):
dim_custom_not_supported = set(dimension_list) & set([
'object_class', 'multiple_objects', 'scene', 'appearance_style', 'color', 'spatial_relationship'
])
assert len(dim_custom_not_supported) == 0, f"dimensions : {dim_custom_not_supported} not supported for custom input"
def build_full_info_json(self, videos_path, name, dimension_list, prompt_list=[], special_str='', verbose=False, mode='vbench_standard', **kwargs):
cur_full_info_list=[] # to save the prompt and video path info for the current dimensions
if mode=='custom_input':
self.check_dimension_requires_extra_info(dimension_list)
if os.path.isfile(videos_path):
cur_full_info_list = [{"prompt_en": get_prompt_from_filename(videos_path), "dimension": dimension_list, "video_list": [videos_path]}]
if len(prompt_list) == 1:
cur_full_info_list[0]["prompt_en"] = prompt_list[0]
else:
video_names = os.listdir(videos_path)
cur_full_info_list = []
for filename in video_names:
postfix = Path(os.path.join(videos_path, filename)).suffix
if postfix.lower() not in ['.mp4', '.gif', '.jpg', '.png']:
continue
cur_full_info_list.append({
"prompt_en": get_prompt_from_filename(filename),
"dimension": dimension_list,
"video_list": [os.path.join(videos_path, filename)]
})
if len(prompt_list) > 0:
prompt_list = {os.path.join(videos_path, path): prompt_list[path] for path in prompt_list}
assert len(prompt_list) >= len(cur_full_info_list), """
Number of prompts should match with number of videos.\n
Got {len(prompt_list)=}, {len(cur_full_info_list)=}\n
To read the prompt from filename, delete --prompt_file and --prompt_list
"""
all_video_path = [os.path.abspath(file) for file in list(chain.from_iterable(vid["video_list"] for vid in cur_full_info_list))]
backslash = "\n"
assert len(set(all_video_path) - set([os.path.abspath(path_key) for path_key in prompt_list])) == 0, f"""
The prompts for the following videos are not found in the prompt file: \n
{backslash.join(set(all_video_path) - set([os.path.abspath(path_key) for path_key in prompt_list]))}
"""
video_map = {}
for prompt_key in prompt_list:
video_map[os.path.abspath(prompt_key)] = prompt_list[prompt_key]
for video_info in cur_full_info_list:
video_info["prompt_en"] = video_map[os.path.abspath(video_info["video_list"][0])]
elif mode=='vbench_category':
self.check_dimension_requires_extra_info(dimension_list)
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
category_supported = [ Path(category).stem for category in os.listdir(f'prompts/prompts_per_category') ]# TODO: probably need refactoring again
if 'category' not in kwargs:
category = category_supported
else:
category = kwargs['category']
assert category is not None, "Please specify the category to be evaluated with --category"
assert category in category_supported, f'''
The following category is not supported, {category}.
'''
video_names = os.listdir(videos_path)
postfix = Path(video_names[0]).suffix
with open(f'{CUR_DIR}/prompts_per_category/{category}.txt', 'r') as f:
video_prompts = [line.strip() for line in f.readlines()]
for prompt in video_prompts:
video_list = []
for filename in video_names:
if (not Path(filename).stem.startswith(prompt)):
continue
postfix = Path(os.path.join(videos_path, filename)).suffix
if postfix.lower() not in ['.mp4', '.gif', '.jpg', '.png']:
continue
video_list.append(os.path.join(videos_path, filename))
cur_full_info_list.append({
"prompt_en": prompt,
"dimension": dimension_list,
"video_list": video_list
})
else:
full_info_list = load_json(self.full_info_dir)
video_names = os.listdir(videos_path)
postfix = Path(video_names[0]).suffix
for prompt_dict in full_info_list:
# if the prompt belongs to any dimension we want to evaluate
if set(dimension_list) & set(prompt_dict["dimension"]):
prompt = prompt_dict['prompt_en']
prompt_dict['video_list'] = []
for i in range(5): # video index for the same prompt
intended_video_name = f'{prompt}{special_str}-{str(i)}{postfix}'
if intended_video_name in video_names: # if the video exists
intended_video_path = os.path.join(videos_path, intended_video_name)
prompt_dict['video_list'].append(intended_video_path)
if verbose:
print(f'Successfully found video: {intended_video_name}')
else:
print(f'WARNING!!! This required video is not found! Missing benchmark videos can lead to unfair evaluation result. The missing video is: {intended_video_name}')
cur_full_info_list.append(prompt_dict)
cur_full_info_path = os.path.join(self.output_path, name+'_full_info.json')
save_json(cur_full_info_list, cur_full_info_path)
print(f'Evaluation meta data saved to {cur_full_info_path}')
return cur_full_info_path
def evaluate(self, videos_path, name, prompt_list=[], dimension_list=None, local=False, read_frame=False, mode='vbench_standard', **kwargs):
results_dict = {}
if dimension_list is None:
dimension_list = self.build_full_dimension_list()
submodules_dict = init_submodules(dimension_list, local=local, read_frame=read_frame)
cur_full_info_path = self.build_full_info_json(videos_path, name, dimension_list, prompt_list, mode=mode, **kwargs)
for dimension in dimension_list:
try:
dimension_module = importlib.import_module(f'vbench.{dimension}')
evaluate_func = getattr(dimension_module, f'compute_{dimension}')
except Exception as e:
raise NotImplementedError(f'UnImplemented dimension {dimension}!, {e}')
submodules_list = submodules_dict[dimension]
print(f'cur_full_info_path: {cur_full_info_path}') # TODO: to delete
results = evaluate_func(cur_full_info_path, self.device, submodules_list, **kwargs)
results_dict[dimension] = results
output_name = os.path.join(self.output_path, name+'_eval_results.json')
save_json(results_dict, output_name)
print(f'Evaluation results saved to {output_name}')
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