File size: 3,976 Bytes
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import shlex
import subprocess
import argparse
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
def register_subparsers(subparser):
parser = subparser.add_parser('evaluate', formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument(
"--ngpus",
type=int,
default=1,
help="Number of GPUs to run evaluation on"
)
parser.add_argument(
"--output_path",
type=str,
default='./evaluation_results/',
help="output path to save the evaluation results",
)
parser.add_argument(
"--full_json_dir",
type=str,
default=f'{CUR_DIR}/../VBench2_full_info.json',
help="path to save the json file that contains the prompt and dimension information",
)
parser.add_argument(
"--videos_path",
type=str,
required=True,
help="folder that contains the sampled videos",
)
parser.add_argument(
"--dimension",
type=str,
required=True,
help="list of evaluation dimensions, usage: --dimension <dim_1> <dim_2>",
)
parser.add_argument(
"--load_ckpt_from_local",
type=bool,
required=False,
help="whether load checkpoints from local default paths (assuming you have downloaded the checkpoints locally",
)
parser.add_argument(
"--read_frame",
type=bool,
required=False,
help="whether directly read frames, or directly read videos",
)
parser.add_argument(
"--mode",
choices=['vbench_standard'],
default='vbench_standard',
help="""This flags determine the mode of evaluations, choose one of the following:
1. "vbench_standard": evaluate on standard prompt suite of VBench
""",
)
parser.add_argument(
"--prompt",
type=str,
default=None,
help="""Specify the input prompt
If not specified, filenames will be used as input prompts
* Mutually exclusive to --prompt_file.
** This option must be used with --mode=custom_input flag
"""
)
parser.add_argument(
"--prompt_file",
type=str,
required=False,
help="""Specify the path of the file that contains prompt lists
If not specified, filenames will be used as input prompts
* Mutually exclusive to --prompt.
** This option must be used with --mode=custom_input flag
"""
)
## for dimension specific params ###
parser.add_argument(
"--imaging_quality_preprocessing_mode",
type=str,
required=False,
default='longer',
help="""This is for setting preprocessing in imaging_quality
1. 'shorter': if the shorter side is more than 512, the image is resized so that the shorter side is 512.
2. 'longer': if the longer side is more than 512, the image is resized so that the longer side is 512.
3. 'shorter_centercrop': if the shorter side is more than 512, the image is resized so that the shorter side is 512.
Then the center 512 x 512 after resized is used for evaluation.
4. 'None': no preprocessing
""",
)
parser.set_defaults(func=evaluate)
def stringify_cmd(cmd_ls):
cmd = ""
for string in cmd_ls:
cmd += string + " "
return cmd
## TODO
def evaluate(args):
args_dict = vars(args)
abs_path_main = os.path.abspath(f'{CUR_DIR}/../launch/evaluate.py')
abs_path_json = os.path.abspath(f'{CUR_DIR}/../VBench2_full_info.json')
cmd = [
'python3',
abs_path_main,
'--output_path', os.path.join(args_dict['output_path'], args_dict['dimension']),
'--full_json_dir', abs_path_json,
'--videos_path', args_dict['videos_path'],
'--dimension', args_dict['dimension'],
'--mode', args_dict['mode'],
'--imaging_quality_preprocessing_mode', 'longer'
]
subprocess.run(cmd)
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